scholarly journals Summarization on 73 Cases of Apoplectic Aphasia Patients after Stroke Who Treated by Electric Acupuncture and Rehabilitation Training

2017 ◽  
Vol 06 (05) ◽  
pp. 181-184
Author(s):  
婷婷 周
Keyword(s):  
Rehabilitation Training ◽  
Electric Acupuncture

Application Study on Finger Joint Motion in Rehabilitation Training

2014 ◽  
Vol 644-650 ◽  
pp. 879-883
Author(s):  
Jing Jing Yu
Keyword(s):  
Control Method ◽  
Finger Joint ◽  
Continuous Passive Motion ◽  
Joint Motion ◽  
Joint Movement ◽  
Rehabilitation Training ◽  
Angle Data ◽  
Finger Flexion ◽  
And Control ◽  
Flexion And Extension

In various forms of movement of finger rehabilitation training, Continuous Passive Motion (CPM) of single degree of freedom (1 DOF) has outstanding application value. Taking classic flexion and extension movement for instance, this study collected the joint angle data of finger flexion and extension motion by experiments and confirmed that the joint motion of finger are not independent of each other but there is certain rule. This paper studies the finger joint movement rule from qualitative and quantitative aspects, and the conclusion can guide the design of the mechanism and control method of finger rehabilitation training robot.

scholarly journals Correction to: A method of VR‑EEG scene cognitive rehabilitation training

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Wenjun Tan ◽  
Yang Xu ◽  
Pan Liu ◽  
Chunyan Liu ◽  
Yujin Li ◽  
...  
Keyword(s):  
Cognitive Rehabilitation ◽  
Rehabilitation Training

Kinematic dexterity analysis of human-robot interaction of an upper limb rehabilitation robot

2020 ◽  
pp. 1-17
Author(s):  
Qing Sun ◽  
Shuai Guo ◽  
Leigang Zhang
Keyword(s):  
Upper Limb ◽  
Constraint Equation ◽  
Human Robot Interaction ◽  
Rehabilitation Robot ◽  
Connecting Rod ◽  
Robot Interaction ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Limb Rehabilitation ◽  
Training Trajectory

BACKGROUND: The definition of rehabilitation training trajectory is of great significance during rehabilitation training, and the dexterity of human-robot interaction motion provides a basis for selecting the trajectory of interaction motion. OBJECTIVE: Aimed at the kinematic dexterity of human-robot interaction, a velocity manipulability ellipsoid intersection volume (VMEIV) index is proposed for analysis, and the dexterity distribution cloud map is obtained with the human-robot cooperation space. METHOD: Firstly, the motion constraint equation of human-robot interaction is established, and the Jacobian matrix is obtained based on the speed of connecting rod. Then, the Monte Carlo method and the cell body segmentation method are used to obtain the collaborative space of human-robot interaction, and the VMEIV of human-robot interaction is solved in the cooperation space. Finally, taking the upper limb rehabilitation robot as the research object, the dexterity analysis of human-robot interaction is carried out by using the index of the approximate volume of the VMEIV. RESULTS: The results of the simulation and experiment have a certain consistency, which indicates that the VMEIV index is effective as an index of human-robot interaction kinematic dexterity. CONCLUSIONS: The VMEIV index can measure the kinematic dexterity of human-robot interaction, and provide a reference for the training trajectory selection of rehabilitation robot.

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