A Novel Low-Pressure Robotic Glove Based on CT-Optimized Finger Joint Kinematic Model for Long-Term Rehabilitation of Stroke Patients

Abstract

Wearing robotic gloves has become increas-1 ingly crucial for hand rehabilitation in stroke patients. 2 However, traditional robotic gloves can exert additional 3 pressure on the hand, such as prolonged use leading to 4 poor blood circulation and muscle stiffness. To address 5 these concerns, this work analyzes the finger kinematic 6 model based on computerized tomography (CT) images of 7 human hands, and designs a low-pressure robotic glove 8 that conforms to finger kinematic characteristics. Firstly, 9 physiological data on finger joint flexion and extension 10 were collected through CT scans. The equivalent rotation 11 centers of finger joints were obtained using the SURF and 12 RANSAC algorithms. Furthermore, the trajectory of finger 13 joint end and the correlation equation of finger joint motion 14 were fitted, and a comprehensive finger kinematic model 15 was established. Based on this finger kinematic model, 16 a novel under-actuated exoskeleton mechanism was de-17 signed using a human-machine integration approach. The 18 novel robotic glove fully aligns with the equivalent rota-19 tion centers and natural motion trajectories of the fingers, 20 exerting minimal and evenly distributed dynamic pressure 21 on the fingers, with a theoretical static pressure value 22 of zero. Experiments involving gripping everyday objects 23 demonstrated that the novel robotic glove significantly re-24 duces the overall pressure on the fingers during grasping 25 compared to the pneumatic glove and the traditional ex-26 oskeleton robotic glove. It is suitable for long-term use by 27 stroke patients for rehabilitation training.