Smart Insoles for Gait Analysis Based on Meshless Conductive Rubber Sensors and Neural Networks

Abstract

Abstract In recent years, advances in wearable medical devices have been driven by the development of flexible sensors and wireless IoT technologies, with research and applications in this field rapidly increasing. Plantar pressure analysis is a gait method that can be used to analyze foot pressure during human movement to identify potential health problems, but most of the devices based on this method are currently single-functional, poorly portable, and expensive. This work proposes a smart insole using meshless conductive rubber sensors, as well as a multi-channel data acquisition and transmission system based on these sensors, deep learning networks, and Bluetooth technology. The smart insole sensing unit and circuit board were made of flexible materials and powered by rechargeable lithium batteries. The system can be used to collect plantar pressure data from the sensors in real time, analyze the pressure in different regions of the foot through a neural network, and infer the gait cycle and abnormal gait of the user. The effective communication range can be up to 70 meters under barrier-free conditions. This smart insole has a bright future thanks to the pressure detection range, fast response time, and good durability.