Gait Analysis with a Low Cost Smart Shoe Insole
Emely Villa, Dylan Thai
School of Engineering
Faculty Supervisor: David Quintero
The gait cycle involves complex movements of the hips, pelvis, legs, and upper body, aiming for efficient and coordinated walking or running patterns. Analyzing these patterns can reveal underlying neurological or musculoskeletal issues. To aid in rehabilitation, we developed a wearable shoe insole sensor with embedded force-sensitive resistors (FSRs), providing real-time pressure sensory feedback for assistive healthcare. Our goal is to provide an affordable, comfortable insole with pressure sensors to record real-time data for gait rehabilitation. The wearable insole sensor system comprises several key off-the-shelf components: an Arduino Mega microcontroller, an insole integrated with eight FSRs, a mini breadboard, a 6V power supply, and a computer for data collection. When the user steps on the insole, analog readings are obtained and converted into voltage outputs using MATLAB. After obtaining voltage measurements throughout the walking cycle, we calculated the average force for the toe, midfoot, and heel regions. Using these averages, we detected whether the force exceeded a pressure threshold, indicating heel-strike, mid-stance, or toe-off phases. As well as calculating the ground reactive force and center of pressure. This smart insole system holds promise for gait rehabilitation, providing accessible, real-time feedback for individuals recovering from injuries. In contrast to current methodologies reliant on specialized training and motion capture laboratories, our approach offers a user-friendly and accessible solution that can be easily implemented at home, requiring minimal expertise.