End-effector type robots have been popularly applied to robot-aided therapy for rehabilitation purpose. However, those robots have a key drawback for the purpose: lack of the user's posture (joint angle) information. This paper proposes a novel end-effector rehabilitation robot system that contains a contactless motion sensor to monitor upper- extremity posture during robot-aided reaching exercise. The sensor allows the posture estimation without complicated procedures but has an inaccuracy problem such as occlusion and an unreliable segment length. Therefore, we developed a posture monitoring method, which is an analytical method without training procedure, based on the combined use of the information obtained from the sensor and the robot. Eight healthy subjects participated in the experiment with planar reaching exercise for validation. The results of joint angle estimation, high correlation coefficient (about 0.95) and small errors (about 3.55 degree), show that the proposed system can provide affordable upper-extremity posture estimation.

In rehabilitation, the Fugl–Meyer assessment (FMA) is a typical clinical instrument to assess upper-extremity motor function of stroke patients, but it cannot measure fine changes of motor function (both in recovery and deterioration) due to its limited sensitivity. This paper introduces a sensor-based automated FMA system that addresses this limitation with a continuous rating algorithm. The system consists of a depth sensor (Kinect V2) and an algorithm to rate the continuous FM scale based on fuzzy inference. Using a binary logic based classification method developed from a linguistic scoring guideline of FMA, we designed fuzzy input/output variables, fuzzy rules, membership functions, and a defuzzification method for several representative FMA tests. A pilot trial with nine stroke patients was performed to test the feasibility of the proposed approach. The continuous FM scale from the proposed algorithm exhibited a high correlation with the clinician rated scores and the results showed the possibility of more sensitive upper-extremity motor function assessment.