A study on estimating the knee joint angle during walking using the motion sensors (Focusing on the effect of centrifugal acceleration and tangential acceleration)

Abstract

This paper describes the use of nine-axis motion sensors to evaluate knee joint angle estimation accuracy during walking. The nine-axis motion sensor comprises a three-axis gyro sensor, a three-axis acceleration sensor and a three-axis geomagnetic sensor. It can estimate joint angles during exercise by correcting the drift of the three-axis gyro sensor using information obtained from the other two sensors. Human movement results from the rotational motion of the respective joints, so that the proportion of the centrifugal acceleration and the tangential acceleration in the output of the acceleration sensor increases during exercise. Processing the centrifugal acceleration and tangential acceleration appropriately and ascertaining the degree of estimation error are important for improving the joint angle estimation accuracy. For this study, the authors produced a sensor fusion algorithm using an extended Kalman filter to correct the acceleration sensor output. The sensor fusion algorithm uses information obtained from the nine-axis motion sensors to estimate the knee joint angle by correcting the centrifugal acceleration and tangential acceleration. During the experiment, the 3D motion analysis system and two nine-axis motion sensors measured walking exercise. The knee joint angle was estimated using an extended Kalman filter with information obtained from the nine-axis motion sensors. We evaluated the system accuracy for knee joint angle estimation by comparing the nine-axis motion sensor results and the 3D motion analysis system results. This analytical method is anticipated for use in estimating motion in sports and healthcare applications.

Keywords

• motion sensor
• sensor fusion
• kalman filter
• joint angle
• walking