Real-time tracking of flexion angle by using wearable accelerometer sensors

Abstract

This paper presents a new algorithm for real time tracking the flexion angle from wearable accelerometer sensor data using wireless body sensor network (BSN). The proposed algorithm uses dynamic filter for tracking the flexion angles of which the human body dynamics is described by its system model. In this work, the Extended Kalman Filtering is used to demonstrate the superiority of this approach. Results from a thigh tracking experiment show that the flexion angle estimated closely followed that of the video data.