FRL Wrist Control: Wrist Movement Decoding from Surface Electromyography

This dataset comprises wrist-based surface electromyography (sEMG) recordings from 100 participants performing continuous cursor control via wrist flexion and extension movements. Synchronized motion capture provides ground-truth wrist angles, enabling evaluation of sEMG-based decoding of motor intent. The study demonstrates the feasibility of gesture-free, non-invasive neuromotor interfaces for human-computer interaction, with applications to AR/VR navigation and assistive control systems. Note: Raw data contains duplicate timestamps and irregular sampling in many sessions; post-processing includes duplicate removal and resampling to regular 2000 Hz intervals.