Self-Powered Multisensor with Electromagnetic and Triboelectric Energy Harvesting for Wireless Monitoring in Every Knee Joint Motion

Artificial Intelligence of Things (AIoT) enables convenient human health monitoring but consumes massive data and energy. Traditional power supplies and single-sensor setups struggle to reconcile this wireless convenience and multimodal data transmission. A hybrid knee-bending energy harvester is designed, integrating two frequency-up electromagnetic generators (EMGs) and two flexible contact-separate triboelectric nanogenerators (TENGs). The maximum EMG output power is 1.09 W at a frequency of 1.5 Hz and an angle of 180°. A two-stage capacitor scheme is adopted for the cointegration of power generation and sensing. One optimized capacitor stores energy and can wake the wireless system via a single undervoltage lockout (UVLO) discharge. The other capacitor regards linearly charging voltage as angle sensing. The TENG voltage reflects flexible pressure, while motion frequency is derived from the reciprocal of wireless data reception intervals. A custom web-based Bluetooth host computer displays motion data in real time. This system supports long-distance remote monitoring of knee-bending states, facilitating wireless knee health tracking and clinical rehabilitation between patients and clinicians.