Lightweight Shoulder Physiotherapy Exercise Recognition via Efficient Channel Attention and Depthwise Separable Residual Networks on Wrist-Worn IMU
ECA-ResNet1D-Lite is presented, a lightweight one-dimensional depthwise separable residual network augmented with efficient channel attention (ECA), trained and evaluated on the SPARS9x dataset comprising six shoulder exercises recorded from 20 subjects using a commercial wrist-worn smartwatch at 50 Hz, establishing th...