Design of an Arm Posture Recognition System and Adaptive TENS Therapeutic Device Based on sEMG Signals

This study presents the design of a novel arm posture recognition and adaptive transcutaneous electrical nerve stimulation (TENS) physiotherapeutic device utilizing surface electromyographic (EMG) signals. The system employs high-precision EMG sensors for real-time monitoring of users' arm EMG signals, alongside sophisticated signal processing algorithms to facilitate posture recognition. Unlike conventional physiotherapy methods, this innovative design incorporates an adaptive adjustment feature that dynamically modulates the electrical stimulation intensity and frequency based on the user's myoelectric feedback, thereby optimizing therapeutic efficacy. Furthermore, it integrates lightweight algorithmic deployment of embedded artificial intelligence, enhancing its usability. This system holds significant potential for application in rehabilitation medicine, sports medicine, and geriatric care, with the aim of improving treatment precision and comfort while aiding in the restoration and maintenance of arm functionality.