StrikeWatch deploys four compact time-series models on two low-power FPGAs for on-device heel-forefoot strike classification from wrist IMU data, with the best 6-bit 1D-SepCNN reaching 0.847 F1 at 0.35 µJ and 0.14 ms per inference.
Integer-only quantized Transformers for embedded FPGA-based time-series forecasting in AIoT
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StrikeWatch: Wrist-worn Gait Recognition with Compact Time-series Models on Low-power FPGAs
StrikeWatch deploys four compact time-series models on two low-power FPGAs for on-device heel-forefoot strike classification from wrist IMU data, with the best 6-bit 1D-SepCNN reaching 0.847 F1 at 0.35 µJ and 0.14 ms per inference.