title: Generation of a Movement Scheme for Positive Training.
abstract: Rehabilitation robots have been demonstrated to be an efficient tool in the field of rehabilitation training. Meanwhile, there are varieties of tasks designed for motion training. These tasks need to be transmitted to motion data for rehabilitation robots. In this paper, we designed a drinking task and captured the motion data as the ground truth, through sensors of an exoskeleton device named Neo-Arm. To verify the effectiveness of Neo-Arm, we used a Vicon system to capture the same motion task without Neo-Arm for comparison. Eight subjects participated in the experiment. The motion data of the drinking task, including the range of motion (ROM) and the velocity of each joint, are obtained. The result shows that the Neo-Arm can achieve the suitable precision and be fit for other kinds of upper limb motion tasks.
authors.affiliation: Institute of Forming Technology and Equipment, Shanghai Jiao Tong University Shanghai, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Liu
authors.affiliation: Institute of Forming Technology and Equipment, Shanghai Jiao Tong UniversityShanghai, China; School of Biomedical Engineering, Shanghai Jiao Tong UniversityShanghai, China.
authors.forename: Le
authors.initials: L
authors.lastname: Xie
authors.affiliation: School of Biomedical Engineering, Shanghai Jiao Tong University Shanghai, China.
authors.forename: Yun-Yong
authors.initials: YY
authors.lastname: Shi
authors.affiliation: HuaDong Hospital Affiliated with Fudan University Shanghai, China.
authors.forename: Bing-Chen
authors.initials: BC
authors.lastname: An
keywords: rehabilitation; robot; training; trajectory; upper limb