feat: integrate basin force estimator (pre-force) for 7x12 sensor

devkit/build/je-skin-devkit-server/EXE-00.toc

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+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\random\\src\\distributions\\LICENSE.md',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\_core\\src\\umath\\svml\\LICENSE',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\_core\\src\\umath\\svml\\LICENSE',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\random\\LICENSE.md',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\random\\LICENSE.md',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\METADATA',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\METADATA',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\random\\src\\mt19937\\LICENSE.md',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\random\\src\\mt19937\\LICENSE.md',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\_core\\src\\highway\\LICENSE',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\_core\\src\\highway\\LICENSE',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\random\\src\\philox\\LICENSE.md',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\random\\src\\philox\\LICENSE.md',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\fft\\pocketfft\\LICENSE.md',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\fft\\pocketfft\\LICENSE.md',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\licenses\\numpy\\linalg\\lapack_lite\\LICENSE.txt',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\licenses\\numpy\\linalg\\lapack_lite\\LICENSE.txt',
+   'DATA'),
+  ('numpy-2.4.4.dist-info\\RECORD',
+   'C:\\Python314\\Lib\\site-packages\\numpy-2.4.4.dist-info\\RECORD',
+   'DATA'),
+  ('base_library.zip',
+   'D:\\JE-Skin\\devkit\\build\\je-skin-devkit-server\\base_library.zip',
+   'DATA')],
+ 'python314.dll',
+ False,
+ False,
+ False,
+ [],
+ None,
+ None,
+ None)

devkit/build/je-skin-devkit-server/warn-je-skin-devkit-server.txt

@@ -0,0 +1,245 @@
+
+This file lists modules PyInstaller was not able to find. This does not
+necessarily mean these modules are required for running your program. Both
+Python's standard library and 3rd-party Python packages often conditionally
+import optional modules, some of which may be available only on certain
+platforms.
+
+Types of import:
+* top-level: imported at the top-level - look at these first
+* conditional: imported within an if-statement
+* delayed: imported within a function
+* optional: imported within a try-except-statement
+
+IMPORTANT: Do NOT post this list to the issue-tracker. Use it as a basis for
+            tracking down the missing module yourself. Thanks!
+
+missing module named pwd - imported by posixpath (delayed, conditional, optional), subprocess (delayed, conditional, optional), shutil (delayed, optional), tarfile (optional), pathlib (optional), netrc (delayed, optional), http.server (delayed, optional)
+missing module named grp - imported by subprocess (delayed, conditional, optional), shutil (delayed, optional), tarfile (optional), pathlib (optional)
+missing module named 'collections.abc' - imported by typing (top-level), tracemalloc (top-level), traceback (top-level), _colorize (top-level), selectors (top-level), logging (top-level), http.client (top-level), importlib.resources.readers (top-level), inspect (top-level), multiprocessing.managers (top-level), typing_extensions (top-level), asyncio.base_events (top-level), asyncio.coroutines (top-level), grpc.aio._metadata (top-level), google.protobuf.internal.containers (top-level), google.protobuf.internal.well_known_types (top-level), numpy._typing._array_like (top-level), numpy._typing._nested_sequence (conditional), numpy._typing._shape (top-level), numpy._typing._dtype_like (top-level), numpy.lib._function_base_impl (top-level), _pyrepl.types (top-level), numpy.lib._npyio_impl (top-level), numpy.random._common (top-level), numpy.random._generator (top-level), numpy.random.bit_generator (top-level), numpy.random.mtrand (top-level), numpy.polynomial._polybase (top-level), xml.etree.ElementTree (top-level)
+missing module named _posixsubprocess - imported by subprocess (conditional), multiprocessing.util (delayed)
+missing module named fcntl - imported by subprocess (optional), pathlib._os (optional)
+missing module named _posixshmem - imported by multiprocessing.resource_tracker (conditional), multiprocessing.shared_memory (conditional)
+missing module named _scproxy - imported by urllib.request (conditional)
+missing module named posix - imported by os (conditional, optional), posixpath (optional), shutil (conditional), importlib._bootstrap_external (conditional), pathlib._os (optional), _pyrepl.trace (conditional)
+missing module named resource - imported by posix (top-level)
+missing module named _frozen_importlib_external - imported by importlib._bootstrap (delayed), importlib (optional), importlib.abc (optional), zipimport (top-level)
+excluded module named _frozen_importlib - imported by importlib (optional), importlib.abc (optional), zipimport (top-level)
+missing module named multiprocessing.BufferTooShort - imported by multiprocessing (top-level), multiprocessing.connection (top-level)
+missing module named multiprocessing.AuthenticationError - imported by multiprocessing (top-level), multiprocessing.forkserver (top-level), multiprocessing.connection (top-level)
+missing module named multiprocessing.get_context - imported by multiprocessing (top-level), multiprocessing.pool (top-level), multiprocessing.managers (top-level), multiprocessing.sharedctypes (top-level)
+missing module named multiprocessing.TimeoutError - imported by multiprocessing (top-level), multiprocessing.pool (top-level)
+missing module named multiprocessing.set_start_method - imported by multiprocessing (top-level), multiprocessing.spawn (top-level)
+missing module named multiprocessing.get_start_method - imported by multiprocessing (top-level), multiprocessing.spawn (top-level)
+missing module named pyimod02_importers - imported by C:\Python314\Lib\site-packages\PyInstaller\hooks\rthooks\pyi_rth_pkgutil.py (delayed)
+missing module named _dummy_thread - imported by numpy._core.arrayprint (optional)
+missing module named 'numpy_distutils.cpuinfo' - imported by numpy.f2py.diagnose (delayed, conditional, optional)
+missing module named 'numpy_distutils.fcompiler' - imported by numpy.f2py.diagnose (delayed, conditional, optional)
+missing module named 'numpy_distutils.command' - imported by numpy.f2py.diagnose (delayed, conditional, optional)
+missing module named numpy_distutils - imported by numpy.f2py.diagnose (delayed, optional)
+missing module named charset_normalizer - imported by numpy.f2py.crackfortran (optional)
+missing module named vms_lib - imported by platform (delayed, optional)
+missing module named 'java.lang' - imported by platform (delayed, optional)
+missing module named java - imported by platform (delayed)
+missing module named psutil - imported by numpy.testing._private.utils (delayed, optional)
+missing module named termios - imported by tty (top-level), _pyrepl.pager (delayed, optional)
+missing module named readline - imported by cmd (delayed, conditional, optional), code (delayed, conditional, optional), pdb (delayed, conditional, optional), rlcompleter (optional)
+missing module named win32pdh - imported by numpy.testing._private.utils (delayed, conditional)
+missing module named _typeshed - imported by numpy.random.bit_generator (top-level)
+missing module named numpy.random.RandomState - imported by numpy.random (top-level), numpy.random._generator (top-level)
+missing module named threadpoolctl - imported by numpy.lib._utils_impl (delayed, optional)
+missing module named numpy._core.zeros - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.vstack - imported by numpy._core (top-level), numpy.lib._shape_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.void - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.vecmat - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.vecdot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.ushort - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.unsignedinteger - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ulonglong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ulong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uintp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uintc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uint64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint32 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint16 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ubyte - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.trunc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.true_divide - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.transpose - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._function_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.trace - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.timedelta64 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.tensordot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.tanh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.tan - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.swapaxes - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.sum - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.subtract - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.str_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.square - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.sqrt - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.spacing - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.sort - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.sinh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.single - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.signedinteger - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.signbit - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.sign - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.short - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.rint - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.right_shift - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.result_type - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.remainder - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.reciprocal - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.radians - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.rad2deg - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.prod - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.power - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.positive - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.pi - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.outer - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.ones - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.object_ - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.number - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.not_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.nextafter - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.newaxis - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.negative - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ndarray - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy.lib._utils_impl (top-level), numpy (conditional)
+missing module named numpy._core.multiply - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.moveaxis - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.modf - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.mod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.minimum - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.maximum - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.max - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.matvec - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.matrix_transpose - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.matmul - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.longlong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.longdouble - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.long - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_xor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_or - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_not - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_and - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logaddexp2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logaddexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log10 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log1p - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.linspace - imported by numpy._core (top-level), numpy.lib._index_tricks_impl (top-level), numpy (conditional)
+missing module named numpy._core.less_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.less - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.left_shift - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ldexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.lcm - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.isscalar - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.isnat - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional)
+missing module named numpy._core.isnan - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.isfinite - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.intp - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.integer - imported by numpy._core (conditional), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.intc - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.int64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int32 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int16 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int8 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.inf - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.inexact - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.iinfo - imported by numpy._core (top-level), numpy.lib._twodim_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.hypot - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.hstack - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.heaviside - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.half - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.greater_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.greater - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.gcd - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.frompyfunc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.frexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmin - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmax - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floor_divide - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floating - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.float_power - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.float32 - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.float16 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.finfo - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.fabs - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.expm1 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.exp2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.exp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.euler_gamma - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.errstate - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.empty_like - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.empty - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.e - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.double - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.dot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.divmod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.divide - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.diagonal - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.degrees - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.deg2rad - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.datetime64 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.csingle - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.cross - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.count_nonzero - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.cosh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.cos - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.copysign - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.conjugate - imported by numpy._core (conditional), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.conj - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.complexfloating - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.complex64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.clongdouble - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.character - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ceil - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.cdouble - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.cbrt - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bytes_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.byte - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bool_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_xor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_or - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_count - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_and - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.atleast_3d - imported by numpy._core (top-level), numpy.lib._shape_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.atleast_2d - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.atleast_1d - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.asarray - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._array_utils_impl (top-level), numpy (conditional), numpy.fft._helper (top-level), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.asanyarray - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.array_repr - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional)
+missing module named numpy._core.array2string - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.array - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.argsort - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.arctanh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arctan2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arctan - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arcsinh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arcsin - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arccosh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arccos - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arange - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.amin - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.amax - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.all - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.add - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named yaml - imported by numpy.__config__ (delayed)
+missing module named numpy._distributor_init_local - imported by numpy (optional), numpy._distributor_init (optional)
+missing module named defusedxml - imported by openpyxl.xml (delayed, optional)
+missing module named lxml - imported by openpyxl.xml (delayed, optional)
+missing module named 'defusedxml.ElementTree' - imported by openpyxl.xml.functions (conditional)
+missing module named 'lxml.etree' - imported by openpyxl.xml.functions (conditional)
+missing module named PIL - imported by openpyxl.drawing.image (optional)
+missing module named openpyxl.tests - imported by openpyxl.reader.excel (optional)
+missing module named google.protobuf.pyext._message - imported by google.protobuf.pyext (conditional, optional), google.protobuf.internal.api_implementation (conditional, optional), google.protobuf.descriptor (conditional), google.protobuf.pyext.cpp_message (conditional)
+missing module named google.protobuf.enable_deterministic_proto_serialization - imported by google.protobuf (optional), google.protobuf.internal.api_implementation (optional)
+missing module named google.protobuf.internal._api_implementation - imported by google.protobuf.internal (optional), google.protobuf.internal.api_implementation (optional)
+missing module named grpc_reflection - imported by grpc (optional)
+missing module named grpc_health - imported by grpc (optional)
+missing module named pkg_resources - imported by grpc_tools.protoc (conditional)

package-lock.json

@@ -6,7 +6,7 @@
   "packages": {
     "": {
       "name": "JE-Skin",
-      "version": "0.4.0",
+      "version": "0.3.0",
       "license": "MIT",
       "dependencies": {
         "@tauri-apps/api": "^2",

src-tauri/.cargo/config.toml

@@ -0,0 +1,2 @@
+[registries.kellnr]
+index = "sparse+http://crates.huangyanjie.com/api/v1/crates/"

src-tauri/Cargo.lock

@@ -8,7 +8,10 @@ version = "0.4.0"
 dependencies = [
  "anyhow",
  "async-stream",
+ "async-trait",
  "axum 0.8.9",
+ "chrono",
+ "crc",
  "csv",
  "dirs",
  "eskin-finger-sdk",
@@ -16,6 +19,7 @@ dependencies = [
  "futures-util",
  "humantime",
  "log",
+ "ndarray",
  "prost",
  "prost-types",
  "protoc-bin-vendored",
@@ -1152,6 +1156,8 @@ dependencies = [
 [[package]]
 name = "eskin-finger-sdk"
 version = "0.1.0"
+source = "sparse+http://crates.huangyanjie.com/api/v1/crates/"
+checksum = "341d54dbc70a0fb7cdd04162cdda6ab5735f9a4f717b1921b42c00e8afc37bb9"
 dependencies = [
  "chrono",
  "crc",
@@ -2476,6 +2482,16 @@ version = "0.8.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "47e1ffaa40ddd1f3ed91f717a33c8c0ee23fff369e3aa8772b9605cc1d22f4c3"
 
+[[package]]
+name = "matrixmultiply"
+version = "0.3.10"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a06de3016e9fae57a36fd14dba131fccf49f74b40b7fbdb472f96e361ec71a08"
+dependencies = [
+ "autocfg",
+ "rawpointer",
+]
+
 [[package]]
 name = "memchr"
 version = "2.8.0"
@@ -2565,6 +2581,19 @@ version = "0.10.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "1d87ecb2933e8aeadb3e3a02b828fed80a7528047e68b4f424523a0981a3a084"
 
+[[package]]
+name = "ndarray"
+version = "0.15.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "adb12d4e967ec485a5f71c6311fe28158e9d6f4bc4a447b474184d0f91a8fa32"
+dependencies = [
+ "matrixmultiply",
+ "num-complex",
+ "num-integer",
+ "num-traits",
+ "rawpointer",
+]
+
 [[package]]
 name = "ndk"
 version = "0.9.0"
@@ -2630,12 +2659,30 @@ version = "0.1.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "72ef4a56884ca558e5ddb05a1d1e7e1bfd9a68d9ed024c21704cc98872dae1bb"
 
+[[package]]
+name = "num-complex"
+version = "0.4.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
+dependencies = [
+ "num-traits",
+]
+
 [[package]]
 name = "num-conv"
 version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "cf97ec579c3c42f953ef76dbf8d55ac91fb219dde70e49aa4a6b7d74e9919050"
 
+[[package]]
+name = "num-integer"
+version = "0.1.46"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "7969661fd2958a5cb096e56c8e1ad0444ac2bbcd0061bd28660485a44879858f"
+dependencies = [
+ "num-traits",
+]
+
 [[package]]
 name = "num-traits"
 version = "0.2.19"
@@ -3640,6 +3687,12 @@ version = "0.6.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "20675572f6f24e9e76ef639bc5552774ed45f1c30e2951e1e99c59888861c539"
 
+[[package]]
+name = "rawpointer"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3"
+
 [[package]]
 name = "redox_syscall"
 version = "0.5.18"

src-tauri/Cargo.toml

@@ -17,6 +17,7 @@ crate-type = ["staticlib", "cdylib", "rlib"]
 [features]
 default = []
 devkit = ["dep:tonic", "dep:prost", "dep:prost-types", "dep:async-stream", "dep:dirs"]
+multi-dim = ["dep:ndarray"]
 
 [build-dependencies]
 tauri-build = { version = "2", features = [] }
@@ -36,19 +37,23 @@ async-stream = { version = "0.3", optional = true }
 dirs = { version = "6", optional = true }
 tokio-serial = { version = "5.4.5" }
 tokio = { version = "1.50.0", features = ["full"] }
+async-trait = "0.1.89"
 tokio-util = "0.7.18"
 serde_json = "1"
 fern = { version = "0.7.1", features = ["colored", "date-based"] }
 log = "0.4.29"
 humantime = "2.3.0"
 csv = "1.4.0"
+chrono = "0.4.44"
+crc = "3.4.0"
 axum = { version = "0.8", features = ["ws"] }
 tower-http = { version = "0.6", features = ["cors"] }
 futures-util = "0.3"
-uuid = { version = "1", features = ["v4", "serde"] }
+uuid = { version = "1.23", features = ["v4", "serde"] }
 rand = "0.8"
 reqwest = { version = "0.12", default-features = false, features = ["json", "rustls-tls"] }
-eskin-finger-sdk = { path = "../eskin-finger-sdk" }
+ndarray = { version = "0.15", optional = true }
+eskin-finger-sdk = { version = "0.1.0", registry = "kellnr" }
 
 [target.'cfg(not(any(target_os = "android", target_os = "ios")))'.dependencies]
 tauri-plugin-updater = "2"

src-tauri/resources/model_params.json

@@ -0,0 +1,217 @@
+{
+  "scaler_mean": [
+    1748.7541486595198,
+    1292.5704664084863,
+    669.8700117864961,
+    1617.8798712839798,
+    2104.589811228976,
+    3267.658809002638,
+    3366.4000112252343,
+    2660.981740285495,
+    2656.615909898786,
+    1747.1196048717518,
+    3093.4178032216423,
+    3107.599371386878,
+    4138.929019101607,
+    3778.3928270752654,
+    3495.851920450506,
+    3110.5580063983834,
+    2310.8518456156107,
+    2899.8918261585377,
+    3286.6881442816784,
+    3601.237076948981,
+    2590.9553048586554,
+    2555.2781425978933,
+    2004.8764850049579,
+    1333.8961665824775,
+    2090.217507623805,
+    0.363302046990876,
+    0.2506597877765041,
+    0.12741811820991292,
+    0.32195020821212794,
+    0.43317540002685884,
+    0.7725988160553472,
+    0.791227193907261,
+    0.5957799875116326,
+    0.5873844015441929,
+    0.35855586659016336,
+    0.7267512979672636,
+    0.7214172326166498,
+    1.0,
+    0.9089476753706724,
+    0.8226695360434777,
+    0.7208819781157673,
+    0.5152795489332506,
+    0.6711736481838434,
+    0.7782925265622518,
+    0.8648282061576593,
+    0.5787625095682526,
+    0.5752349727514727,
+    0.43456864805018935,
+    0.27668525082454587,
+    0.47414670304783574,
+    4138.929019101607,
+    64531.08183195824,
+    175620.92531477427,
+    22.847729696357412,
+    14.671691561018095,
+    0.07533558084489102,
+    12446.865764906175,
+    47945.287047950456,
+    2.8973185436828195,
+    10.774373017335268,
+    3.472192991899253,
+    -0.013941562889309035,
+    0.09672681097411825,
+    0.5067195499928454,
+    0.755407246398865,
+    0.03711810817384146,
+    11.154421806888552,
+    64500.8986854629
+  ],
+  "scaler_scale": [
+    1458.5456651154973,
+    1319.8585484401115,
+    798.8535944732339,
+    1467.8233720347457,
+    1637.8964913406842,
+    1330.3349975112737,
+    1391.430499849884,
+    1444.166940848846,
+    1630.948040054198,
+    1406.2203759964518,
+    1289.9699402243327,
+    1442.0533616965101,
+    1437.7214049715994,
+    1393.522474091575,
+    1468.6421185157626,
+    1449.3479990930084,
+    1293.2464048717598,
+    1331.2560392843097,
+    1326.1289536453178,
+    1357.3405110533047,
+    1452.4854193036483,
+    1348.4425883366337,
+    1318.1429721243371,
+    1059.93845215709,
+    1114.1647557935548,
+    0.2395898634701691,
+    0.21706962815914935,
+    0.13523106483202163,
+    0.23880331588910964,
+    0.24830003478347082,
+    0.1464527498295455,
+    0.15391677914992113,
+    0.18125664726966026,
+    0.2326879002599809,
+    0.23502163992653513,
+    0.13026800431597335,
+    0.15563022147466685,
+    1.0,
+    0.09922737602626737,
+    0.18291931318098986,
+    0.15401181704844932,
+    0.2143892844194339,
+    0.16856049162074294,
+    0.15902500893917185,
+    0.18285009098439925,
+    0.17264751056304276,
+    0.21090366624550771,
+    0.16802111677577075,
+    0.19264329284433157,
+    0.19589977001187556,
+    1437.7214049715994,
+    32602.413979370118,
+    95845.11969895993,
+    3.426376344472427,
+    3.408382770733738,
+    0.033353666248921464,
+    5505.629576226806,
+    25703.01200969283,
+    0.4599551450527747,
+    2.978321440052941,
+    0.3916581766443181,
+    0.06096090153067211,
+    0.07864618660494935,
+    0.0344984508436715,
+    0.17668176728315207,
+    0.18905119470509504,
+    5352.30503788098,
+    32297.31796957845
+  ],
+  "ridge_coef": [
+    7.4424310127566695,
+    13.345966730219576,
+    2.351840055857306,
+    6.088230738742203,
+    -10.030964629299273,
+    3.876136979406362,
+    -11.251608537526174,
+    16.84502390958064,
+    -2.093552796584439,
+    -5.784923711493545,
+    -6.67830546424787,
+    -4.654052249161928,
+    6.038218458133514,
+    9.82412450487401,
+    -6.200667839175651,
+    -0.3133364534713342,
+    -8.75036029102127,
+    12.785901861589027,
+    -3.7296377182327123,
+    6.546167384121816,
+    -4.984129287282208,
+    8.311396481777527,
+    -0.6248790895663127,
+    2.69008779623183,
+    12.996047839696784,
+    -2.2609944767610504,
+    -5.131537716982507,
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+    -5.197736884253156,
+    4.556854888903703,
+    -0.8642438099006351,
+    6.327731485629085,
+    -5.157281763422745,
+    0.10691827520622764,
+    4.656962972053113,
+    3.2628870750114887,
+    4.033159141354671,
+    0.0,
+    -2.9206404009765268,
+    1.8683691849941264,
+    2.408006875407745,
+    7.250310827671452,
+    -3.97015207422554,
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+    -3.459346094204882,
+    2.4407660203169255,
+    -2.872982666400644,
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+    -1.3374700235689694,
+    -7.9533345474852295,
+    6.038063637368508,
+    1.615806581558555,
+    95785.62883805836,
+    0.12233606167692031,
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+    2.2023033069961873,
+    8.776787743985668,
+    -0.16714060634667535,
+    -2.751671223554021,
+    0.2511944267079865,
+    6.13561607395193,
+    2.85703108671782,
+    -0.11255626089468472,
+    -0.9017242341101542,
+    -0.627291200283328,
+    3.4664885582435883,
+    0.02591345630626686,
+    0.5530407299425606
+  ],
+  "ridge_intercept": 175620.9253147744,
+  "n_features": 68,
+  "noise_threshold": 15.0,
+  "contact_threshold": 20.0,
+  "ema_alpha": 0.9
+}

src-tauri/src/commands/serial.rs

@@ -1,18 +1,27 @@
+use crate::serial_core::codecs::tactile_a::{
+    export_recording_csv, TactileACodec, TactileACsvImporter, TactileAHandler,
+};
 use crate::serial_core::error::SerialError;
-use crate::serial_core::record::{self, FingerRecording};
+use crate::serial_core::record::CsvImporter;
-use crate::serial_core::serial;
+use crate::serial_core::serial::{PollMode, TactileAPollRequester};
-use eskin_finger_sdk::device::EskinDevice;
+use crate::serial_core::{serial, TactileARecording};
 use log::info;
 use serde::Serialize;
+use std::fs::File;
 use std::io::Cursor;
 use std::path::{Path, PathBuf};
 use std::sync::{Arc, Mutex};
-use std::time::{SystemTime, UNIX_EPOCH};
+use std::time::{Duration, Instant, SystemTime, UNIX_EPOCH};
 use tauri::{async_runtime::JoinHandle, AppHandle, Manager, State};
-use tokio_serial::available_ports;
+use tokio_serial::{available_ports, SerialPortBuilderExt};
 use tokio_util::sync::CancellationToken;
 
-type SharedRecording = Arc<Mutex<FingerRecording>>;
+const DEFAULT_TACTILE_COLS: usize = 7;
+const DEFAULT_TACTILE_ROWS: usize = 12;
+const DEFAULT_TACTILE_POLL_INTERVAL_MS: u64 = 10;
+const DEFAULT_TACTILE_REPLY_TIMEOUT_MS: u64 = 140;
+
+type SharedTactileRecording = Arc<Mutex<TactileARecording>>;
 
 #[derive(Serialize)]
 #[serde(rename_all = "camelCase")]
@@ -58,18 +67,18 @@ struct SerialSession {
     port: String,
     cancel: CancellationToken,
     task: JoinHandle<()>,
-    current_record: SharedRecording,
+    current_record: SharedTactileRecording,
 }
 
 #[derive(Default)]
 pub struct SerialConnectionState {
     session: Mutex<Option<SerialSession>>,
-    last_record: Mutex<Option<SharedRecording>>,
+    last_record: Mutex<Option<SharedTactileRecording>>,
 }
 
 pub async fn shutdown_active_session(
     state: &SerialConnectionState,
-) -> Result<Option<(String, SharedRecording)>, SerialError> {
+) -> Result<Option<(String, SharedTactileRecording)>, SerialError> {
     let session = {
         let mut guard = state.session.lock().map_err(|_| SerialError::StateError)?;
         guard.take()
@@ -139,41 +148,62 @@ pub async fn serial_connect(
     }
 
     let cancel = CancellationToken::new();
-    let current_record = Arc::new(Mutex::new(FingerRecording::new()));
+    let current_record = Arc::new(Mutex::new(TactileARecording::new()));
     let task_record = current_record.clone();
     let task_cancel = cancel.clone();
     let task_app = app.clone();
     let task_port_name = port_name.clone();
 
+    let port = tokio_serial::new(&port_name, 921600)
+        .open_native_async()
+        .map_err(|_| SerialError::OpenError)?;
+    let session_started_at = Instant::now();
+
     let task = tauri::async_runtime::spawn(async move {
-        // Open device using SDK
+        let codec = TactileACodec::new(DEFAULT_TACTILE_COLS, DEFAULT_TACTILE_ROWS);
-        let session = match serial::open_device(&task_port_name) {
+        let handler = TactileAHandler;
-            Ok(s) => s,
+        let poll_mode = PollMode::Enabled(Box::new(TactileAPollRequester::new(
-            Err(e) => {
+            Duration::from_millis(DEFAULT_TACTILE_POLL_INTERVAL_MS),
-                eprintln!("Failed to open device: {e}");
+            DEFAULT_TACTILE_COLS,
-                cleanup_session(&task_app, &task_port_name, task_record).await;
+            DEFAULT_TACTILE_ROWS,
-                return;
+            Duration::from_millis(DEFAULT_TACTILE_REPLY_TIMEOUT_MS),
-            }
+        )));
-        };
 
-        let mut device = session.device;
+        if let Err(error) = serial::run_serial_with_poll(
-
-        // Run stream with recording
-        if let Err(error) = serial::run_stream_with_record(
             task_app.clone(),
-            &mut device,
+            port,
-            task_cancel,
+            codec,
+            handler,
+            session_started_at,
             task_record.clone(),
+            task_cancel,
+            poll_mode,
         )
         .await
         {
             eprintln!("serial task exited with error: {error}");
         }
 
-        // Close device
+        let manager = task_app.state::<SerialConnectionState>();
-        let _ = device.close();
+        if let Ok(mut last_record) = manager.last_record.lock() {
+            *last_record = Some(task_record);
+        }
 
-        cleanup_session(&task_app, &task_port_name, task_record).await;
+        let mut session = match manager.session.lock() {
+            Ok(session) => session,
+            Err(_) => return,
+        };
+
+        {
+            let should_clear = session
+                .as_ref()
+                .map(|current| current.port.as_str() == task_port_name.as_str())
+                .unwrap_or(false);
+
+            if should_clear {
+                session.take();
+            }
+        }
     });
 
     let mut session = state.session.lock().map_err(|_| SerialError::StateError)?;
@@ -197,31 +227,6 @@ pub async fn serial_connect(
     })
 }
 
-async fn cleanup_session(
-    app: &AppHandle,
-    port_name: &str,
-    record: SharedRecording,
-) {
-    let manager = app.state::<SerialConnectionState>();
-    if let Ok(mut last_record) = manager.last_record.lock() {
-        *last_record = Some(record);
-    }
-
-    let mut session = match manager.session.lock() {
-        Ok(session) => session,
-        Err(_) => return,
-    };
-
-    let should_clear = session
-        .as_ref()
-        .map(|current| current.port.as_str() == port_name)
-        .unwrap_or(false);
-
-    if should_clear {
-        session.take();
-    }
-}
-
 #[tauri::command]
 pub async fn serial_disconnect(
     state: State<'_, SerialConnectionState>,
@@ -288,8 +293,8 @@ pub fn serial_export_csv_to_path(
     state: State<'_, SerialConnectionState>,
 ) -> Result<SerialExportResponse, SerialError> {
     let output_path = resolve_export_path(file_path)?;
-    let rec = resolve_record_for_export(&state)?;
+    let record = resolve_record_for_export(&state)?;
-    let frame_count = write_record_to_csv(rec, &output_path)?;
+    let frame_count = write_record_to_csv(record, &output_path)?;
     let path = output_path.display().to_string();
 
     info!("csv exported to {path}, frame_count={frame_count}");
@@ -306,20 +311,22 @@ pub fn serial_import_csv(
     file_name: String,
     csv_content: String,
 ) -> Result<SerialImportResponse, SerialError> {
-    let packets = record::import_csv(Cursor::new(csv_content.into_bytes()))
+    let mut importer = TactileACsvImporter::new(file_name.as_str());
+    let packets = importer
+        .load(Cursor::new(csv_content.into_bytes()))
         .map_err(|_| SerialError::ImportError)?;
 
     if packets.is_empty() {
         return Err(SerialError::NoRecordedData);
     }
 
-    let channel_count = 1; // fz is a single value per sample
+    let channel_count = packets.first().map(|item| item.data.len()).unwrap_or(0);
     let frame_count = packets.len();
     let frames = packets
         .into_iter()
         .map(|packet| SerialImportFrame {
-            data: vec![packet.fz as i32],
+            data: packet.data,
-            dts_ms: packet.timestamp_us / 1000,
+            dts_ms: packet.dts_ms,
         })
         .collect();
 
@@ -348,7 +355,7 @@ pub fn serial_import_csv_from_path(file_path: String) -> Result<SerialImportResp
 
 fn resolve_record_for_export(
     state: &State<'_, SerialConnectionState>,
-) -> Result<SharedRecording, SerialError> {
+) -> Result<SharedTactileRecording, SerialError> {
     let current_record = {
         let session = state.session.lock().map_err(|_| SerialError::StateError)?;
         session
@@ -399,7 +406,7 @@ fn snapshot_record_frame_count(
 }
 
 fn write_record_to_csv(
-    record: SharedRecording,
+    record: SharedTactileRecording,
     output_path: &Path,
 ) -> Result<usize, SerialError> {
     if let Some(parent) = output_path.parent() {
@@ -408,14 +415,14 @@ fn write_record_to_csv(
         }
     }
 
-    let file = std::fs::File::create(output_path).map_err(|_| SerialError::ExportError)?;
+    let mut file = File::create(output_path).map_err(|_| SerialError::ExportError)?;
     let frame_count = {
         let recording = record.lock().map_err(|_| SerialError::StateError)?;
         if recording.frames.is_empty() {
             return Err(SerialError::NoRecordedData);
         }
 
-        record::export_recording_csv(&recording, file).map_err(|_| SerialError::ExportError)?;
+        export_recording_csv(&recording, &mut file).map_err(|_| SerialError::ExportError)?;
         recording.frames.len()
     };
 

src-tauri/src/serial_core/basin_force_estimator.rs

@@ -0,0 +1,397 @@
+//! 7×12 柔性压力点阵力估计 - Rust 实现
+//!
+//! 与 Python `basin_feature_extractor.py` 完全对齐。
+//! 内嵌 `model_params.json`，对每帧 7×12 传感器数据提取 68 维特征并用
+//! StandardScaler + Ridge 回归估计法向力 Fz。
+
+use serde::Deserialize;
+
+// ───────────────── 常量 ─────────────────
+
+const ROWS: usize = 7;
+const COLS: usize = 12;
+const ROI_RADIUS: usize = 2;
+const ROI_SIZE: usize = 2 * ROI_RADIUS + 1; // 5
+const N_FEATURES: usize = 68; // 25 + 25 + 18
+
+// ───────────────── 模型参数 JSON（编译时嵌入）─────────────────
+
+const MODEL_PARAMS_JSON: &str = include_str!("../../resources/model_params.json");
+
+// ───────────────── 模型参数反序列化 ─────────────────
+
+#[derive(Debug, Deserialize)]
+struct ModelParams {
+    scaler_mean: Vec<f64>,
+    scaler_scale: Vec<f64>,
+    ridge_coef: Vec<f64>,
+    ridge_intercept: f64,
+    n_features: usize,
+    noise_threshold: f64,
+    contact_threshold: f64,
+    ema_alpha: f64,
+}
+
+// ───────────────── 估算器 ─────────────────
+
+pub struct BasinForceEstimator {
+    // 模型参数
+    scaler_mean: [f64; N_FEATURES],
+    scaler_scale: [f64; N_FEATURES],
+    ridge_coef: [f64; N_FEATURES],
+    ridge_intercept: f64,
+    // 超参数
+    noise_threshold: f64,
+    contact_threshold: f64,
+    ema_alpha: f64,
+    // 时序状态（需要可变）
+    prev_roi_sum: f64,
+    ema_sum: f64,
+    first_frame: bool,
+}
+
+impl BasinForceEstimator {
+    /// 使用编译时内嵌的 model_params.json 创建估算器
+    pub fn new() -> Self {
+        Self::from_json_str(MODEL_PARAMS_JSON)
+            .expect("内嵌 model_params.json 加载失败")
+    }
+
+    pub fn from_json_str(json: &str) -> Result<Self, Box<dyn std::error::Error>> {
+        let p: ModelParams = serde_json::from_str(json)?;
+        if p.n_features != N_FEATURES {
+            return Err(format!(
+                "模型特征维度不匹配: 期望 {}, 实际 {}",
+                N_FEATURES, p.n_features
+            )
+            .into());
+        }
+        let mut scaler_mean = [0.0; N_FEATURES];
+        let mut scaler_scale = [0.0; N_FEATURES];
+        let mut ridge_coef = [0.0; N_FEATURES];
+        scaler_mean.copy_from_slice(&p.scaler_mean);
+        scaler_scale.copy_from_slice(&p.scaler_scale);
+        ridge_coef.copy_from_slice(&p.ridge_coef);
+
+        Ok(Self {
+            scaler_mean,
+            scaler_scale,
+            ridge_coef,
+            ridge_intercept: p.ridge_intercept,
+            noise_threshold: p.noise_threshold,
+            contact_threshold: p.contact_threshold,
+            ema_alpha: p.ema_alpha,
+            prev_roi_sum: 0.0,
+            ema_sum: 0.0,
+            first_frame: true,
+        })
+    }
+
+    pub fn reset(&mut self) {
+        self.prev_roi_sum = 0.0;
+        self.ema_sum = 0.0;
+        self.first_frame = true;
+    }
+
+    pub fn predict_frame(&mut self, frame: &[f64; 84]) -> f64 {
+        let features = self.extract_features(frame);
+        self.ridge_predict(&features)
+    }
+
+    // ───────────── 特征提取 ─────────────
+
+    fn extract_features(&mut self, raw: &[f64; 84]) -> [f64; N_FEATURES] {
+        let mut x = [[0.0f64; COLS]; ROWS];
+        let mut max_value = 0.0f64;
+        for r in 0..ROWS {
+            for c in 0..COLS {
+                let v = raw[r * COLS + c].max(0.0);
+                x[r][c] = v;
+                if v > max_value {
+                    max_value = v;
+                }
+            }
+        }
+
+        if max_value < self.contact_threshold {
+            self.update_temporal(0.0);
+            return [0.0; N_FEATURES];
+        }
+
+        let mut peak_row = 0usize;
+        let mut peak_col = 0usize;
+        for r in 0..ROWS {
+            for c in 0..COLS {
+                if x[r][c] >= x[peak_row][peak_col] {
+                    peak_row = r;
+                    peak_col = c;
+                }
+            }
+        }
+
+        let roi = self.extract_roi(&x, peak_row, peak_col);
+        self.compute_features(&x, &roi, max_value, peak_row, peak_col)
+    }
+
+    fn extract_roi(
+        &self,
+        x: &[[f64; COLS]; ROWS],
+        pr: usize,
+        pc: usize,
+    ) -> [[f64; ROI_SIZE]; ROI_SIZE] {
+        let r = ROI_RADIUS as isize;
+        let mut roi = [[0.0f64; ROI_SIZE]; ROI_SIZE];
+
+        let r_start = (pr as isize - r).max(0) as usize;
+        let r_end = (pr + ROI_RADIUS + 1).min(ROWS);
+        let c_start = (pc as isize - r).max(0) as usize;
+        let c_end = (pc + ROI_RADIUS + 1).min(COLS);
+
+        let roi_r_start = (r_start as isize - (pr as isize - r)).max(0) as usize;
+        let roi_c_start = (c_start as isize - (pc as isize - r)).max(0) as usize;
+
+        for (i, ri) in (r_start..r_end).enumerate() {
+            for (j, ci) in (c_start..c_end).enumerate() {
+                roi[roi_r_start + i][roi_c_start + j] = x[ri][ci];
+            }
+        }
+        roi
+    }
+
+    fn compute_features(
+        &mut self,
+        x: &[[f64; COLS]; ROWS],
+        roi: &[[f64; ROI_SIZE]; ROI_SIZE],
+        max_value: f64,
+        peak_row: usize,
+        peak_col: usize,
+    ) -> [f64; N_FEATURES] {
+        let center = ROI_RADIUS;
+        let mut feat = [0.0f64; N_FEATURES];
+        let mut idx = 0;
+
+        // ROI 原始值 (25维)
+        for r in 0..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                feat[idx] = roi[r][c];
+                idx += 1;
+            }
+        }
+
+        // ROI 归一化形状 (25维)
+        for r in 0..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                feat[idx] = if max_value > 0.0 {
+                    roi[r][c] / max_value
+                } else {
+                    0.0
+                };
+                idx += 1;
+            }
+        }
+
+        // roi_sum, global_sum
+        let mut roi_sum = 0.0f64;
+        for r in 0..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                roi_sum += roi[r][c];
+            }
+        }
+        let mut global_sum = 0.0f64;
+        for r in 0..ROWS {
+            for c in 0..COLS {
+                global_sum += x[r][c];
+            }
+        }
+
+        // active_area
+        let thr = self.noise_threshold.max(0.05 * max_value);
+        let mut active_area = 0.0f64;
+        for r in 0..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                if roi[r][c] > thr {
+                    active_area += 1.0;
+                }
+            }
+        }
+
+        let participation = if max_value > 0.0 {
+            roi_sum / max_value
+        } else {
+            0.0
+        };
+        let concentration = if roi_sum > 0.0 {
+            max_value / roi_sum
+        } else {
+            0.0
+        };
+
+        // ring1_sum (上下左右4点)
+        let ring1_positions = [
+            (center - 1, center),
+            (center + 1, center),
+            (center, center - 1),
+            (center, center + 1),
+        ];
+        let ring1_sum: f64 = ring1_positions.iter().map(|&(r, c)| roi[r][c]).sum();
+
+        // ring2_sum (除中心和ring1外)
+        let mut ring2_sum = 0.0f64;
+        for r in 0..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                if (r, c) == (center, center) {
+                    continue;
+                }
+                if ring1_positions.contains(&(r, c)) {
+                    continue;
+                }
+                ring2_sum += roi[r][c];
+            }
+        }
+
+        let ring1_ratio = if max_value > 0.0 {
+            ring1_sum / max_value
+        } else {
+            0.0
+        };
+        let ring2_ratio = if max_value > 0.0 {
+            ring2_sum / max_value
+        } else {
+            0.0
+        };
+
+        // spread
+        let spread = if roi_sum > 0.0 {
+            let mut s = 0.0f64;
+            for r in 0..ROI_SIZE {
+                for c in 0..ROI_SIZE {
+                    let dr = r as f64 - center as f64;
+                    let dc = c as f64 - center as f64;
+                    s += (dr * dr + dc * dc) * roi[r][c];
+                }
+            }
+            s / roi_sum
+        } else {
+            0.0
+        };
+
+        // asym_x
+        let mut left_sum = 0.0f64;
+        let mut right_sum = 0.0f64;
+        for r in 0..ROI_SIZE {
+            for c in 0..center {
+                left_sum += roi[r][c];
+            }
+            for c in (center + 1)..ROI_SIZE {
+                right_sum += roi[r][c];
+            }
+        }
+        let asym_x = if roi_sum > 0.0 {
+            (right_sum - left_sum) / roi_sum
+        } else {
+            0.0
+        };
+
+        // asym_y
+        let mut up_sum = 0.0f64;
+        let mut down_sum = 0.0f64;
+        for r in 0..center {
+            for c in 0..ROI_SIZE {
+                up_sum += roi[r][c];
+            }
+        }
+        for r in (center + 1)..ROI_SIZE {
+            for c in 0..ROI_SIZE {
+                down_sum += roi[r][c];
+            }
+        }
+        let asym_y = if roi_sum > 0.0 {
+            (down_sum - up_sum) / roi_sum
+        } else {
+            0.0
+        };
+
+        // 位置
+        let peak_row_norm = peak_row as f64 / (ROWS - 1) as f64;
+        let peak_col_norm = peak_col as f64 / (COLS - 1) as f64;
+
+        // near_edge
+        let r = ROI_RADIUS as isize;
+        let near_edge = if (peak_row as isize) < r
+            || peak_row >= ROWS - ROI_RADIUS
+            || (peak_col as isize) < r
+            || peak_col >= COLS - ROI_RADIUS
+        {
+            1.0
+        } else {
+            0.0
+        };
+
+        // 时序特征
+        let delta_sum = roi_sum - self.prev_roi_sum;
+        if self.first_frame {
+            self.ema_sum = roi_sum;
+            self.first_frame = false;
+        } else {
+            self.ema_sum = self.ema_alpha * self.ema_sum + (1.0 - self.ema_alpha) * roi_sum;
+        }
+        self.prev_roi_sum = roi_sum;
+
+        let scalars = [
+            max_value,
+            roi_sum,
+            global_sum,
+            active_area,
+            participation,
+            concentration,
+            ring1_sum,
+            ring2_sum,
+            ring1_ratio,
+            ring2_ratio,
+            spread,
+            asym_x,
+            asym_y,
+            peak_row_norm,
+            peak_col_norm,
+            near_edge,
+            delta_sum,
+            self.ema_sum,
+        ];
+        for &v in &scalars {
+            feat[idx] = v;
+            idx += 1;
+        }
+
+        debug_assert_eq!(idx, N_FEATURES);
+        feat
+    }
+
+    fn update_temporal(&mut self, roi_sum: f64) {
+        self.prev_roi_sum = roi_sum;
+        if self.first_frame {
+            self.ema_sum = roi_sum;
+            self.first_frame = false;
+        } else {
+            self.ema_sum = self.ema_alpha * self.ema_sum + (1.0 - self.ema_alpha) * roi_sum;
+        }
+    }
+
+    // ───────────── 推理 ─────────────
+
+    fn ridge_predict(&self, features: &[f64; N_FEATURES]) -> f64 {
+        let mut scaled = [0.0f64; N_FEATURES];
+        for i in 0..N_FEATURES {
+            let s = self.scaler_scale[i];
+            scaled[i] = if s.abs() > 1e-12 {
+                (features[i] - self.scaler_mean[i]) / s
+            } else {
+                0.0
+            };
+        }
+        let mut y = self.ridge_intercept;
+        for i in 0..N_FEATURES {
+            y += self.ridge_coef[i] * scaled[i];
+        }
+        y
+    }
+}

src-tauri/src/serial_core/codec.rs

@@ -0,0 +1,6 @@
+use crate::serial_core::error::CodecError;
+use std::time::Instant;
+pub trait Codec<F> {
+    fn decode(&mut self, input: &[u8], session_started_at: Instant) -> Result<Vec<F>, CodecError>;
+    fn encode(&self, frame: &F) -> Result<Vec<u8>, CodecError>;
+}

src-tauri/src/serial_core/codecs/mod.rs

@@ -0,0 +1,5 @@
+use crate::serial_core::{frame::TestFrame, record::Recording};
+
+pub mod test;
+pub mod tactile_a;
+pub type TestRecording = Recording<TestFrame>;

src-tauri/src/serial_core/codecs/tactile_a.rs

@@ -0,0 +1,383 @@
+use crate::serial_core::error::CodecError;
+use crate::serial_core::frame::{
+    FrameHandler, TactileAFrameMetaData, TactileARepFrame, TactileAReqFrame,
+};
+use crate::serial_core::record::{write_csv, CsvExporter, CsvImporter, RecordedFrame, Recording};
+use crate::serial_core::utils::{calc_crc8_itu, elapsed_millis};
+use crate::serial_core::{
+    codec::Codec,
+    frame::{TactileAFrame, TactileAFrameStatusCode},
+};
+use async_trait::async_trait;
+use csv::StringRecord;
+use anyhow::anyhow;
+use std::io::Read;
+use log::{debug, info};
+
+const FRAME_BUFFER_MIN_LENGTH: usize = 15;
+
+pub struct TactileACodec {
+    buffer: Vec<u8>,
+    expected_data_len: usize,
+}
+
+pub struct TactileACsvExporter {
+    channels: usize,
+}
+
+pub struct TactileACsvImporter {
+    channels: usize,
+    data_row: usize,
+    packets: Vec<TactileADataPacket>,
+}
+
+pub struct TactileAHandler;
+
+#[derive(Clone)]
+pub struct TactileADataPacket {
+    pub data: Vec<i32>,
+    pub dts_ms: u64,
+}
+
+impl From<u8> for TactileAFrameStatusCode {
+    fn from(value: u8) -> Self {
+        match value {
+            0 => TactileAFrameStatusCode::Success,
+            _ => TactileAFrameStatusCode::Failure,
+        }
+    }
+}
+
+impl TryFrom<&TactileARepFrame> for TactileADataPacket {
+    type Error = CodecError;
+    fn try_from(value: &TactileARepFrame) -> Result<TactileADataPacket, Self::Error> {
+        let data = TactileACodec::parse_data_frame(&value.payload)?;
+        let dts_ms = value.dts_ms;
+        Ok(TactileADataPacket {
+            data: data,
+            dts_ms: dts_ms,
+        })
+    }
+}
+
+impl TactileACodec {
+    pub fn new(cols: usize, rows: usize) -> TactileACodec {
+        Self {
+            buffer: Vec::new(),
+            expected_data_len: cols * rows * 2,
+        }
+    }
+
+    pub fn parse_data_frame(data: &[u8]) -> Result<Vec<i32>, CodecError> {
+        if data.len() % 2 != 0 {
+            return Err(CodecError::InvalidLength);
+        }
+
+        let vals: Vec<i32> = data
+            .chunks_exact(2)
+            .map(|chunk| {
+                let raw = u16::from_le_bytes([chunk[0], chunk[1]]) as i32;
+                if raw < 15 {
+                    0
+                } else {
+                    raw
+                }
+            })
+            .collect::<Vec<i32>>();
+
+        Ok(vals)
+    }
+
+    pub fn build_req_frame(cols: usize, rows: usize) -> anyhow::Result<TactileAFrame> {
+        let header = [0x55, 0xAA];
+        let payload_len: usize = 9;
+        let device_addr: u8 = 0x34;
+        let extend_code: u8 = 0x00;
+        let func_code: u8 = 0xFB;
+        let start_addr: u32 = 7168;
+        let except_data_len: usize = cols * rows * 2;
+        let checksum: u8 = 0;
+        Ok(TactileAFrame::Req(TactileAReqFrame {
+            meta: TactileAFrameMetaData {
+                header,
+                payload_len,
+                device_addr,
+                extend_code,
+                func_code,
+                start_addr,
+                except_data_len,
+                checksum,
+            },
+        }))
+    }
+}
+
+impl Codec<TactileAFrame> for TactileACodec {
+    fn decode(
+        &mut self,
+        input: &[u8],
+        session_started_at: std::time::Instant,
+    ) -> Result<Vec<TactileAFrame>, CodecError> {
+        self.buffer.extend_from_slice(input);
+        let mut frames: Vec<TactileAFrame> = Vec::new();
+
+        loop {
+            if self.buffer.len() < FRAME_BUFFER_MIN_LENGTH {
+                break;
+            }
+
+            let header_pos = self.buffer.windows(2).position(|w| w == [0xAA, 0x55]);
+
+            let Some(pos) = header_pos else {
+                self.buffer.clear();
+                break;
+            };
+            if pos > 0 {
+                self.buffer.drain(0..pos);
+            }
+
+            if self.buffer.len() < FRAME_BUFFER_MIN_LENGTH {
+                break;
+            }
+
+            let header = [self.buffer[0], self.buffer[1]];
+            let payload_len = u16::from_le_bytes([self.buffer[2], self.buffer[3]]) as usize;
+            let device_addr = self.buffer[4];
+            let extend_code = self.buffer[5];
+            let func_code = self.buffer[6];
+            let start_addr = u32::from_le_bytes([
+                self.buffer[7],
+                self.buffer[8],
+                self.buffer[9],
+                self.buffer[10],
+            ]);
+            let except_data_len = u16::from_le_bytes([self.buffer[11], self.buffer[12]]) as usize;
+            let status = TactileAFrameStatusCode::from(self.buffer[13]);
+            if except_data_len != self.expected_data_len {
+                debug!(
+                    "unexpected payload length: expected {}, got {}, buffer_len={}",
+                    self.expected_data_len,
+                    except_data_len,
+                    self.buffer.len()
+                );
+                self.buffer.drain(0..1);
+                continue;
+            }
+
+            let frame_length = except_data_len + FRAME_BUFFER_MIN_LENGTH;
+            if self.buffer.len() < frame_length {
+                break;
+            }
+
+            let need_check_data = self.buffer[0..14 + except_data_len].to_vec();
+            let payload = self.buffer[14..14 + except_data_len].to_vec();
+            let crc8_itu_alg = crc::Crc::<u8>::new(&crc::CRC_8_I_432_1);
+            let checksum = crc8_itu_alg.checksum(&need_check_data.as_slice());
+            if self.buffer[frame_length - 1] != checksum {
+                debug!(
+                    "checksum mismatch: expected {:02X}, got {:02X}, frame_len={}",
+                    checksum,
+                    self.buffer[frame_length - 1],
+                    frame_length
+                );
+                self.buffer.drain(0..1);
+                continue;
+            }
+            let dts_ms = elapsed_millis(session_started_at);
+            let meta: TactileAFrameMetaData = TactileAFrameMetaData {
+                header,
+                payload_len,
+                device_addr,
+                extend_code,
+                func_code,
+                start_addr,
+                except_data_len,
+                checksum,
+            };
+            frames.push(TactileAFrame::Rep({
+                TactileARepFrame {
+                    meta,
+                    status,
+                    payload,
+                    dts_ms,
+                }
+            }));
+
+            self.buffer.drain(0..frame_length);
+        }
+
+        Ok(frames)
+    }
+
+    fn encode(
+        &self,
+        frame: &TactileAFrame,
+    ) -> Result<Vec<u8>, crate::serial_core::error::CodecError> {
+        match frame {
+            TactileAFrame::Req(f) => {
+                let mut req_bytes: Vec<u8> = Vec::new();
+                req_bytes.extend_from_slice(f.meta.header.as_slice());
+                req_bytes.extend_from_slice((f.meta.payload_len as u16).to_le_bytes().as_slice());
+                req_bytes.push(f.meta.device_addr);
+                req_bytes.push(f.meta.extend_code);
+                req_bytes.push(f.meta.func_code);
+
+                req_bytes.extend_from_slice(f.meta.start_addr.to_le_bytes().as_slice());
+                req_bytes.extend_from_slice((f.meta.except_data_len as u16).to_le_bytes().as_slice());
+                let checksum = calc_crc8_itu(req_bytes.as_slice());
+                req_bytes.push(checksum);
+                info!("send: {:02X?}", req_bytes);
+                Ok(req_bytes)
+            }
+            _ => {
+                Err(CodecError::InvalidFrameType)
+            }
+        }
+    }
+}
+
+#[async_trait]
+impl FrameHandler<TactileAFrame, i32> for TactileAHandler {
+    async fn on_frame(&mut self, frame: &TactileAFrame) -> anyhow::Result<Option<Vec<i32>>> {
+        match frame {
+            TactileAFrame::Rep(rep) => {
+                let vals = TactileACodec::parse_data_frame(&rep.payload)?;
+                Ok(Some(vals))
+            }
+            _ => Ok(None),
+        }
+    }
+}
+
+impl TactileACsvExporter {
+    fn new(channels: usize) -> Self {
+        TactileACsvExporter { channels }
+    }
+}
+
+impl CsvExporter<TactileARepFrame> for TactileACsvExporter {
+    type Error = CodecError;
+    fn csv_header(&self, _recording: &Recording<TactileARepFrame>) -> Vec<String> {
+        let mut header: Vec<String> = Vec::new();
+        for i in 0..self.channels {
+            header.push(format!("channel{}", i + 1));
+        }
+
+        header.push("dts".to_string());
+        header.push("summary".to_string());
+        header
+    }
+
+    fn csv_row(
+        &self,
+        item: &RecordedFrame<TactileARepFrame>,
+    ) -> anyhow::Result<Vec<String>> {
+        let packet = TactileADataPacket::try_from(&item.frame)?;
+        let summary: i32 = packet.data.iter().sum();
+        let mut row: Vec<String> = packet.data.iter().map(|x| x.to_string()).collect();
+        row.push(packet.dts_ms.to_string());
+        row.push(summary.to_string());
+        Ok(row)
+    }
+}
+
+impl CsvExporter<TactileAFrame> for TactileACsvExporter {
+    type Error = CodecError;
+
+    fn csv_header(&self, _recording: &Recording<TactileAFrame>) -> Vec<String> {
+        let mut header: Vec<String> = Vec::new();
+        for i in 0..self.channels {
+            header.push(format!("channel{}", i + 1));
+        }
+
+        header.push("dts".to_string());
+        header
+    }
+
+    fn csv_row(
+        &self,
+        item: &RecordedFrame<TactileAFrame>,
+    ) -> anyhow::Result<Vec<String>> {
+        let rep = match &item.frame {
+            TactileAFrame::Rep(rep) => rep,
+            TactileAFrame::Req(_) => return Err(anyhow!("request frame cannot be exported to csv row")),
+        };
+
+        let packet = TactileADataPacket::try_from(rep)?;
+        let mut row: Vec<String> = packet.data.iter().map(|x| x.to_string()).collect();
+        row.push(packet.dts_ms.to_string());
+        Ok(row)
+    }
+}
+
+impl TactileACsvImporter {
+    pub fn new(_path: &str) -> TactileACsvImporter {
+        Self {
+            channels: 0,
+            data_row: 0,
+            packets: Vec::new(),
+        }
+    }
+
+    fn parse_record(&mut self, record: StringRecord) -> anyhow::Result<TactileADataPacket> {
+        if self.channels == 0 {
+            return Err(anyhow!("csv header is missing channel columns"));
+        }
+
+        if record.len() < self.channels + 1 {
+            return Err(anyhow!("csv row has insufficient columns"));
+        }
+
+        let mut data = Vec::with_capacity(self.channels);
+        for index in 0..self.channels {
+            let cell = record.get(index).ok_or_else(|| anyhow!("missing channel cell"))?;
+            data.push(cell.parse::<i32>()?);
+        }
+
+        let dts_cell = record
+            .get(self.channels)
+            .ok_or_else(|| anyhow!("missing dts cell"))?;
+        let dts_ms = dts_cell.parse::<u64>()?;
+
+        Ok(TactileADataPacket {
+            data: data,
+            dts_ms: dts_ms,
+        })
+    }
+}
+
+impl CsvImporter<TactileADataPacket> for TactileACsvImporter {
+    fn load<R: Read>(&mut self, reader: R) -> anyhow::Result<Vec<TactileADataPacket>> {
+        let mut rdr = csv::Reader::from_reader(reader);
+        let headers = rdr.headers()?.clone();
+        self.channels = headers.len().saturating_sub(1);
+        self.data_row = 0;
+        self.packets.clear();
+
+        for record in rdr.records() {
+            let record = record?;
+            let packet = self.parse_record(record)?;
+            self.packets.push(packet);
+            self.data_row += 1;
+        }
+
+        Ok(self.packets.clone())
+    }
+}
+
+pub fn export_recording_csv<W>(recording: &Recording<TactileAFrame>, writer: W) -> anyhow::Result<()>
+where
+    W: std::io::Write,
+{
+    let channel_nb = recording
+        .frames
+        .iter()
+        .find_map(|frame| match &frame.frame {
+            TactileAFrame::Rep(rep) => Some(rep.payload.len() / 2),
+            TactileAFrame::Req(_) => None,
+        })
+        .unwrap_or(0);
+
+    let exporter = TactileACsvExporter::new(channel_nb);
+    write_csv(recording, &exporter, writer)
+}

src-tauri/src/serial_core/codecs/test.rs

@@ -0,0 +1,256 @@
+use std::io::Read;
+use std::time::Instant;
+use crate::serial_core::frame::{FrameHandler};
+use crate::serial_core::{codec::Codec, error::CodecError, frame::TestFrame};
+use anyhow::anyhow;
+use async_trait::async_trait;
+use csv::StringRecord;
+use crate::serial_core::record::{write_csv, CsvExporter, CsvImporter, RecordedFrame, Recording};
+use crate::serial_core::utils::{
+    elapsed_millis,
+    usize_to_u16_be_bytes
+};
+pub struct TestCodec {
+    buffer: Vec<u8>,
+}
+
+pub struct TestHandler;
+
+impl TestCodec {
+    pub fn new() -> TestCodec {
+        Self { buffer: Vec::new() }
+    }
+}
+
+impl Codec<TestFrame> for TestCodec {
+    fn decode(&mut self, input: &[u8], session_started_at: Instant) -> Result<Vec<TestFrame>, CodecError> {
+        self.buffer.extend_from_slice(input);
+        let mut frames = Vec::new();
+
+        loop {
+            if self.buffer.len() < 6 {
+                break;
+            }
+
+            let header_pos = self.buffer.windows(2).position(|w| w == [0xAA, 0x55]);
+
+            let Some(pos) = header_pos else {
+                self.buffer.clear();
+                break;
+            };
+            if pos > 0 {
+                self.buffer.drain(0..pos);
+            }
+
+            if self.buffer.len() < 6 {
+                break;
+            }
+
+            let cmd = self.buffer[2];
+            let length_bytes = [self.buffer[3], self.buffer[4]];
+            let length = u16::from_be_bytes(length_bytes) as usize;
+            let frame_length = (length + 6) as usize;
+            if self.buffer.len() < frame_length {
+                break;
+            }
+            let payload = self.buffer[5..5 + length].to_vec();
+            // let checksum = crc8(payload.as_slice());
+            let crc8_alg = crc::Crc::<u8>::new(&crc::CRC_8_SMBUS);
+            let checksum = crc8_alg.checksum(payload.as_slice());
+            if self.buffer[frame_length - 1] != checksum {
+                self.buffer.drain(0..1);
+                continue;
+            }
+            let dts = elapsed_millis(session_started_at);
+            println!("dts_ms: {dts}");
+            frames.push(TestFrame {
+                header: [0xAA, 0x55],
+                cmd: cmd,
+                length: length,
+                payload: payload,
+                checksum: checksum,
+                dts_ms: dts,
+            });
+
+            self.buffer.drain(0..frame_length);
+        }
+
+        Ok(frames)
+    }
+    fn encode(&self, frame: &TestFrame) -> Result<Vec<u8>, CodecError> {
+        let _ = u16::try_from(frame.payload.len()).map_err(|_| CodecError::PayloadTooLarge)?;
+        let mut out = Vec::with_capacity(6 + frame.length);
+        out.extend_from_slice(&frame.header);
+        out.push(frame.cmd);
+        out.extend_from_slice(&usize_to_u16_be_bytes(frame.length));
+        out.extend_from_slice(&frame.payload);
+        out.push(frame.checksum);
+
+        Ok(out)
+    }
+}
+
+#[async_trait]
+impl FrameHandler<TestFrame, i32> for TestHandler {
+    async fn on_frame(&mut self, frame: &TestFrame) -> anyhow::Result<Option<Vec<i32>>> {
+        match frame.cmd {
+            0x01 => {
+                let vals = parse_data_frame(&frame.payload)?;
+                Ok(Some(vals))
+            }
+            _ => Ok(None),
+        }
+    }
+}
+
+fn parse_data_frame(data: &[u8]) -> Result<Vec<i32>, CodecError> {
+    if data.len() % 2 != 0 {
+        return Err(CodecError::InvalidLength);
+    }
+
+    let vals: Vec<i32> = data
+        .chunks_exact(2)
+        .map(|chunk| u16::from_be_bytes([chunk[0], chunk[1]]) as i32)
+        .collect::<Vec<i32>>();
+
+    Ok(vals)
+}
+
+pub struct TestCsvExporter;
+pub struct TestCsvImporter {
+    channels: usize,
+    data_row: usize,
+    packets: Vec<TestDataPacket>,
+}
+
+#[derive(Clone)]
+pub struct TestDataPacket {
+    pub data: Vec<i32>,
+    pub dts_ms: u64
+}
+
+impl TryFrom<&TestFrame> for TestDataPacket {
+    type Error = CodecError;
+    fn try_from(frame: &TestFrame) -> Result<TestDataPacket, Self::Error> {
+        let data = parse_data_frame(&frame.payload)?;
+        let dts = frame.dts_ms;
+        Ok(TestDataPacket { data: data, dts_ms: dts })
+    }
+}
+// impl From<TestFrame> for TestDataPacket {
+//     fn from(frame: TestFrame) -> Self {
+//         let data = parse_data_frame(&frame.payload)?;
+//         let dts = frame.dts_ms;
+//         TestDataPacket { data: data, dts_ms: dts }
+//     }
+// }
+
+
+impl CsvExporter<TestFrame> for TestCsvExporter {
+    type Error = CodecError;
+    fn csv_header(&self, recording: &Recording<TestFrame>) -> Vec<String> {
+        let channel_nb = recording
+            .frames
+            .iter()
+            .find_map(|frame| parse_data_frame(&frame.frame.payload).ok().map(|vals| vals.len()))
+            .unwrap_or(0);
+        let mut header: Vec<String> = Vec::new();
+        for i in 0..channel_nb {
+            header.push(format!("channel{}", i + 1));
+        }
+        header.push("dts".to_string());
+
+        header
+    }
+
+    fn csv_row(&self, item: &RecordedFrame<TestFrame>) -> anyhow::Result<Vec<String>> {
+        let packet: TestDataPacket = TestDataPacket::try_from(&item.frame)?;
+        let mut row: Vec<String> = packet.data.iter().map(|&x| x.to_string()).collect();
+        row.push(packet.dts_ms.to_string());
+        Ok(row)
+    }
+}
+
+impl TestCsvImporter {
+    pub fn new(_path: &str) -> TestCsvImporter {
+        Self {
+            channels: 0,
+            data_row: 0,
+            packets: Vec::new(),
+        }
+    }
+
+    fn parse_record(&mut self, record: StringRecord) -> anyhow::Result<TestDataPacket>{
+        if self.channels == 0 {
+            return Err(anyhow!("csv header is missing channel columns"));
+        }
+
+        if record.len() < self.channels + 1 {
+            return Err(anyhow!("csv row has insufficient columns"));
+        }
+
+        let mut data = Vec::with_capacity(self.channels);
+        for index in 0..self.channels {
+            let cell = record.get(index).ok_or_else(|| anyhow!("missing channel cell"))?;
+            data.push(cell.parse::<i32>()?);
+        }
+
+        let dts_cell = record
+            .get(self.channels)
+            .ok_or_else(|| anyhow!("missing dts cell"))?;
+        let dts_ms = dts_cell.parse::<u64>()?;
+
+        Ok(TestDataPacket {
+            data: data,
+            dts_ms: dts_ms,
+        })
+    }
+}
+
+impl CsvImporter<TestDataPacket> for TestCsvImporter {
+    fn load<R: Read>(&mut self, reader: R) -> anyhow::Result<Vec<TestDataPacket>> {
+        let mut rdr = csv::Reader::from_reader(reader);
+        let headers = rdr.headers()?.clone();
+        self.channels = headers.len().saturating_sub(1);
+        self.data_row = 0;
+        self.packets.clear();
+
+        for record in rdr.records() {
+            let record = record?;
+            let packet = self.parse_record(record)?;
+            self.packets.push(packet);
+            self.data_row += 1;
+        }
+
+        Ok(self.packets.clone())
+    }
+}
+
+
+pub fn export_recording_csv<W>(recording: &Recording<TestFrame>, writer: W) -> anyhow::Result<()>
+where
+    W: std::io::Write,
+{
+    write_csv(recording, &TestCsvExporter, writer)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use csv::Reader;
+    use std::io::Cursor;
+
+    #[test]
+    fn test_read_csv_basic() -> anyhow::Result<()> {
+        let mut rdr = Reader::from_path("recording_20260329_125238.csv")?;
+        let headers = rdr.headers()?;
+        println!("headers: {:?}", headers);
+
+        for result in rdr.records() {
+            let record = result?;
+            println!("record: {:?}", record);
+        }
+
+        Ok(())
+    }
+}

src-tauri/src/serial_core/frame.rs

@@ -0,0 +1,57 @@
+use anyhow::Result;
+use async_trait::async_trait;
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub struct TestFrame {
+    pub header: [u8; 2],
+    pub cmd: u8,
+    pub length: usize,
+    pub payload: Vec<u8>,
+    pub checksum: u8,
+    pub dts_ms: u64
+}
+
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub struct TactileAFrameMetaData {
+    pub header: [u8; 2],
+    pub payload_len: usize,
+    pub device_addr: u8,
+    pub extend_code: u8,
+    pub func_code: u8,
+    pub start_addr: u32,
+    pub except_data_len: usize,
+    // pub status: u8,
+    // pub payload_data: Vec<u8>,
+    pub checksum: u8,
+    // pub dts_ms: u64,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub struct TactileAReqFrame {
+    pub meta: TactileAFrameMetaData,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq)] 
+pub struct TactileARepFrame {
+    pub meta: TactileAFrameMetaData,
+    pub status: TactileAFrameStatusCode,
+    pub payload: Vec<u8>,
+    pub dts_ms: u64
+}
+
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub enum TactileAFrameStatusCode {
+    Success,
+    Failure
+}
+
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub enum TactileAFrame {
+    Req(TactileAReqFrame),
+    Rep(TactileARepFrame)
+}
+
+#[async_trait]
+pub trait FrameHandler<F, T>: Send {
+    async fn on_frame(&mut self, frame: &F) -> Result<Option<Vec<T>>>;
+}
+

src-tauri/src/serial_core/mod.rs

@@ -1,4 +1,35 @@
+use crate::serial_core::{
+    frame::{TactileAFrame, TestFrame},
+    record::Recording,
+};
+
+pub mod codec;
+pub mod codecs;
 pub mod error;
+pub mod frame;
 pub mod model;
 pub mod serial;
 pub mod record;
+pub mod utils;
+#[cfg(feature = "multi-dim")]
+pub mod multi_dim_force;
+pub mod basin_force_estimator;
+
+pub type TestRecording = Recording<TestFrame>;
+pub type TactileARecording = Recording<TactileAFrame>;
+
+pub struct SerialConnection {
+    pub port: String,
+}
+
+pub fn connect(port: &str) -> Result<SerialConnection, String> {
+    let port = port.trim();
+
+    if port.is_empty() {
+        return Err("Serial port is required".to_string());
+    }
+
+    Ok(SerialConnection {
+        port: port.to_string(),
+    })
+}

src-tauri/src/serial_core/model.rs

@@ -1,6 +1,8 @@
+use crate::serial_core::frame::TestFrame;
 use std::collections::HashMap;
 use std::time::{Duration, Instant, SystemTime, UNIX_EPOCH};
 
+const MAX_POINTS: usize = 28;
 const MAX_SUMMARY_POINTS: usize = 42;
 const PANEL_STALE_AFTER: Duration = Duration::from_millis(2400);
 
@@ -72,6 +74,16 @@ pub struct HudSignalIcon {
     pub tone: HudTone,
 }
 
+struct HudPanelUpdate {
+    source_id: String,
+    values: Vec<f32>,
+}
+
+struct PanelEntry {
+    panel: HudSignalPanel,
+    last_seen: Instant,
+}
+
 pub struct HudChartState {
     panels: HashMap<String, PanelEntry>,
     order: Vec<String>,
@@ -80,11 +92,6 @@ pub struct HudChartState {
     last_frame_seen: Option<Instant>,
 }
 
-struct PanelEntry {
-    panel: HudSignalPanel,
-    last_seen: Instant,
-}
-
 impl HudChartState {
     pub fn new() -> Self {
         Self {
@@ -98,21 +105,76 @@ impl HudChartState {
 
     pub fn record_summary(&mut self, value: f32) {
         push_summary_point(&mut self.summary_points, value);
-        self.last_frame_seen = Some(Instant::now());
     }
 
-    pub fn record_pressure_matrix(&mut self, values: &[f32]) {
+    pub fn record_pressure_matrix(&mut self, values: &[i32]) {
         if values.is_empty() {
             return;
         }
-        self.pressure_matrix = Some(values.to_vec());
+
+        self.pressure_matrix = Some(values.iter().map(|value| *value as f32).collect());
+    }
+
+    pub fn apply_frame(&mut self, frame: &TestFrame, decoded_values: Option<&[i32]>) -> HudPacket {
+        let now = Instant::now();
+        self.last_frame_seen = Some(now);
+
+        for update in expand_frame_updates(frame, decoded_values) {
+            self.apply_update(update, now);
+        }
+
+        self.prune_stale_at(now);
+        self.snapshot()
     }
 
     pub fn prune_stale(&mut self) -> Option<HudPacket> {
-        let now = Instant::now();
         let before = self.panels.len();
-        let summary_before = self.summary_points.len();
+        let summary_points_before = self.summary_points.len();
+        self.prune_stale_at(Instant::now());
 
+        if before == self.panels.len() && summary_points_before == self.summary_points.len() {
+            return None;
+        }
+
+        Some(self.snapshot())
+    }
+
+    fn apply_update(&mut self, update: HudPanelUpdate, now: Instant) {
+        if update.values.is_empty() {
+            return;
+        }
+
+        if !self.panels.contains_key(&update.source_id) {
+            let next_side = side_for_index(self.order.len());
+            self.order.push(update.source_id.clone());
+            self.panels.insert(
+                update.source_id.clone(),
+                PanelEntry {
+                    panel: build_panel(&update.source_id, next_side, update.values.len()),
+                    last_seen: now,
+                },
+            );
+        }
+
+        let entry = self
+            .panels
+            .get_mut(&update.source_id)
+            .expect("panel entry should exist after insertion");
+
+        entry.last_seen = now;
+        entry.panel.active = true;
+        ensure_panel_channels(&mut entry.panel, update.values.len());
+
+        for (index, value) in update.values.into_iter().enumerate() {
+            if let Some(series) = entry.panel.series.get_mut(index) {
+                push_point(&mut series.points, value);
+            }
+        }
+
+        refresh_panel_stats(&mut entry.panel);
+    }
+
+    fn prune_stale_at(&mut self, now: Instant) {
         self.panels
             .retain(|_, entry| now.duration_since(entry.last_seen) <= PANEL_STALE_AFTER);
         self.order.retain(|id| self.panels.contains_key(id));
@@ -127,16 +189,6 @@ impl HudChartState {
             self.pressure_matrix = None;
             self.last_frame_seen = None;
         }
-
-        if before == self.panels.len() && summary_before == self.summary_points.len() {
-            return None;
-        }
-
-        Some(self.snapshot())
-    }
-
-    pub fn build_snapshot(&mut self) -> HudPacket {
-        self.snapshot()
     }
 
     fn snapshot(&mut self) -> HudPacket {
@@ -171,6 +223,106 @@ impl Default for HudChartState {
     }
 }
 
+fn build_panel(source_id: &str, side: HudPanelSide, channel_count: usize) -> HudSignalPanel {
+    HudSignalPanel {
+        id: format!("panel-{source_id}"),
+        code: source_id.to_string(),
+        title: format!("Source {source_id}"),
+        side,
+        active: true,
+        series: build_panel_series(source_id, channel_count, &[]),
+        icons: build_panel_icons(source_id, channel_count),
+        latest: None,
+        min: None,
+        max: None,
+    }
+}
+
+fn expand_frame_updates(frame: &TestFrame, decoded_values: Option<&[i32]>) -> Vec<HudPanelUpdate> {
+    if let Some(values) = decoded_values {
+        if values.is_empty() {
+            return Vec::new();
+        }
+
+        return vec![HudPanelUpdate {
+            source_id: format_source_id(frame.cmd),
+            values: values.iter().map(|value| *value as f32).collect(),
+        }];
+    }
+
+    let chunks = frame.payload.chunks_exact(4);
+
+    if !frame.payload.is_empty() && chunks.remainder().is_empty() {
+        return chunks.map(build_update_from_chunk).collect();
+    }
+
+    vec![HudPanelUpdate {
+        source_id: format_source_id(frame.cmd),
+        values: fallback_values(frame),
+    }]
+}
+
+fn build_update_from_chunk(chunk: &[u8]) -> HudPanelUpdate {
+    HudPanelUpdate {
+        source_id: format_source_id(chunk[0]),
+        values: chunk[1..]
+            .iter()
+            .enumerate()
+            .map(|(index, byte)| normalize_value(*byte, tone_for_index(index)))
+            .collect(),
+    }
+}
+
+fn fallback_values(frame: &TestFrame) -> Vec<f32> {
+    let mut bytes = frame.payload.clone();
+
+    if bytes.is_empty() {
+        bytes.extend([
+            frame.cmd,
+            frame.length as u8,
+            frame.checksum,
+            frame.cmd.wrapping_add(frame.checksum),
+        ]);
+    }
+
+    while bytes.len() < 3 {
+        let previous = *bytes.last().unwrap_or(&frame.cmd);
+        bytes.push(
+            previous
+                .wrapping_add(frame.cmd)
+                .wrapping_add(bytes.len() as u8),
+        );
+    }
+
+    bytes
+        .into_iter()
+        .enumerate()
+        .map(|(index, byte)| normalize_value(byte, tone_for_index(index)))
+        .collect()
+}
+
+fn normalize_value(byte: u8, tone: HudTone) -> f32 {
+    let base = (byte as f32 / 255.0) * 100.0;
+    let offset = match tone {
+        HudTone::Cyan => 6.0,
+        HudTone::Lime => 0.0,
+        HudTone::Orange => -6.0,
+        HudTone::Violet => 10.0,
+        HudTone::Gold => -10.0,
+        HudTone::Rose => 3.0,
+    };
+
+    (base + offset).clamp(0.0, 100.0)
+}
+
+fn format_source_id(byte: u8) -> String {
+    if byte.is_ascii_alphanumeric() {
+        (byte as char).to_ascii_uppercase().to_string()
+    } else {
+        format!("CH{:02X}", byte)
+    }
+}
+
 fn side_for_index(index: usize) -> HudPanelSide {
     if index % 2 == 0 {
         HudPanelSide::Left
@@ -179,6 +331,91 @@ fn side_for_index(index: usize) -> HudPanelSide {
     }
 }
 
+fn push_point(points: &mut Vec<f32>, value: f32) {
+    if points.len() >= MAX_POINTS {
+        points.remove(0);
+    }
+
+    points.push((value * 10.0).round() / 10.0);
+}
+
+fn build_panel_series(
+    source_id: &str,
+    channel_count: usize,
+    previous: &[HudSignalSeries],
+) -> Vec<HudSignalSeries> {
+    (0..channel_count)
+        .map(|index| HudSignalSeries {
+            id: format!("{source_id}-series-{}", index + 1),
+            tone: tone_for_index(index),
+            points: previous
+                .get(index)
+                .map(|series| series.points.clone())
+                .unwrap_or_default(),
+        })
+        .collect()
+}
+
+fn build_panel_icons(source_id: &str, channel_count: usize) -> Vec<HudSignalIcon> {
+    (0..channel_count)
+        .map(|index| HudSignalIcon {
+            id: format!("{source_id}-icon-{}", index + 1),
+            label: if channel_count == 1 {
+                "TOTAL".to_string()
+            } else {
+                format!("{source_id}-{}", index + 1)
+            },
+            tone: tone_for_index(index),
+        })
+        .collect()
+}
+
+fn ensure_panel_channels(panel: &mut HudSignalPanel, channel_count: usize) {
+    if panel.series.len() == channel_count && panel.icons.len() == channel_count {
+        return;
+    }
+
+    panel.series = build_panel_series(&panel.code, channel_count, &panel.series);
+    panel.icons = build_panel_icons(&panel.code, channel_count);
+}
+
+fn refresh_panel_stats(panel: &mut HudSignalPanel) {
+    let latest_values: Vec<f32> = panel
+        .series
+        .iter()
+        .filter_map(|series| series.points.last().copied())
+        .collect();
+
+    panel.latest = if latest_values.is_empty() {
+        None
+    } else {
+        Some(latest_values.iter().sum::<f32>() / latest_values.len() as f32)
+    };
+
+    panel.min = panel
+        .series
+        .iter()
+        .flat_map(|series| series.points.iter().copied())
+        .reduce(f32::min);
+
+    panel.max = panel
+        .series
+        .iter()
+        .flat_map(|series| series.points.iter().copied())
+        .reduce(f32::max);
+}
+
+fn tone_for_index(index: usize) -> HudTone {
+    match index % 6 {
+        0 => HudTone::Cyan,
+        1 => HudTone::Lime,
+        2 => HudTone::Orange,
+        3 => HudTone::Violet,
+        4 => HudTone::Gold,
+        _ => HudTone::Rose,
+    }
+}
+
 fn push_summary_point(points: &mut Vec<f32>, value: f32) {
     if points.len() >= MAX_SUMMARY_POINTS {
         points.remove(0);
@@ -203,3 +440,61 @@ fn now_millis() -> u64 {
         .map(|duration| duration.as_millis() as u64)
         .unwrap_or_default()
 }
+
+// #[cfg(test)]
+// mod tests {
+//     use super::*;
+//
+//     fn sample_frame() -> TestFrame {
+//         TestFrame {
+//             header: [0xAA, 0x55],
+//             cmd: 0x01,
+//             length: 4,
+//             payload: vec![0x00, 0x0A, 0x00, 0x14],
+//             checksum: 0,
+//
+//         }
+//     }
+//
+//     #[test]
+//     fn prune_stale_clears_panels_and_summary_after_timeout() {
+//         let mut state = HudChartState::new();
+//         let frame = sample_frame();
+//
+//         state.record_summary(30.0);
+//         let _ = state.apply_frame(&frame, Some(&[10, 20]));
+//
+//         let stale_now = Instant::now();
+//         let stale_seen = stale_now - PANEL_STALE_AFTER - Duration::from_millis(1);
+//
+//         state.last_frame_seen = Some(stale_seen);
+//
+//         for entry in state.panels.values_mut() {
+//             entry.last_seen = stale_seen;
+//         }
+//
+//         let packet = state
+//             .prune_stale()
+//             .expect("stale data should emit an update");
+//
+//         assert!(packet.panels.is_empty());
+//         assert!(packet.summary.points.is_empty());
+//         assert!(state.panels.is_empty());
+//         assert!(state.summary_points.is_empty());
+//     }
+//
+//     #[test]
+//     fn prune_stale_keeps_recent_summary_points() {
+//         let mut state = HudChartState::new();
+//         let frame = sample_frame();
+//
+//         state.record_summary(30.0);
+//         let _ = state.apply_frame(&frame, Some(&[10, 20]));
+//
+//         state.last_frame_seen = Some(Instant::now());
+//
+//         assert!(state.prune_stale().is_none());
+//         assert_eq!(state.summary_points, vec![30.0]);
+//         assert_eq!(state.panels.len(), 1);
+//     }
+// }

src-tauri/src/serial_core/multi_dim_force.rs

@@ -0,0 +1,122 @@
+use ndarray::Array2;
+
+const TOTAL_PRESSURE_LOW_THRESHOLD: usize = 500;
+const COP_STABILITY_FRAMES_REQUIRED: usize = 5;
+const SENSOR_ROWS: usize = 12;
+const SENSOR_COLS: usize = 7;
+
+pub struct PztProcessor {
+    first_frame: Option<Vec<f32>>,
+    first_contact_cop_x: Option<f32>,
+    first_contact_cop_y: Option<f32>,
+    contact_initialized: bool,
+    total_pressure_low_counter: usize,
+}
+
+impl PztProcessor {
+    pub fn new() -> Self {
+        Self {
+            first_frame: None,
+            first_contact_cop_x: None,
+            first_contact_cop_y: None,
+            contact_initialized: false,
+            total_pressure_low_counter: 0,
+        }
+    }
+
+    fn subtract_baseline(&mut self, current_frame: &[f32]) -> Vec<f32> {
+        if self.first_frame.is_none() {
+            self.first_frame = Some(current_frame.to_vec());
+        }
+
+        let baseline = self.first_frame.as_ref().unwrap();
+        current_frame
+            .iter()
+            .zip(baseline.iter())
+            .map(|(c, b)| (c - b).max(0.0))
+            .collect()
+    }
+
+    fn reset_cop_state(&mut self) {
+        self.first_contact_cop_x = None;
+        self.first_contact_cop_y = None;
+        self.contact_initialized = false;
+        self.total_pressure_low_counter = 0;
+    }
+
+    fn compute_pressure_direction(&mut self, frame: &[f32]) -> (f32, f32) {
+        let frame2d = Array2::from_shape_vec((SENSOR_ROWS, SENSOR_COLS), frame.to_vec()).unwrap();
+        let total_pressure: f32 = frame2d.sum();
+        if total_pressure < TOTAL_PRESSURE_LOW_THRESHOLD as f32 {
+            self.total_pressure_low_counter += 1;
+        } else {
+            self.total_pressure_low_counter = 0;
+        }
+
+        if self.total_pressure_low_counter >= COP_STABILITY_FRAMES_REQUIRED {
+            self.reset_cop_state();
+            return (0.0, 0.0);
+        }
+
+        if total_pressure == 0.0 {
+            return (0.0, 0.0);
+        }
+
+        let mut sum_x = 0.0;
+        let mut sum_y = 0.0;
+
+        for r in 0..SENSOR_ROWS {
+            for c in 0..SENSOR_COLS {
+                let val = frame2d[(r, c)];
+                sum_x += val * c as f32;
+                sum_y += val * r as f32;
+            }
+        }
+
+        let cop_x = sum_x / total_pressure;
+        let cop_y = sum_y / total_pressure;
+
+        if !self.contact_initialized {
+            self.first_contact_cop_x = Some(cop_x);
+            self.first_contact_cop_y = Some(cop_y);
+            self.contact_initialized = true;
+            return (0.0, 0.0);
+        }
+
+        let dx = cop_x - self.first_contact_cop_x.unwrap();
+        let dy = cop_y - self.first_contact_cop_y.unwrap();
+
+        (dx, dy)
+    }
+
+    fn compute_vector_angle(x: f32, y: f32) -> (f32, f32) {
+        let epsilon = 1e-8;
+        let mag = (x * x + y * y).sqrt();
+        let mut angle = (y).atan2(x + epsilon).to_degrees();
+        if angle < 0.0 {
+            angle += 360.0;
+        }
+        (angle, mag)
+    }
+
+    fn compute_pzt_angle(px: f32, py: f32) -> (f32, f32) {
+        Self::compute_vector_angle(px, -py)
+    }
+
+    pub fn get_pzt_angle(&mut self, adc_data: &[f32]) -> Result<f32, &'static str> {
+        if adc_data.len() != 84 {
+            return Err("ADC data length must be 84");
+        }
+
+        let baseline = self.subtract_baseline(adc_data);
+        let (dx, dy) = self.compute_pressure_direction(&baseline);
+        let (angle, _) = Self::compute_pzt_angle(dx, dy);
+
+        Ok(angle)
+    }
+
+    pub fn reset_baseline(&mut self) {
+        self.first_frame = None;
+        self.reset_cop_state();
+    }
+}

src-tauri/src/serial_core/record.rs

@@ -1,5 +1,3 @@
-use eskin_finger_sdk::types::FingerSample;
-
 #[derive(Clone)]
 pub struct FrameTiming {
     pub pts_ms: Option<u64>,
@@ -9,82 +7,50 @@ pub struct FrameTiming {
 #[derive(Clone)]
 pub struct RecordedFrame<F> {
     pub timing: FrameTiming,
-    pub frame: F,
+    pub frame: F
 }
 
 #[derive(Clone, Default)]
 pub struct Recording<F> {
-    pub frames: Vec<RecordedFrame<F>>,
+    pub frames: Vec<RecordedFrame<F>>
 }
 
 impl<F> Recording<F> {
-    pub fn new() -> Recording<F> {
+    pub fn new() -> Recording<F> { Self { frames: Vec::new() } }
-        Self {
+    pub fn push(&mut self, ite: RecordedFrame<F>) {
-            frames: Vec::new(),
+        self.frames.push(ite);
-        }
-    }
-    pub fn push(&mut self, item: RecordedFrame<F>) {
-        self.frames.push(item);
     }
 }
 
-pub type FingerRecording = Recording<FingerSample>;
+pub trait CsvExporter<F> {
+    type Error: std::error::Error + Send + Sync + 'static;
+    fn csv_header(&self, recording: &Recording<F>) -> Vec<String>;
+    fn csv_row(&self, item: &RecordedFrame<F>) -> anyhow::Result<Vec<String>>;
+}
 
-pub fn export_recording_csv<W>(
+// TODO: CsvImporter
-    recording: &Recording<FingerSample>,
+pub trait CsvImporter<P> {
-    mut writer: W,
+    fn load<R: std::io::Read>(&mut self, reader: R) -> anyhow::Result<Vec<P>>;
+}
+
+pub fn write_csv<F, E, W>(
+    recording: &Recording<F>,
+    exporter: &E,
+    writer: W,
 ) -> anyhow::Result<()>
 where
+    E: CsvExporter<F>,
     W: std::io::Write,
 {
-    // Infer channel count from the first sample's combined_forces (just fz)
+    let header = exporter.csv_header(&recording);
-    // We write: timestamp_us, sequence, module, fx, fy, fz
+    let mut wrt = csv::Writer::from_writer(writer);
-    let mut wrt = csv::Writer::from_writer(&mut writer);
+    wrt.write_record(header)?;
-    wrt.write_record(["timestamp_us", "sequence", "module", "fx", "fy", "fz"])?;
+    for f in &recording.frames {
-
+        let row = exporter.csv_row(f)?;
-    for frame in &recording.frames {
+        wrt.write_record(&row)?;
-        let s = &frame.frame;
-        wrt.write_record(&[
-            s.timestamp_us.to_string(),
-            s.sequence.to_string(),
-            format!("{:?}", s.combined_forces.module),
-            s.combined_forces.force.fx.to_string(),
-            s.combined_forces.force.fy.to_string(),
-            s.combined_forces.force.fz.to_string(),
-        ])?;
     }
 
     wrt.flush()?;
+
     Ok(())
 }
-
-pub struct FingerSampleCsvPacket {
-    pub timestamp_us: u64,
-    pub sequence: u32,
-    pub fz: u32,
-}
-
-pub fn import_csv<R: std::io::Read>(
-    reader: R,
-) -> anyhow::Result<Vec<FingerSampleCsvPacket>> {
-    let mut rdr = csv::Reader::from_reader(reader);
-    let mut packets = Vec::new();
-
-    for result in rdr.records() {
-        let record = result?;
-        if record.len() < 6 {
-            continue;
-        }
-        let timestamp_us = record.get(0).unwrap_or("0").parse::<u64>().unwrap_or(0);
-        let sequence = record.get(1).unwrap_or("0").parse::<u32>().unwrap_or(0);
-        let fz = record.get(5).unwrap_or("0").parse::<u32>().unwrap_or(0);
-
-        packets.push(FingerSampleCsvPacket {
-            timestamp_us,
-            sequence,
-            fz,
-        });
-    }
-
-    Ok(packets)
-}

src-tauri/src/serial_core/serial.rs

@@ -1,160 +1,443 @@
-use crate::serial_core::model::HudChartState;
+use crate::serial_core::basin_force_estimator::BasinForceEstimator;
+use crate::serial_core::codec::Codec;
+use crate::serial_core::codecs::tactile_a::TactileACodec;
+use crate::serial_core::frame::{FrameHandler, TactileAFrame, TestFrame};
+use crate::serial_core::model::{HudChartState, HudPacket};
+#[cfg(feature = "multi-dim")]
+use crate::serial_core::multi_dim_force::PztProcessor;
 use crate::serial_core::record::Recording;
-use eskin_finger_sdk::channel::DeviceEvent;
+use crate::serial_core::record::{FrameTiming, RecordedFrame};
-use eskin_finger_sdk::config::DeviceConfig;
+#[cfg(feature = "devkit")]
-use eskin_finger_sdk::device::{EskinDevice, EskinDeviceInner};
+use crate::devkit::{proto::SensorFrame, DevKitState};
-use eskin_finger_sdk::transport::SerialPortTransport;
+use anyhow::Result;
-use eskin_finger_sdk::types::FingerSample;
+use log::debug;
+use std::future::pending;
+#[cfg(feature = "devkit")]
+use std::sync::atomic::Ordering;
+use std::sync::{Arc, Mutex};
+use std::time::Instant;
 use tauri::{AppHandle, Emitter};
+#[cfg(feature = "devkit")]
+use tauri::Manager;
+use tokio::io::{AsyncReadExt, AsyncWriteExt};
+use tokio::time::{self, Duration, MissedTickBehavior};
+use tokio_serial::SerialStream;
 use tokio_util::sync::CancellationToken;
 
-use super::model::HudPacket;
+const AUTO_SUB_INTERVAL: Duration = Duration::from_nanos(16_666_667);
 
-pub struct SdkSession {
+pub enum PollMode<F> {
-    pub device: EskinDeviceInner,
+    Disable,
+    Enabled(Box<dyn PollRequester<F>>),
 }
 
-pub fn open_device(port: &str) -> Result<SdkSession, String> {
+struct PendingSubFrame<F> {
-    let port = port.trim();
+    frame: F,
-    if port.is_empty() {
+    values: Vec<i32>,
-        return Err("Serial port is required".to_string());
+}
+
+pub trait SerialFrame: Clone + Send + 'static {
+    fn dts_ms(&self) -> u64;
+
+    fn to_hud_packet(
+        &self,
+        chart_state: &mut HudChartState,
+        display_values: Option<&[i32]>,
+    ) -> Option<HudPacket>;
+}
+
+impl SerialFrame for TestFrame {
+    fn dts_ms(&self) -> u64 {
+        self.dts_ms
     }
 
-    let transport = SerialPortTransport::new(port, 921600);
+    fn to_hud_packet(
-    let config = DeviceConfig::default();
+        &self,
-    let mut device = EskinDeviceInner::new(config, Box::new(transport));
+        chart_state: &mut HudChartState,
-    device.open().map_err(|e| e.to_string())?;
+        display_values: Option<&[i32]>,
-
+    ) -> Option<HudPacket> {
-    Ok(SdkSession { device })
+        Some(chart_state.apply_frame(self, display_values))
+    }
 }
 
-pub async fn run_stream(
+impl SerialFrame for TactileAFrame {
+    fn dts_ms(&self) -> u64 {
+        match self {
+            TactileAFrame::Req(_) => 0,
+            TactileAFrame::Rep(rep) => rep.dts_ms,
+        }
+    }
+
+    fn to_hud_packet(
+        &self,
+        chart_state: &mut HudChartState,
+        display_values: Option<&[i32]>,
+    ) -> Option<HudPacket> {
+        match self {
+            TactileAFrame::Req(_) => None,
+            TactileAFrame::Rep(rep) => {
+                let proxy = TestFrame {
+                    header: rep.meta.header,
+                    cmd: rep.meta.func_code,
+                    length: rep.meta.except_data_len,
+                    payload: rep.payload.clone(),
+                    checksum: rep.meta.checksum,
+                    dts_ms: rep.dts_ms,
+                };
+
+                Some(chart_state.apply_frame(&proxy, display_values))
+            }
+        }
+    }
+}
+
+pub trait PollRequester<F>: Send {
+    fn poll_interval(&self) -> Option<Duration> {
+        None
+    }
+
+    fn should_request(&mut self) -> bool {
+        true
+    }
+
+    fn next_request(&mut self) -> Result<Option<F>> {
+        Ok(None)
+    }
+
+    fn on_rx_frame(&mut self, _frame: &F) {}
+}
+
+#[derive(Default)]
+pub struct NoopPollRequester;
+
+impl<F> PollRequester<F> for NoopPollRequester {}
+
+pub struct TactileAPollRequester {
+    period: Duration,
+    cols: usize,
+    rows: usize,
+    awaiting_reply: bool,
+    last_request_at: Option<Instant>,
+    reply_timeout: Duration,
+}
+
+impl TactileAPollRequester {
+    pub fn new(period: Duration, cols: usize, rows: usize, reply_timeout: Duration) -> Self {
+        Self {
+            period,
+            cols,
+            rows,
+            awaiting_reply: false,
+            last_request_at: None,
+            reply_timeout,
+        }
+    }
+}
+
+impl PollRequester<TactileAFrame> for TactileAPollRequester {
+    fn poll_interval(&self) -> Option<Duration> {
+        Some(self.period)
+    }
+
+    fn should_request(&mut self) -> bool {
+        if !self.awaiting_reply {
+            return true;
+        }
+        let timed_out = self
+            .last_request_at
+            .map(|t| t.elapsed() >= self.reply_timeout)
+            .unwrap_or(false);
+
+        if timed_out {
+            self.awaiting_reply = false;
+            self.last_request_at = None;
+            return true;
+        }
+
+        false
+    }
+
+    fn next_request(&mut self) -> Result<Option<TactileAFrame>> {
+        let req = TactileACodec::build_req_frame(self.cols, self.rows)?;
+        self.awaiting_reply = true;
+        self.last_request_at = Some(Instant::now());
+        Ok(Some(req))
+    }
+
+    fn on_rx_frame(&mut self, frame: &TactileAFrame) {
+        if matches!(frame, TactileAFrame::Rep(_)) {
+            self.awaiting_reply = false;
+            self.last_request_at = None
+        }
+    }
+}
+
+pub async fn run_serial<C, H, T, F>(
     app: AppHandle,
-    device: &mut EskinDeviceInner,
+    port: SerialStream,
+    codec: C,
+    handler: H,
+    session_started_at: Instant,
+    recording: Arc<Mutex<Recording<F>>>,
     cancel: CancellationToken,
-) -> Result<(), String> {
+) -> Result<()>
-    device
+where
-        .start_stream()
+    F: SerialFrame,
-        .map_err(|e| format!("start_stream failed: {e}"))?;
+    C: Codec<F> + Send + 'static,
+    H: FrameHandler<F, T> + Send + 'static,
+    T: Into<i32>,
+{
+    run_serial_with_poll(
+        app,
+        port,
+        codec,
+        handler,
+        session_started_at,
+        recording,
+        cancel,
+        PollMode::Disable,
+    )
+    .await
+}
 
-    let channels = device.channels();
+pub async fn run_serial_with_poll<C, H, T, F>(
-    let mut chart_state = HudChartState::new();
+    app: AppHandle,
-
+    mut port: SerialStream,
-    let result = loop {
+    mut codec: C,
-        tokio::select! {
+    mut handler: H,
-            _ = cancel.cancelled() => {
+    session_started_at: Instant,
-                break Ok(());
+    recording: Arc<Mutex<Recording<F>>>,
-            }
+    cancel: CancellationToken,
-            _ = tokio::time::sleep(tokio::time::Duration::from_millis(1)) => {}
+    poll_mode: PollMode<F>,
-        }
+) -> Result<()>
-
+where
-        // Try to receive a sample (non-blocking-ish via small timeout)
+    F: SerialFrame,
-        match channels.recv_sample(5) {
+    C: Codec<F> + Send + 'static,
-            Ok(sample) => {
+    H: FrameHandler<F, T> + Send + 'static,
-                if let Some(packet) = build_hud_packet_from_sample(&sample, &mut chart_state) {
+    T: Into<i32>,
-                    let _ = app.emit("hud_stream", packet);
+{
-                }
+    let mut requester = match poll_mode {
-            }
+        PollMode::Disable => None,
-            Err(eskin_finger_sdk::error::SdkError::Timeout) => {
+        PollMode::Enabled(r) => Some(r),
-                // No sample yet, check for events
-            }
-            Err(e) => {
-                break Err(format!("sample recv error: {e}"));
-            }
-        }
-
-        // Drain any events
-        if let Err(e) = drain_events(&channels) {
-            break Err(e);
-        }
     };
 
-    let _ = device.stop_stream();
+    let mut poll_interval = requester.as_ref().and_then(|r| r.poll_interval()).map(|d| {
-    result
+        let mut it = time::interval(d);
-}
+        it.set_missed_tick_behavior(MissedTickBehavior::Skip);
+        it
+    });
+    let mut poll_sub_interval = time::interval(AUTO_SUB_INTERVAL);
+    poll_sub_interval.set_missed_tick_behavior(MissedTickBehavior::Skip);
 
-pub async fn run_stream_with_record(
-    app: AppHandle,
-    device: &mut EskinDeviceInner,
-    cancel: CancellationToken,
-    recording: std::sync::Arc<std::sync::Mutex<Recording<FingerSample>>>,
-) -> Result<(), String> {
-    device
-        .start_stream()
-        .map_err(|e| format!("start_stream failed: {e}"))?;
-
-    let channels = device.channels();
     let mut chart_state = HudChartState::new();
+    let mut buffer = [0u8; 1024];
+    let mut prune_interval = time::interval(Duration::from_millis(450));
+    #[cfg(feature = "multi-dim")]
+    let mut pzt_processor = PztProcessor::new();
+    let mut force_estimator = BasinForceEstimator::new();
+    let mut pending_sub_frame: Option<PendingSubFrame<F>> = None;
+    prune_interval.set_missed_tick_behavior(MissedTickBehavior::Delay);
 
-    let result = loop {
+    loop {
         tokio::select! {
-            _ = cancel.cancelled() => {
+            _ = cancel.cancelled() => break,
-                break Ok(());
+            _ = async {
+                match poll_interval.as_mut() {
+                    Some(it) => {
+                        it.tick().await;
+                    }
+                    None => pending::<()>().await,
+                }
+            } => {
+                if let Some(r) = requester.as_mut() {
+                    if r.should_request() {
+                        if let Some(req) = r.next_request()? {
+                            let bytes = codec.encode(&req)?;
+                            port.write_all(&bytes).await?;
+                        }
+                    }
+                }
             }
-            _ = tokio::time::sleep(tokio::time::Duration::from_millis(1)) => {}
+            _ = prune_interval.tick() => {
-        }
+                if let Some(packet) = chart_state.prune_stale() {
+                    app.emit("hud_stream", packet)?;
+                }
+            }
+            _ = poll_sub_interval.tick() => {
+                if let Some(pending) = pending_sub_frame.take() {
+                    let display_values = build_display_values(
+                        &mut chart_state,
+                        pending.values.as_slice(),
+                    );
+
+                    if let Some(packet) = pending
+                        .frame
+                        .to_hud_packet(&mut chart_state, display_values.as_deref())
+                    {
+                        app.emit("hud_stream", packet)?;
+                    }
+                }
+            }
+            read_result = port.read(&mut buffer) => {
+                let n = read_result?;
+                if n == 0 {
+                    // Some serial drivers can resolve reads with 0 bytes repeatedly.
+                    // Yield here so timer-driven poll requests are not starved by a busy loop.
+                    tokio::task::yield_now().await;
+                    continue;
+                }
+
+                let frames = codec.decode(&buffer[..n], session_started_at)?;
+                for frame in frames {
+                    if let Some(r) = requester.as_mut() {
+                        r.on_rx_frame(&frame);
+                    }
+
+                    let decode_res = handler
+                        .on_frame(&frame)
+                        .await?
+                        .map(|vals| vals.into_iter().map(Into::into).collect::<Vec<i32>>());
 
-        match channels.recv_sample(5) {
-            Ok(sample) => {
-                // Record
-                {
                     let mut record = recording
                         .lock()
-                        .map_err(|_| "recording state poisoned".to_string())?;
+                        .map_err(|_| anyhow::anyhow!("recording state poisoned"))?;
-                    record.push(crate::serial_core::record::RecordedFrame {
+                    record.push(RecordedFrame {
-                        timing: crate::serial_core::record::FrameTiming {
+                        timing: FrameTiming {
                             pts_ms: None,
-                            dts_ms: sample.timestamp_us / 1000,
+                            dts_ms: frame.dts_ms(),
                         },
-                        frame: sample.clone(),
+                        frame: frame.clone(),
                     });
-                }
+                    drop(record);
 
-                if let Some(packet) = build_hud_packet_from_sample(&sample, &mut chart_state) {
+                    if let Some(vals) = decode_res {
-                    let _ = app.emit("hud_stream", packet);
+                        // Basin force estimation (pre-force)
+                        if vals.len() == 84 {
+                            let mut frame_f64 = [0.0f64; 84];
+                            for (i, v) in vals.iter().enumerate() {
+                                frame_f64[i] = *v as f64;
+                            }
+                            let pre_force = force_estimator.predict_frame(&frame_f64);
+                            debug!("pre-force: {:.2}", pre_force);
+                        }
+
+                        #[cfg(feature = "multi-dim")]
+                        {
+                            let pzt_values = vals.iter().map(|value| *value as f32).collect::<Vec<f32>>();
+                            if let Ok(angle) = pzt_processor.get_pzt_angle(&pzt_values) {
+                                // debug!("pzt angle: {:.2}", angle);
+                            }
+                        }
+                        #[cfg(feature = "devkit")]
+                        {
+                            let summary = vals.iter().copied().sum::<i32>();
+                            let force = raw_to_g1(summary as u32);
+                            push_devkit_frame(&app, vals.as_slice(), frame.dts_ms(), force);
+                        }
+
+                        pending_sub_frame = Some(PendingSubFrame {
+                            frame: frame.clone(),
+                            values: vals,
+                        });
+                    } else if let Some(packet) = frame.to_hud_packet(&mut chart_state, None) {
+                        app.emit("hud_stream", packet)?;
+                    }
                 }
             }
-            Err(eskin_finger_sdk::error::SdkError::Timeout) => {}
-            Err(e) => {
-                break Err(format!("sample recv error: {e}"));
-            }
-        }
-
-        if let Err(e) = drain_events(&channels) {
-            break Err(e);
-        }
-    };
-
-    let _ = device.stop_stream();
-    result
-}
-
-fn drain_events(channels: &std::sync::Arc<eskin_finger_sdk::channel::ChannelManager>) -> Result<(), String> {
-    loop {
-        match channels.recv_event(0) {
-            Ok(DeviceEvent::IoError(msg)) => {
-                eprintln!("SDK stream io error: {msg}");
-                return Err(format!("stream io error: {msg}"));
-            }
-            Ok(_) => {}
-            Err(eskin_finger_sdk::error::SdkError::Timeout) => return Ok(()),
-            Err(eskin_finger_sdk::error::SdkError::ChannelClosed) => {
-                return Err("event channel closed".into());
-            }
-            Err(_) => return Ok(()),
         }
     }
+    Ok(())
 }
 
-fn build_hud_packet_from_sample(
+fn build_display_values(chart_state: &mut HudChartState, values: &[i32]) -> Option<Vec<i32>> {
-    sample: &FingerSample,
+    let summary = values.iter().copied().sum::<i32>();
-    chart_state: &mut HudChartState,
+    let force = raw_to_g1(summary as u32);
-) -> Option<HudPacket> {
+    chart_state.record_summary(force as f32);
-    let fz = sample.combined_forces.force.fz as f32;
+    chart_state.record_pressure_matrix(values);
-    chart_state.record_summary(fz);
+    Some(vec![summary])
-    if !sample.raw_adcs.is_empty() {
+}
-        let pressure: Vec<f32> = sample.raw_adcs.iter().map(|&v| v as f32).collect();
+
-        chart_state.record_pressure_matrix(&pressure);
+#[cfg(feature = "devkit")]
-    }
+fn push_devkit_frame(app: &AppHandle, values: &[i32], dts_ms: u64, resultant_force: f64) {
-    Some(chart_state.build_snapshot())
+    let devkit_state = app.state::<DevKitState>();
+    if !devkit_state.running.load(Ordering::Relaxed) {
+        return;
+    }
+
+    let (rows, cols) = infer_matrix_shape(values.len());
+    let timestamp_ms = std::time::SystemTime::now()
+        .duration_since(std::time::UNIX_EPOCH)
+        .unwrap_or_default()
+        .as_millis() as u64;
+
+    let seq = timestamp_ms;
+    let matrix = values
+        .iter()
+        .map(|value| (*value).max(0) as u32)
+        .collect::<Vec<_>>();
+
+    devkit_state.push_frame(SensorFrame {
+        seq,
+        timestamp_ms,
+        rows,
+        cols,
+        matrix,
+        resultant_force,
+        dts_ms: dts_ms as u32,
+    });
+}
+
+#[cfg(feature = "devkit")]
+fn infer_matrix_shape(len: usize) -> (u32, u32) {
+    if len == 84 {
+        return (12, 7);
+    }
+
+    if len == 0 {
+        return (0, 0);
+    }
+
+    let mut best = (len, 1);
+    let mut factor = 1usize;
+    while factor * factor <= len {
+        if len % factor == 0 {
+            best = (len / factor, factor);
+        }
+        factor += 1;
+    }
+
+    (best.0 as u32, best.1 as u32)
+}
+
+fn raw_to_g1(raw: u32) -> f64 {
+    const X: [u32; 12] = [
+        0, 84402, 117218, 140176, 159126, 175812, 191484, 208758, 224703, 252448, 302361, 352703,
+    ];
+
+    const Y: [f64; 12] = [
+        0.0, 160.0, 260.0, 360.0, 460.0, 560.0, 660.0, 760.0, 860.0, 1060.0, 1560.0, 2060.0,
+    ];
+
+    let n = X.len();
+    if raw <= X[0] {
+        return Y[0] / 100.0;
+    }
+    if raw >= X[n - 1] {
+        return Y[n - 1] / 100.0;
+    }
+
+    let mut left = 0;
+    let mut right = n - 1;
+
+    while left + 1 < right {
+        let mid = (left + right) / 2;
+        if raw < X[mid] {
+            right = mid;
+        } else {
+            left = mid;
+        }
+    }
+
+    let ratio = (raw - X[left]) as f64 / (X[right] - X[left]) as f64;
+    Y[left] / 100.0 + ratio * (Y[right] - Y[left]) / 100.0
 }

src-tauri/src/serial_core/utils.rs

@@ -0,0 +1,59 @@
+
+use std::time::Instant;
+
+pub fn usize_to_u16_be_bytes(n: usize) -> [u8; 2] {
+    (n as u16).to_be_bytes()
+}
+
+pub fn usize_to_u16_le_bytes(n: usize) -> [u8; 2] {
+    (n as u16).to_be_bytes()
+}
+
+pub fn u16_to_hex_be_bytes(n: u16) -> [u8; 2] {
+    (n as u16).to_be_bytes()
+}
+
+pub fn u16_to_hex_le_bytes(n: u16) -> [u8; 2] {
+    (n as u16).to_le_bytes()
+}
+
+pub fn calc_crc8_smbus(c: &[u8]) -> u8 {
+    let crc8_smbus = crc::Crc::<u8>::new(&crc::CRC_8_SMBUS);
+    let checksum = crc8_smbus.checksum(c);
+    return checksum;
+}
+
+pub fn calc_crc8_itu(c: &[u8]) -> u8 {
+    let crc8_itu_alg = crc::Crc::<u8>::new(&crc::CRC_8_I_432_1);
+    let checksum = crc8_itu_alg.checksum(c);
+    return checksum;
+}
+
+pub fn elapsed_millis(start_at: Instant) -> u64 {
+    start_at.elapsed().as_millis() as u64
+}
+
+#[cfg(test)]
+mod test {
+    use anyhow::Ok;
+
+    use crate::serial_core::utils::{calc_crc8_itu, calc_crc8_smbus};
+
+    #[test]
+    fn test_crc8_itu() -> anyhow::Result<()> {
+        let req_vec = vec![0x55, 0xAA, 0x09, 0x00, 0x34, 0x00, 0xFB, 0x00, 0x1C, 0x00, 0x00, 0x18, 0x00];
+        let checksum = calc_crc8_itu(req_vec.as_slice());
+        assert_eq!(checksum, 0x7A);
+
+        Ok(())
+    }
+
+    #[test]
+    fn test_crc8_smbus() -> anyhow::Result<()> {
+        let req_vec = vec![0x55, 0xAA, 0x09, 0x00, 0x34, 0x00, 0xFB, 0x00, 0x1C, 0x00, 0x00, 0x18, 0x00];
+        let checksum = calc_crc8_smbus(req_vec.as_slice());
+        assert_eq!(checksum, 0x2F);
+
+        Ok(())
+    }
+}

src-tauri/tauri.conf.json

@@ -23,7 +23,7 @@
     }
   },
   "bundle": {
-    "createUpdaterArtifacts": true,
+    "createUpdaterArtifacts": false,
     "active": true,
     "targets": "all",
     "icon": [

src/indicator/indicator498.py

@@ -0,0 +1,747 @@
+from typing import Dict, List, Tuple
+import numpy as np
+from indicator.base import Indicator
+import math
+
+
+class EMA:
+    """指数移动平均"""
+
+    @staticmethod
+    def calc(data: np.ndarray, period: int) -> np.ndarray:
+        alpha = 2.0 / (period + 1)
+        out = np.empty_like(data)
+        out[0] = data[0]
+        for i in range(1, len(data)):
+            out[i] = alpha * data[i] + (1 - alpha) * out[i - 1]
+        return out
+
+
+class SMA:
+    """简单移动平均"""
+
+    @staticmethod
+    def calc(data: np.ndarray, period: int) -> np.ndarray:
+        out = np.full_like(data, np.nan)
+        if len(data) < period:
+            return out
+        cumsum = np.cumsum(data)
+        out[period - 1:] = (cumsum[period - 1:] - np.concatenate([[0], cumsum[:-period]])) / period
+        return out
+
+
+def true_range(high: np.ndarray, low: np.ndarray, close: np.ndarray) -> np.ndarray:
+    """True Range"""
+    tr = np.empty(len(high))
+    tr[0] = high[0] - low[0]
+    for i in range(1, len(high)):
+        tr[i] = max(high[i] - low[i], abs(high[i] - close[i - 1]), abs(low[i] - close[i - 1]))
+    return tr
+
+
+class SignalTracker:
+    """逐帧更新的信号追踪器（无回看依赖，纯实时）"""
+
+    def __init__(
+        self,
+        ob_threshold: float = 80,
+        os_threshold: float = 20,
+        dist_extreme: float = 5,
+        dist_far: float = 15,
+        dist_mid: float = 30,
+        macd_th: float = 0.3,
+        rsi_ob: float = 70,
+        rsi_os: float = 30,
+        di_gap_bull: float = 15,
+        di_gap_bear: float = -15,
+        aroon_ob: float = 80,
+        aroon_os: float = 20,
+        williams_ob: float = -20,
+        williams_os: float = -80,
+        bias_ob: float = 5,
+        bias_os: float = -5,
+    ):
+        self.ob_threshold = ob_threshold
+        self.os_threshold = os_threshold
+        self.dist_extreme = dist_extreme
+        self.dist_far = dist_far
+        self.dist_mid = dist_mid
+        self.macd_th = macd_th
+        self.rsi_ob = rsi_ob
+        self.rsi_os = rsi_os
+        self.di_gap_bull = di_gap_bull
+        self.di_gap_bear = di_gap_bear
+        self.aroon_ob = aroon_ob
+        self.aroon_os = aroon_os
+        self.williams_ob = williams_ob
+        self.williams_os = williams_os
+        self.bias_ob = bias_ob
+        self.bias_os = bias_os
+
+        # 状态缓存
+        self._intp_buy_sma: float = 0.0
+        self._intp_sell_sma: float = 0.0
+        self._intp_sma_count: int = 0
+        self._max_qtb_score: float = 0.0
+        self._bull_count: int = 0
+        self._bear_count: int = 0
+        self._last_bull_idx: int = -100
+        self._last_bear_idx: int = -100
+        self._frame_idx: int = 0
+
+        # 历史缓冲区（保留最近200帧用于EMA/SMA/DI计算）
+        self._buf_size: int = 200
+        self._bbi_buf: List[float] = []
+        self._amplitude_buf: List[float] = []
+        self._close_buf: List[float] = []
+        self._high_buf: List[float] = []
+        self._low_buf: List[float] = []
+        self._wr_buf: List[float] = []
+
+    def reset(self):
+        """重置所有状态"""
+        self._intp_buy_sma = 0.0
+        self._intp_sell_sma = 0.0
+        self._intp_sma_count = 0
+        self._max_qtb_score = 0.0
+        self._bull_count = 0
+        self._bear_count = 0
+        self._last_bull_idx = -100
+        self._last_bear_idx = -100
+        self._frame_idx = 0
+        self._bbi_buf.clear()
+        self._amplitude_buf.clear()
+        self._close_buf.clear()
+        self._high_buf.clear()
+        self._low_buf.clear()
+        self._wr_buf.clear()
+
+    def _append_buf(self, buf: List[float], val: float):
+        buf.append(val)
+        if len(buf) > self._buf_size:
+            buf.pop(0)
+
+    def _ema_val(self, buf: List[float], period: int) -> float:
+        """返回缓冲区中最后一个EMA值"""
+        if len(buf) < period:
+            return buf[-1] if buf else 0.0
+        arr = np.array(buf, dtype=float)
+        ema = EMA.calc(arr, period)
+        return float(ema[-1])
+
+    def _sma_val(self, buf: List[float], period: int) -> float:
+        if len(buf) < period:
+            return np.nan
+        arr = np.array(buf, dtype=float)
+        sma = SMA.calc(arr, period)
+        return float(sma[-1])
+
+    def get_signals(
+        self,
+        amplitude: float,
+        bbi: float,
+        cci: float,
+        close: float,
+        dmk: float,
+        high: float,
+        k: float,
+        low: float,
+        qtb_score: float,
+        result: float,
+        wr: float,
+        percent: float,
+        v0: float,
+        boll_upper: float,
+        boll_lower: float,
+        macd_val: float,
+        pmacd: float,
+        bias: float,
+    ) -> Tuple[str, str, str, str]:
+        """
+        逐帧更新，返回 (market_status, signal_type, intensity, detail)
+
+        不依赖历史数组，所有指标值由外部实时计算后传入。
+        """
+
+        # ─── 更新缓冲区 ───
+        self._append_buf(self._bbi_buf, bbi)
+        self._append_buf(self._amplitude_buf, amplitude)
+        self._append_buf(self._close_buf, close)
+        self._append_buf(self._high_buf, high)
+        self._append_buf(self._low_buf, low)
+        self._append_buf(self._wr_buf, wr)
+
+        # ─── 指标因子计算（使用传入值 + 缓冲区衍生值）───
+        k_macd = self._k_macd_factor(k, macd_val, pmacd)
+        k_di = self._k_di_factor(dmk, amplitude, close)
+        k_aroon = self._k_aroon_factor(high, low, close)
+        k_williams = self._k_williams_factor(wr)
+        k_result = self._k_result_factor(result)
+        k_bias = self._k_bias_factor(bias)
+        k_trix = self._k_trix_factor(close)
+        k_ema = self._k_ema_factor(close)
+        k_amplitude = self._k_amplitude_factor(amplitude)
+
+        # ─── 累计 ───
+        k_bull = k_macd + k_di + k_aroon + k_williams + k_result + k_bias + k_trix + k_ema + k_amplitude
+        k_bear = k_macd + k_di + k_aroon + k_williams + k_result + k_bias + k_trix + k_ema + k_amplitude
+
+        if result > self.ob_threshold and k_bull > 0 and result >= 90:
+            k_bull *= 1.5
+
+        # ─── 指数平滑 ───
+        if self._intp_sma_count == 0:
+            self._intp_buy_sma = k_bull
+            self._intp_sell_sma = k_bear
+            self._intp_sma_count = 1
+        else:
+            self._intp_sma_count += 1
+            period = max(3, min(5, self._intp_sma_count))
+            alpha = 2.0 / (period + 1)
+            self._intp_buy_sma = alpha * k_bull + (1 - alpha) * self._intp_buy_sma
+            self._intp_sell_sma = alpha * k_bear + (1 - alpha) * self._intp_sell_sma
+
+        # ─── 趋势确认与背离检测 ───
+        is_bull_div, is_bear_div = self._detect_divergence(close, result)
+        if is_bull_div:
+            self._intp_buy_sma *= 1.3
+            k_bull *= 1.3
+        if is_bear_div:
+            self._intp_sell_sma *= 1.3
+            k_bear *= 1.3
+
+        is_bull, is_bear = self._detect_trend(close)
+        if is_bull:
+            self._intp_buy_sma *= 1.15
+            k_bull *= 1.15
+        if is_bear:
+            self._intp_sell_sma *= 1.15
+            k_bear *= 1.15
+
+        wmacd = self._wmacd()
+        if wmacd > 0:
+            k_bull += wmacd * 0.5
+        elif wmacd < 0:
+            k_bear += abs(wmacd) * 0.5
+
+        if qtb_score > self._max_qtb_score * 0.7:
+            pass
+        elif qtb_score < 3 and qtb_score > 1:
+            k_bull *= 0.85
+            k_bear *= 0.85
+
+        # ─── 信号分类 ───
+        max_k = max(abs(k_bull), abs(k_bear))
+        if max_k > 0:
+            buy_score = ((k_bull + max_k) / (2 * max_k)) * 100
+            sell_score = ((k_bear + max_k) / (2 * max_k)) * 100
+        else:
+            buy_score = sell_score = 50
+
+        bull_t = buy_score > 70 and result < 90
+        bear_t = sell_score > 70 and result > 10
+        k_cci = cci / 300
+        boll_mid = self._boll_mid()
+
+        is_bull_t = (
+            bull_t
+            and k_bull > k_cci
+            and close < boll_mid
+            and (
+                (result > 65 and result < 85 and k_bull > 0 and k_bear > 0 and (k_bear - k_bull < 1.5 or result > 75))
+                or (result < 35 and result > 15 and k_bear > 0 and k_bull > 0 and (k_bull - k_bear < 1.5 or result < 25))
+            )
+        )
+        is_bear_t = (
+            bear_t
+            and k_bear > k_cci
+            and close > boll_mid
+            and (
+                (result > 65 and result < 85 and k_bull > 0 and k_bear > 0 and (k_bear - k_bull < 1.5 or result > 75))
+                or (result < 35 and result > 15 and k_bear > 0 and k_bull > 0 and (k_bull - k_bear < 1.5 or result < 25))
+            )
+        )
+
+        if is_bull_t:
+            self._bull_count += 1
+            self._bear_count = 0
+            self._last_bull_idx = self._frame_idx
+        elif is_bear_t:
+            self._bear_count += 1
+            self._bull_count = 0
+            self._last_bear_idx = self._frame_idx
+        else:
+            self._bull_count = max(self._bull_count - 1, 0)
+            self._bear_count = max(self._bear_count - 1, 0)
+
+        # ─── 信号输出 ───
+        sig_strength = 1.0 + max(0, (self._bull_count - 3) * 0.1) + max(0, (self._bear_count - 3) * 0.1)
+
+        strength = (
+            "极强" if sig_strength >= 1.7
+            else "强" if sig_strength >= 1.4
+            else "中" if sig_strength >= 1.1
+            else "弱"
+        )
+
+        if buy_score >= sell_score:
+            signal = f"买{strength}"
+        else:
+            signal = f"卖{strength}"
+
+        # ─── 市场状态 ───
+        if abs(buy_score - sell_score) < 10:
+            status = "中性震荡"
+        elif buy_score > sell_score:
+            if self._bull_count >= 3:
+                status = "强势上涨"
+            elif result > self.ob_threshold:
+                status = "高位企稳"
+            else:
+                status = "温和上涨"
+        else:
+            if self._bear_count >= 3:
+                status = "强势下跌"
+            elif result < self.os_threshold:
+                status = "低位企稳"
+            else:
+                status = "温和下跌"
+
+        # ─── 距离 ───
+        boll_len = boll_upper - boll_lower
+        if boll_len > 0:
+            dist_ratio = (close - boll_lower) / boll_len * 100
+        else:
+            dist_ratio = 50
+
+        if dist_ratio < 50 - self.dist_extreme:
+            dist = "极端超卖"
+        elif dist_ratio < 50 - self.dist_far:
+            dist = "远离"
+        elif dist_ratio < 50 - self.dist_mid:
+            dist = "偏离"
+        elif dist_ratio < 50 + self.dist_mid:
+            dist = "接近"
+        elif dist_ratio < 50 + self.dist_far:
+            dist = "靠近"
+        elif dist_ratio < 50 + self.dist_extreme:
+            dist = "远超"
+        else:
+            dist = "极端超买"
+
+        # ─── 强度 ───
+        max_score = max(buy_score, sell_score)
+        intensity = (
+            "超强" if max_score >= 90
+            else "强" if max_score >= 80
+            else "中" if max_score >= 65
+            else "弱" if max_score >= 55
+            else "极弱"
+        )
+
+        # ─── 详情 ───
+        bias_val = self._ema_bias()
+        bbp_val = self._boll_pct_b(close, boll_upper, boll_lower)
+        detail = (
+            f"前量:{percent:.1f} 数量:{int(amplitude):03d} 百分比:{bbp_val:.1f} "
+            f"正:{k_bull:.1f} 负:{k_bear:.1f} 连买:{self._bull_count} 连卖:{self._bear_count} "
+            f"误差:{bias_val:.1f}"
+        )
+
+        self._frame_idx += 1
+        return status, signal, intensity, detail
+
+    # ═══════════════════════════════════════════════════
+    #  指标因子（全部基于实时数据，无回看窗口）
+    # ═══════════════════════════════════════════════════
+
+    def _k_macd_factor(self, k: float, macd_val: float, pmacd: float) -> float:
+        is_ob = k > self.ob_threshold
+        is_os = k < self.os_threshold
+        k_macd = 0.0
+        if is_ob or is_os:
+            if macd_val < 0:
+                if is_os and k < 30 and pmacd > 0 and pmacd <= 10 and macd_val > 1.5:
+                    k_macd = 3.5
+                elif is_ob and k > 80 and macd_val > 3 and abs(pmacd) < 5:
+                    k_macd = -3.5
+        elif pmacd < 0 and macd_val < 0:
+            if abs(pmacd) > 15 and macd_val >= -0.5:
+                k_macd = 3.5
+            elif 5 < abs(pmacd) < 15 and macd_val > 0.7:
+                k_macd = 3.5
+        elif pmacd > 0 and macd_val > 0:
+            if pmacd >= 15 and macd_val < 0.5:
+                k_macd = -3.5
+            elif 5 < pmacd < 15 and macd_val < -0.7:
+                k_macd = -3.5
+        elif macd_val >= 3:
+            k_macd = macd_val * 1.5
+        elif macd_val <= -3:
+            k_macd = macd_val * 1.5
+        return k_macd
+
+    def _k_di_factor(self, dmk: float, amplitude: float, close: float) -> float:
+        if len(self._close_buf) < 20:
+            return 0.0
+        k_close = np.array(self._close_buf, dtype=float)
+        period = 14
+        if len(k_close) < period + 1:
+            return 0.0
+        dx_list = []
+        for i in range(1, min(period + 1, len(k_close))):
+            diff = k_close[-i] - k_close[-i - 1]
+            dx_list.append(diff)
+        if not dx_list:
+            return 0.0
+        last_diff = dx_list[0]
+        adx_val = abs(dmk) * 0.5
+
+        k_di = 0.0
+        if adx_val < 20:
+            return 0.0
+        if dmk > 0 and len(dx_list) > 5:
+            gains = [d for d in dx_list[:5] if d > 0]
+            if len(gains) >= 3 and last_diff > 0:
+                k_di = min(adx_val / 5, 6.0)
+        elif dmk < 0 and len(dx_list) > 5:
+            losses = [d for d in dx_list[:5] if d < 0]
+            if len(losses) >= 3 and last_diff < 0:
+                k_di = -min(adx_val / 5, 6.0)
+        return k_di
+
+    def _k_aroon_factor(self, high: float, low: float, close: float) -> float:
+        period = 14
+        if len(self._high_buf) < period:
+            return 0.0
+        highs = self._high_buf[-period:]
+        lows = self._low_buf[-period:]
+        highest = max(highs)
+        lowest = min(lows)
+        rng = highest - lowest
+        if rng == 0:
+            return 0.0
+        k_aroon = 0.0
+        pct = (close - lowest) / rng * 100
+        if pct >= self.aroon_ob:
+            if close >= highest * 0.995:
+                k_aroon = -2.0
+            else:
+                k_aroon = 2.0
+        elif pct <= self.aroon_os:
+            if close <= lowest * 1.005:
+                k_aroon = 2.0
+            else:
+                k_aroon = -2.0
+        else:
+            k_aroon = (pct - 50) / 50 * 1.2
+        return k_aroon
+
+    def _k_williams_factor(self, wr: float) -> float:
+        k_wr = 0.0
+        if wr > self.williams_ob:
+            if wr > -10:
+                k_wr = -1.2
+            else:
+                k_wr = -0.8
+        elif wr < self.williams_os:
+            if wr < -90:
+                k_wr = 1.2
+            else:
+                k_wr = 0.8
+        return k_wr
+
+    def _k_result_factor(self, result: float) -> float:
+        k_result = 0.0
+        is_ob = result > self.ob_threshold
+        is_os = result < self.os_threshold
+        if is_os and result < 10:
+            k_result = 1.5
+        elif is_ob and result > 90:
+            k_result = -1.5
+        return k_result
+
+    def _k_bias_factor(self, bias: float) -> float:
+        k_bias = 0.0
+        if bias < self.bias_os and bias < -3:
+            k_bias = min(abs(bias) / 5, 2.5)
+        elif bias > self.bias_ob and bias > 3:
+            k_bias = -min(abs(bias) / 5, 2.5)
+        return k_bias
+
+    def _k_trix_factor(self, close: float) -> float:
+        ema3 = self._ema_val(self._close_buf, 3)
+        ema9 = self._ema_val(self._close_buf, 9)
+        if ema9 == 0:
+            return 0.0
+        trix = (ema3 - ema9) / ema9 * 100
+        k_trix = 0.0
+        if trix > 0:
+            k_trix = min(trix / 2, 3.0)
+        elif trix < 0:
+            k_trix = max(trix / 2, -3.0)
+        return k_trix
+
+    def _k_ema_factor(self, close: float) -> float:
+        ema9 = self._ema_val(self._close_buf, 9)
+        if ema9 == 0:
+            return 0.0
+        bias = (close - ema9) / ema9 * 100
+        k_ema = 0.0
+        if bias < -2:
+            k_ema = min(abs(bias) * 0.3, 2.0)
+        elif bias > 2:
+            k_ema = -min(abs(bias) * 0.3, 2.0)
+        return k_ema
+
+    def _k_amplitude_factor(self, amplitude: float) -> float:
+        if len(self._amplitude_buf) < 10:
+            return 0.0
+        buf = self._amplitude_buf[-10:]
+        mean = sum(buf) / len(buf)
+        if mean == 0:
+            return 0.0
+        ratio = (amplitude - mean) / mean
+        k_amp = 0.0
+        if ratio > 0.5:
+            k_amp = min(ratio * 1.5, 3.0)
+        elif ratio < -0.3:
+            k_amp = max(ratio * 1.5, -3.0)
+        return k_amp
+
+    def _detect_divergence(self, close: float, result: float) -> Tuple[bool, bool]:
+        """简化背离检测（基于累计计数）"""
+        is_bull_div = False
+        is_bear_div = False
+        if len(self._close_buf) > 30:
+            c30 = self._close_buf[-30]
+            if close > c30 * 1.05 and result < 50:
+                is_bull_div = True
+            elif close < c30 * 0.95 and result > 50:
+                is_bear_div = True
+        return is_bull_div, is_bear_div
+
+    def _detect_trend(self, close: float) -> Tuple[bool, bool]:
+        """简化趋势确认"""
+        is_bull = False
+        is_bear = False
+        if len(self._close_buf) > 20:
+            c20 = self._close_buf[-20]
+            if close > c20 * 1.05:
+                is_bull = True
+            elif close < c20 * 0.95:
+                is_bear = True
+        return is_bull, is_bear
+
+    def _wmacd(self) -> float:
+        """简化加权MACD（基于缓冲区）"""
+        if len(self._close_buf) < 12:
+            return 0.0
+        ema12 = self._ema_val(self._close_buf, 12)
+        ema26 = self._ema_val(self._close_buf, 26)
+        return ema12 - ema26
+
+    def _boll_mid(self) -> float:
+        if len(self._close_buf) < 20:
+            return self._close_buf[-1] if self._close_buf else 0.0
+        return sum(self._close_buf[-20:]) / 20
+
+    def _ema_bias(self) -> float:
+        if not self._close_buf:
+            return 0.0
+        ema5 = self._ema_val(self._close_buf, 5)
+        ema10 = self._ema_val(self._close_buf, 10)
+        if ema10 == 0:
+            return 0.0
+        return (ema5 - ema10) / ema10 * 1000
+
+    def _boll_pct_b(self, close: float, upper: float, lower: float) -> float:
+        boll_len = upper - lower
+        if boll_len == 0:
+            return 50.0
+        return (close - lower) / boll_len * 100
+
+
+def get_signals(indicator: Indicator) -> Tuple[str, str, str, str]:
+    """
+    基于技术指标生成交易信号（逐帧调用版）
+
+    参数：
+        indicator: Indicator 对象，包含所有实时指标值
+
+    返回：
+        tuple: (market_status, signal_type, intensity, detail)
+    """
+    # ─── 指标提取 ───
+    bbi = indicator.BBI
+    amplitude = indicator.AMPLITUDE
+    cci = indicator.CCI
+    close = indicator.CLOSE
+    dmk = indicator.DMK
+    high = indicator.HIGH
+    k = indicator.K
+    low = indicator.LOW
+    macd_val = indicator.MACD
+    ob = indicator.OB
+    os_ = indicator.OS
+    ovs = indicator.OVS
+    ovc = indicator.OVC
+    result = indicator.RESULT
+    wr = indicator.WR
+    percent = indicator.PERCENT
+    v0 = indicator.V0
+    boll_upper = indicator.BOLL_UP
+    boll_lower = indicator.BOLL_LO
+    bias = indicator.BIAS
+
+    # ─── 指标阈值 ───
+    ob_threshold = ob if ob > 0 else 80
+    os_threshold = os_ if os_ > 0 else 20
+    dist_extreme = ovc if ovc > 0 else 5
+    dist_far = ovs if ovs > 0 else 15
+    dist_mid = 30
+    macd_th = 0.3
+    rsi_ob = ovc if ovc > 0 else 70
+    rsi_os = ovs if ovs > 0 else 30
+    di_gap_bull = ovc if ovc > 0 else 15
+    di_gap_bear = -di_gap_bull
+    aroon_ob = ob_threshold
+    aroon_os = os_threshold
+    williams_ob = -20
+    williams_os = -80
+    bias_ob = 5
+    bias_os = -5
+
+    # ─── 指标因子 ───
+    pmacd = getattr(indicator, 'PMACD', macd_val)
+
+    k_macd = _k_macd_factor(ob_threshold, os_threshold, k, macd_val, pmacd)
+    k_di = _k_di_factor(dmk, amplitude, close)
+    k_aroon = _k_aroon_factor(aroon_ob, aroon_os, high, low, close)
+    k_williams = _k_williams_factor(williams_ob, williams_os, wr)
+    k_result = _k_result_factor(ob_threshold, os_threshold, result)
+    k_bias = _k_bias_factor(bias_ob, bias_os, bias)
+
+    # ─── K值累计 ───
+    k_bull = k_macd + k_di + k_aroon + k_williams + k_result + k_bias
+    k_bear = k_macd + k_di + k_aroon + k_williams + k_result + k_bias
+
+    if result > ob_threshold and k_bull > 0 and result >= 90:
+        k_bull *= 1.5
+
+    # ─── 强度计算 ───
+    max_k = max(abs(k_bull), abs(k_bear))
+    if max_k > 0:
+        buy_score = ((k_bull + max_k) / (2 * max_k)) * 100
+        sell_score = ((k_bear + max_k) / (2 * max_k)) * 100
+    else:
+        buy_score = sell_score = 50
+
+    # ─── 信号判断 ───
+    bull_t = buy_score > 70 and result < 90
+    bear_t = sell_score > 70 and result > 10
+
+    k_cci = cci / 300
+    boll_mid = indicator.BOLL_MID if hasattr(indicator, 'BOLL_MID') else (boll_upper + boll_lower) / 2
+    boll_len = boll_upper - boll_lower
+
+    is_bull_t = (
+        bull_t
+        and k_bull > k_cci
+        and close < boll_mid
+        and (
+            (result > 65 and result < 85 and k_bull > 0 and k_bear > 0 and (k_bear - k_bull < 1.5 or result > 75))
+            or (result < 35 and result > 15 and k_bear > 0 and k_bull > 0 and (k_bull - k_bear < 1.5 or result < 25))
+        )
+    )
+    is_bear_t = (
+        bear_t
+        and k_bear > k_cci
+        and close > boll_mid
+        and (
+            (result > 65 and result < 85 and k_bull > 0 and k_bear > 0 and (k_bear - k_bull < 1.5 or result > 75))
+            or (result < 35 and result > 15 and k_bear > 0 and k_bull > 0 and (k_bull - k_bear < 1.5 or result < 25))
+        )
+    )
+
+    # ─── 信号强度 ───
+    sig_strength = 1.0
+    if is_bull_t:
+        sig_strength += 0.3 + max(0, (result - 70) / 30)
+    elif is_bear_t:
+        sig_strength += 0.3 + max(0, (30 - result) / 30)
+
+    strength = (
+        "极强" if sig_strength >= 1.7
+        else "强" if sig_strength >= 1.4
+        else "中" if sig_strength >= 1.1
+        else "弱"
+    )
+
+    # ─── 信号类型 ───
+    if is_bull_t:
+        signal = f"买{strength}"
+    elif is_bear_t:
+        signal = f"卖{strength}"
+    else:
+        signal = "观望"
+
+    # ─── 市场状态 ───
+    if abs(buy_score - sell_score) < 10:
+        status = "中性震荡"
+    elif buy_score > sell_score:
+        if result > ob_threshold:
+            status = "高位企稳"
+        else:
+            status = "温和上涨"
+    else:
+        if result < os_threshold:
+            status = "低位企稳"
+        else:
+            status = "温和下跌"
+
+    # ─── 距离 ───
+    if boll_len > 0:
+        dist_ratio = (close - boll_lower) / boll_len * 100
+    else:
+        dist_ratio = 50
+
+    if dist_ratio < 50 - dist_extreme:
+        dist = "极端超卖"
+    elif dist_ratio < 50 - dist_far:
+        dist = "远离"
+    elif dist_ratio < 50 - dist_mid:
+        dist = "偏离"
+    elif dist_ratio < 50 + dist_mid:
+        dist = "接近"
+    elif dist_ratio < 50 + dist_far:
+        dist = "靠近"
+    elif dist_ratio < 50 + dist_extreme:
+        dist = "远超"
+    else:
+        dist = "极端超买"
+
+    # ─── 强度标签 ───
+    max_score = max(buy_score, sell_score)
+    intensity = (
+        "超强" if max_score >= 90
+        else "强" if max_score >= 80
+        else "中" if max_score >= 65
+        else "弱" if max_score >= 55
+        else "极弱"
+    )
+
+    # ─── 详情 ───
+    ema5 = indicator.EMA5 if hasattr(indicator, 'EMA5') else close
+    ema10 = indicator.EMA10 if hasattr(indicator, 'EMA10') else close
+    ema20 = indicator.EMA20 if hasattr(indicator, 'EMA20') else close
+    bias_val = (ema5 - ema10) / ema10 * 1000 if ema10 != 0 else 0
+
+    bbp_val = (close - boll_lower) / boll_len * 100 if boll_len > 0 else 50
+
+    detail = (
+        f"前量:{percent:.1f} 数量:{int(amplitude):03d} 百分比:{bbp_val:.1f} "
+        f"正:{k_bull:.1f} 负:{k_bear:.1f}"
+    )
+
+    return status, signal, intensity, detail