NeuroVisio SyncPatch: A Skin-Conformal Multimodal EMG-Motion Sensing Platform for Quantitative Neuromuscular...

Effective musculoskeletal rehabilitation requires simultaneous assessment of muscle activation and movement kinematics, yet no current system enables this at home. Laboratory motion capture systems provide accurate kinematics but require controlled environments, while portable inertial sensors enable home use at the cost of drift and incomplete joint angle resolution. Critically, neither approach provides direct physiological insight into the muscle activation driving functional movement. Here, we present NeuroVisio SyncPatch, a wearable multimodal platform that unifies conformal surface electromyography (EMG) with vision-based motion tracking within a single sports-tape interface. The device integrates stretchable, breathable, electrically conductive adhesive (ECA) electrodes that enable stable EMG acquisition, along with printed optical markers supporting accurate 3-degree-of-freedom (DOF) knee angle estimation utilizing a single RGB-D camera per leg via a convolutional neural network (CNN)-based vision pipeline. By integrating high-fidelity EMG signals (SNR > 13 dB) with joint kinematics, the system delivered real-time kinematic feedback during movement together with EMG-derived neuromuscular feedback after each trial. Multimodal feedback training showed improved knee alignment and intermuscular coordination in participants with dynamic knee valgus (DKV), demonstrating closed-loop modulation of maladaptive motor patterns. NeuroVisio SyncPatch establishes a scalable, mechanically robust, and physiologically comprehensive framework for home-deployable musculoskeletal rehabilitation.