Self-powered high-resolution smart insole system for plantar pressure mapping

Abstract

Accurate plantar pressure mapping systems with low dependence on the external power supply are highly desired for preventative healthcare and medical diagnosis. Herein, we propose a self-powered smart insole system that can perform both static and dynamic plantar pressure mapping with high accuracy. The smart insole system integrates an insole-shaped sensing unit, a multi-channel data acquisition board, and a data storage module. The smart insole consists of a 44-pixel sensor array based on triboelectric nanogenerators (TENGs) to transduce pressure to the electrical signal. By optimizing the sensor architecture and the system's robustness, the smart insole achieves high sensitivity, good error-tolerance capability, excellent durability, and short response–recovery time. Various gait and mobility patterns, such as standing, introversion/extraversion, throwing, and surpassing obstacles, can be distinguished by analyzing the acquired electrical signals. This work paves the way for self-powered wearable devices for gait monitoring, which might enable a new modality of medical diagnosis.