J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (1): 45-54.doi: 10.1007/s12204-021-2365-6

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  • 收稿日期:2021-01-30 出版日期:2022-01-28 发布日期:2022-01-14
  • 通讯作者: CHEN Guodong (陈国栋),guodongxyz@163.com;WANG Zheng (王正),wangzheng6th@163.com

Safety Protection Method of Rehabilitation Robot Based on fNIRS and RGB-D Information Fusion

LI Dong1 (李栋), FAN Yulin1 (樊钰琳), L v Na3 (吕娜), CHEN Guodong1 (陈国栋), WANG Zheng2 (王正), CHI Wenzheng1 (迟文政)   

  1. (1. School of Mechanical and Electrical Engineering; Jiangsu Provincial Key Laboratory of Advanced Robotics; Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215123, Jiangsu, China; 2. Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China; 3. Department of Instrument Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
  • Received:2021-01-30 Online:2022-01-28 Published:2022-01-14

Abstract: In order to improve the safety protection performance of the rehabilitation robot, an active safety protection method is proposed in the rehabilitation scene. The oxyhemoglobin concentration information and RGB-D information are combined in this method, which aims to realize the comprehensive monitoring of the invasion target, the patient’s brain function movement state, and the joint angle in the rehabilitation scene. The main focus is to study the fusion method of the oxyhemoglobin concentration information and RGB-D information in the rehabilitation scene. Frequency analysis of brain functional connectivity coefficient was used to distinguish the basic motion states. The human skeleton recognition algorithm was used to realize the angle monitoring of the upper limb joint combined with the depth information. Compared with speed and separation monitoring, the protection method of multi-information fusion is safer and more comprehensive for stroke patients. By building the active safety protection platform of the upper limb rehabilitation robot, the performance of the system in different safety states is tested, and the safety protection performance of the method in the upper limb rehabilitation scene is verified.

Key words: upper limb rehabilitation robot, safety protection, functional near-infrared spectroscopy (fNIRS), multi-information fusion