A novel method for estimating knee angle using two leg-mounted gyroscopes for continuous monitoring with mobile health devices

Abstract

Tele-rehabilitation of patients with gait abnormalities could benefit from continuous monitoring of knee joint angle in the home and community. Continuous monitoring with mobile devices can be restricted by the number of body-worn sensors, signal bandwidth, and the complexity of operating algorithms. Therefore, this paper proposes a novel algorithm for estimating knee joint angle using lower limb angular velocity, obtained with only two leg-mounted gyroscopes. This gyroscope only (GO) algorithm calculates knee angle by integrating gyroscope-derived knee angular velocity signal, and thus avoids reliance on noisy accelerometer data. To eliminate drift in gyroscope data, a zero-angle update derived from a characteristic point in the knee angular velocity is applied to every stride. The concurrent validity and construct convergent validity of the GO algorithm was determined with two existing IMU-based algorithms, complementary and Kalman filters, and an optical motion capture system, respectively. Bland-Altman analysis indicated a high-level of agreement between the GO algorithm and other measures of knee angle.