title: A cable-driven wrist robotic rehabilitator using a novel torque-field controller for human motion training.
abstract: Rehabilitation technologies have great potentials in assisted motion training for stroke patients. Considering that wrist motion plays an important role in arm dexterous manipulation of activities of daily living, this paper focuses on developing a cable-driven wrist robotic rehabilitator (CDWRR) for motion training or assistance to subjects with motor disabilities. The CDWRR utilizes the wrist skeletal joints and arm segments as the supporting structure and takes advantage of cable-driven parallel design to build the system, which brings the properties of flexibility, low-cost, and low-weight. The controller of the CDWRR is designed typically based on a virtual torque-field, which is to plan "assist-as-needed" torques for the spherical motion of wrist responding to the orientation deviation in wrist motion training. The torque-field controller can be customized to different levels of rehabilitation training requirements by tuning the field parameters. Additionally, a rapidly convergent parameter self-identification algorithm is developed to obtain the uncertain parameters automatically for the floating wearable structure of the CDWRR. Finally, experiments on a healthy subject are carried out to demonstrate the performance of the controller and the feasibility of the CDWRR on wrist motion training or assistance.
authors.affiliation: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
authors.forename: Weihai
authors.initials: W
authors.lastname: Chen
authors.affiliation: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Cui
authors.affiliation: School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
authors.forename: Jianbin
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D004867:Equipment Design; D005240:Feasibility Studies; D005542:Forearm / Q000502:physiology; D006801:Humans; D008962:Models, Theoretical; D009038:Motion; D009043:Motor Activity / Q000502:physiology; D026201:Musculoskeletal Manipulations / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods; D012371:Robotics / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D019415:Torque; D035501:Uncertainty; D014953:Wrist / Q000502:physiology