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A 3-DOF hemi-constrained wrist motion/force detection device for deploying simultaneous myoelectric control
- Source :
- Medical & Biological Engineering & Computing. 56:1669-1681
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
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).
- Subjects :
- Adult
030506 rehabilitation
Computer science
0206 medical engineering
Biomedical Engineering
02 engineering and technology
Electromyography
Wrist
Cursor (databases)
Motion (physics)
Support vector regression model
Three degrees of freedom
Motion
03 medical and health sciences
Image Processing, Computer-Assisted
medicine
Humans
Computer vision
Training set
medicine.diagnostic_test
business.industry
Movement (music)
020601 biomedical engineering
Biomechanical Phenomena
Computer Science Applications
medicine.anatomical_structure
Regression Analysis
Artificial intelligence
0305 other medical science
business
Subjects
Details
- ISSN :
- 17410444 and 01400118
- Volume :
- 56
- Database :
- OpenAIRE
- Journal :
- Medical & Biological Engineering & Computing
- Accession number :
- edsair.doi.dedup.....8fb26dd7c93a67985022f8f29727a667
- Full Text :
- https://doi.org/10.1007/s11517-018-1807-2