A wireless, self-powered smart insole for gait monitoring and recognition via nonlinear synergistic pressure sensing
Qi Wang, Hui Guan, Chen Wang, Peiming Lei, Hongwei Sheng, Huasheng Bi, Jinkun Hu, Chenhui Guo, Yichuan Mao, Jiao Yuan, Mingjiao Shao, Zhiwen Jin, Jinghua Li, Wei Lan
Abstract
Wearable insole-based pressure sensor systems have gained attention for continuous gait monitoring, showing potential for preventing, diagnosing, and treating conditions such as lumbar degenerative disease and diabetic foot ulcers. However, challenges such as nonlinear response, low stability, and energy limitations have hindered widespread adoption. Here, we report a fully integrated, self-powered, wireless smart insole designed for plantar pressure monitoring and real-time visualization and analysis of gait. The pressure sensor uses a nonlinear synergistic strategy, achieving remarkable linearity ( R 2 > 0.999 over 0 to 225 kilopascals) and high durability (>180,000 compression cycles). Powered by flexible solar cells, the insole features 22 pressure sensors, enabling spatially resolved pressure mapping and real-time visualization on a smartphone interface. Integration of a support vector machine model further enables accurate recognition of eight motion states, including static (e.g., sitting and standing) and dynamic (e.g., walking, running, and squatting) activities. The smart insole provides a practical solution for improving clinical assessments, personalized treatments, and biomechanics research.