Interpretable Shared‐Backbone MobileViT Framework for sEMG‐Based Hand Motion Pattern Recognition and Finger Joint Angle Prediction
Surface electromyography (sEMG) signals are vital bioelectrical indicators for decoding human motion intentions in rehabilitation robotics. However, achieving high‐precision synchronous modeling of hand motion pattern recognition and joint angle prediction remains challenging. This study proposes a shared‐backbone sEMG...