SHOULDER AND ELBOW JOINT ANGLE ESTIMATION FOR UPPER LIMB REHABILITATION TASKS USING LOW-COST INERTIAL AND OPTICAL SENSORS

Abstract

This paper proposes a new method to improve accuracy and real-time performance of inertial joint angle estimation for upper limb rehabilitation applications by modeling body acceleration and adding low-cost markerless optical position sensors. A method based on a combination of the 3D rigid body kinematic equations and Denavit-Hartenberg (DH) convention is used to model body acceleration. Using this model, body acceleration measurements of the accelerometer are utilized to increase linearization order and compensate for body acceleration perturbations. To correct for the sensor-to-segment misalignment of the inertial sensors, position measurements of a low-cost markerless position sensor are used. Joint angles are estimated by Extended Kalman Filter (EKF) and compared with Unscented Kalman Filter (UKF) in terms of performance. Simulations are performed to quantify the existing error and potential improvements achievable by the proposed method. Experiments on a human test subject performing an upper limb rehabilitation task is used to validate the simulation results in realistic conditions.