A High-Fidelity Wearable System for Measuring Lower-Limb Kinetics and Kinematics

Abstract

There are many important challenges in gait analysis, which has many applications in healthcare, rehabilitation, therapy, and exercise training. However, gait analysis is typically performed in a gait laboratory, which is inaccessible to the general population and is not available in natural gait environments (e.g., outdoors). In this paper, we discuss the development of a high-fidelity, cost-effective, wireless sensor network to address the challenge of efficient gait monitoring in real-world walking scenarios. The sensor network is designed in a modular way to capture plantar forces and knee angle, angular velocity, and angular acceleration. A force module called a smart insole is designed to measure the plantar forces. The module is comprised of force sensitive resistors (FSRs) and a signal conditioning circuit. Various signal conditioning techniques, including a novel technique called transfrequency, are investigated to provide a linear mapping for FSR measurements and to provide data acquisition fidelity. The motion module includes a low-cost inertial measurement unit (IMU) augmented with a Kalman filter to provide filtered knee kinematics. A qualitative evaluation of the sensor network communication module is achieved by considering the internal communication protocols between the modules and the external wireless transmission protocol used to deliver data to an end-point terminal PC. Experiments are conducted to validate the motion and force modules. Then, the overall, integrated system is compared to gold standard laboratory results, demonstrating a successful application for gait identification. The results show that the sensor network accurately captures important gait parameters and features.