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Journal of Software Engineering
  Year: 2016 | Volume: 10 | Issue: 4 | Page No.: 347-355
DOI: 10.3923/jse.2016.347.355
Dynamic Modeling of the Human-Computer Interaction for Upper Limb Rehabilitation Robot
Xing Li and Xiaofeng Wang

Abstract:
Background: A lot of machines have been developed for the upper-limb rehabilitation to meet the patient’s needs of upper-limb rehabilitation exercises. As a ctive exercise has been proven to be effective and necessary for neural rehabilitation and motor recovery, it is suggested to be implemented to the rehabilitation machines. To get this goal, the human motion’s desire should have been recognized exactly first. Because the muscle strength of the patient’s upper limb may not be able to supply the gravity of the arm and the rehabilitation machines, some torques comes from the rehabilitation machines will be needed to supply the exercise. Materials and Methods: This study is focused on modeling and identifying the human-computer interaction dynamics, so that the motion’s desire is able to be recognized exactly based on it. Firstly, the human upper limb can be taken as two links with three degrees of freedom (two DOF in shoulder, one in elbow). By combining the dynamics model of human upper limb and robot, the human-computer interaction dynamic model was formed. Results: Meanwhile, the joint angles and torques of human upper limb be measured indirectly by using the position and torque sensors mounted on the joints of the exoskeleton. Conclusion: In this way, a 19 parameter human-computer interaction dynamic model has been established by using the Lagrange method based on the pseudo inertia matrix. The feasibility of the human-computer interaction dynamic model is validated by comparing the math model to the simulation model established by the SolidWorks and the Sim Mechanics.
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How to cite this article:

Xing Li and Xiaofeng Wang, 2016. Dynamic Modeling of the Human-Computer Interaction for Upper Limb Rehabilitation Robot. Journal of Software Engineering, 10: 347-355.

DOI: 10.3923/jse.2016.347.355

URL: https://scialert.net/abstract/?doi=jse.2016.347.355

 
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