Development of a multimodal participation assessment system for upper limb rehabilitation

In conventional and robotic rehabilitation, the patient's active participation in exercises is crucial for obtaining maximum functional outputs received from therapy. In rehabilitation exercises performed with robotic devices, the difficulty levels of therapy tasks and the device assistance are adjusted based on the patient's therapy performance to improve active participation. However, the existing therapy performance evaluation methods are based on either some specific device designs or certain therapy tasks, which reduces their widespread use. Hence, there is a requirement to develop an independent performance measurement system. In this thesis, a patient performance evaluation method is proposed based on a multimodal sensor fusion formed by the trajectory tracking error signal and the patient's physiological responses (heart rate and skin conductance) during the upper extremity rehabilitation. The novelty of the system is assessing the patient's performance independently from any device designs or therapy tasks. The developed system also evaluates the patient's tiredness and slacking, which are substantial factors affecting the therapy performance. The designed system is tested with healthy subjects and clinically with frozen shoulder syndrome patients. The experimental results showed that the proposed system evaluates subjects' participation successfully and adjusts the therapy tasks and difficulty levels of tasks according to subjects' performance and tiredness.