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Medical & Biological Engineering & Computing

, Volume 56, Issue 9, pp 1669–1681 | Cite as

A 3-DOF hemi-constrained wrist motion/force detection device for deploying simultaneous myoelectric control

  • Wei Yang
  • Dapeng YangEmail author
  • Yu Liu
  • Hong Liu
Original Article

Abstract

For describing the state of the wrist, either the force or movement of wrist can be measured as the training target in the simultaneous electromyography control. However, the relationship between the force and movement is so complex that only the force or movement is not precise enough to describe its actual situations. In this paper, we propose a novel platform that can acquire three degrees of freedom (DOF) wrist motion/force synchronously with multi-channel electromyography signals in a hemi-constraint way. The self-made wrist force-movement mapping device establishes a stable relationship between the wrist movement and force. Meanwhile, the elicited wrist movement can be directly fed back to the subjects via laser cursor. The information of the cursor can directly reflect the 3-DOF movement of the wrist without any decoupling algorithms. Through this platform, the support vector regression model learned from the training data can well predict the arbitrary combinations of 3-DOF wrist movements. The cross-validation result indicates that the regression accuracy of free 3-DOF movements can reach a similar performance to that of 2-DOF regular movements (in terms of R2, regular movement vs. free movement, p > 0.1).

Graphical abstract

The hemi-constrained platform used for detecting 3-DOF wrist movements.

Keywords

Wrist motion Simultaneous control Surface electromyography Regression 

Notes

Funding information

This work is partially supported by the National Natural Science Foundation of China (Nos. 51675123, 61603112), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No.51521003), and the Self-Planned Task of State Key Laboratory of Robotics and System (No. SKLRS201603B).

Supplementary material

11517_2018_1807_MOESM1_ESM.mp4 (14 mb)
ESM 1 (MP4 14,370 kb)

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Copyright information

© International Federation for Medical and Biological Engineering 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Robotics and System (SKLRS)Harbin Institute of TechnologyHarbinChina
  2. 2.Artificial Intelligence Research (HAI)Harbin Institute of TechnologyHarbinChina

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