Real Time On Sensor Gait Phase Detection with 0.5KB Deep Learning Model

05/02/2022

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by   Yi-An Chen, et al.

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Gait phase detection with convolution neural network provides accurate classification but demands high computational cost, which inhibits real time low power on-sensor processing. This paper presents a segmentation based gait phase detection with a width and depth downscaled U-Net like model that only needs 0.5KB model size and 67K operations per second with 95.9 easily fitted into resource limited on sensor microcontroller.