[Follow control of upper limb rehabilitation training based on Kinect and NAO robot].

Xiaoguang Liu, Simin Li, Tie Liang, Jun Li, Cunguang Lou, Hongrui Wang, Xiuling Liu
Author Information
  1. Xiaoguang Liu: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  2. Simin Li: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  3. Tie Liang: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  4. Jun Li: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  5. Cunguang Lou: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  6. Hongrui Wang: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
  7. Xiuling Liu: College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.

Abstract

Gesture imitation is a common rehabilitation strategy in limb rehabilitation training. In traditional rehabilitation training, patients need to complete training actions under the guidance of rehabilitation physicians. However, due to the limited resources of the hospital, it cannot meet the training and guidance needs of all patients. In this paper, we proposed a following control method based on Kinect and NAO robot for the gesture imitation task in rehabilitation training. The method realized the joint angles mapping from Kinect coordination to NAO robot coordination through inverse kinematics algorithm. Aiming at the deflection angle estimation problem of the elbow joint, a virtual space plane was constructed and realized the accurate estimation of deflection angle. Finally, a comparative experiment for deflection angle of the elbow joint angle was conducted. The experimental results showed that the root mean square error of the angle estimation value of this method in right elbow transverse deflection and vertical deflection directions was 2.734° and 2.159°, respectively. It demonstrates that the method can follow the human movement in real time and stably using the NAO robot to show the rehabilitation training program for patients.

Keywords

References

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  5. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Feb 25;37(1):129-135 [PMID: 32096386]
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MeSH Term

Humans
Biomechanical Phenomena
Elbow Joint
Physical Therapy Modalities
Robotics
Upper Extremity

Word Cloud

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