Objective evaluation of hand rom and motion quality based on motion capture and brunnstrom scale

Evaluation of hand performance based on the collected data can be used to objectively and accurately assess the characteristics of hand motion quality for stroke patients. Current hand motion assessment is usually done by clinicians, which is heavily dependent on the therapist's experience and subjective judgment, the quality of motion is not quantifiable and intuitional. This paper proposes an objective evaluation method of the hand motion quality using the optical motion capture system combined with Brunnstrom criteria which is assessment a scale commonly used in clinics. The motion capture system is used to detect the maximum range of motion (ROM) of ten finger joints during the hand motion. A K-Nearest Neighbor algorithm is adapted to classify the hand movement quality levels of Brunnstrom evaluation criteria. Computer recognition of rehabilitation assessment of medical scale is realized, and it can intuitively and accurately reflect the user's hand movement state. Experiments were designed by taking into account the motion characteristics of Brunnstrom assessment, and the ROM of five common hand movements, including common flexion, coextension, thumb flexion, thumb-pinch, and spherical grasp were measured. A comparative study was conducted between the proposed method and the Brunnstrom scale, and the results verified this method's capability in evaluating the human hand motion quality, which has potential for rehabilitation evaluation of the hand motion of stroke patients and to provide the basis for the formulation of rehabilitation training programs.