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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.