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Reducing Drifts in the Inertial Measurements of Wrist and Elbow Positions

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2 Author(s)
Huiyu Zhou ; School of Engineering and Design, Brunel University, Uxbridge, U.K. ; Huosheng Hu

In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3??. This indicates that the proposed approach has performed well in terms of accuracy and reliability.

Published in:

IEEE Transactions on Instrumentation and Measurement  (Volume:59 ,  Issue: 3 )