Development of a Wearable Sensor System for Measuring Body Joint Flexion

This paper presents a novel approach for measuring and monitoring human body joint angles using wearable sensors. This type of monitoring is beneficial for therapists and physicians as it allows them to assess patients' activities remotely. In our approach multiple flex-sensors are mounted on supportive cloth to measure the flexion of a joint. The changes in the resistivity of the flex-sensors are measured using an electronic board. We utilize an Extended Kalman Filter (EKF) to predict the joint angle based on the dynamic model of the joint movement and the measurements obtained from the flex-sensors. Due to variations in the measured angle by each sensor, the outputs are fussed to reduce the error and estimate the best value for the actual body joint angle. We evaluated the effectiveness and performance of our approach for measuring knee joint angle by comparing with the measured angles using goniometer. The result shows that the average of error is 6.92Ë with correlation of 0.98.

[1]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[2]  J. L. Roux An Introduction to the Kalman Filter , 2003 .

[3]  P H Veltink,et al.  Ambulatory measurement of arm orientation. , 2007, Journal of biomechanics.

[4]  Shu-Li Sun,et al.  Multi-sensor optimal information fusion Kalman filter , 2004, Autom..

[5]  Yaakov Bar-Shalom,et al.  The Effect of the Common Process Noise on the Two-Sensor Fused-Track Covariance , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Parag A. Pathak,et al.  Massachusetts Institute of Technology , 1964, Nature.

[7]  Y. Bar-Shalom Tracking and data association , 1988 .

[8]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[9]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[10]  H Harry Asada,et al.  Wearable Conductive Fiber Sensors for Multi-Axis Human Joint Angle Measurements , 2005, Journal of NeuroEngineering and Rehabilitation.

[11]  R. Wootton,et al.  Can the Internet be used as a medium to evaluate knee angle? , 2003, Manual therapy.

[12]  B. Steele,et al.  Bodies in motion: monitoring daily activity and exercise with motion sensors in people with chronic pulmonary disease. , 2003, Journal of rehabilitation research and development.

[13]  P. Dario,et al.  Evaluation of an instrumented glove for hand-movement acquisition. , 2003, Journal of rehabilitation research and development.

[14]  Junbin Gao,et al.  Some remarks on Kalman filters for the multisensor fusion , 2002, Inf. Fusion.