The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Comparison of Surface and Intramuscular Myoelectric Signal Classification
Abstract
The surface myoelectric signal (MES) has been used as an input to controllers for powered prostheses for many years. As a result of recent technological advances it is reasonable to assume that there will soon be implantable myoelectric sensors which will enable the internal MES to be used as input to these controllers. An internal MES measurement should have less muscular crosstalk allowing for more independent control sites. However, it remains unclear if this benefit outweighs the loss of the more global information contained in the surface MES. This paper compares the classification accuracy of six pattern recognition-based myoelectric controllers which use multi-channel surface MES as inputs to the same controllers which use multi-channel intramuscular MES as inputs. An experiment was designed during which surface and intramuscular MES were collected simultaneously for 10 different classes of isometric contraction. There was no significant difference in classification accuracy as a result of using the intramuscular MES measurement technique when compared to the surface MES measurement technique. Impressive classification accuracy (97%) could be achieved by optimally selecting only three channels of surface MES.
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Citations
Cites
A robust, real-time control scheme for multifunction myoelectric control
Englehart, K., & Hudgins, B. (2003) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2003.813539 · Cited by 1,743
Self-citationGraupe, D., Salahi, J., & Kohn, K. H. (1982) · Journal of Biomedical Engineering · doi:10.1016/0141-5425(82)90021-8 · Cited by 205
Cited by
Huang, H., Zhang, F., Hargrove, L. J., Dou, Z., Rogers, D. R., & Englehart, K. B. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2161671 · Cited by 542
Self-citationA Strategy for Identifying Locomotion Modes Using Surface Electromyography
Huang, H., Kuiken, T. A., & Lipschutz, R. D. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.2003293 · Cited by 512
Myoelectric forearm prostheses: State of the art from a user-centered perspective
Peerdeman, B., Boere, D., Witteveen, H., Huis in `tVeld, R., Hermens, H., Stramigioli, S., Rietman, H., Veltink, P., & Misra, S. (2011) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2010.08.0161 · Cited by 469
Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses
Li, G., Schultz, A. E., & Kuiken, T. A. (2010) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2039619 · Cited by 443
Control of Hand Prostheses Using Peripheral Information
Micera, S., Carpaneto, J., & Raspopovic, S. (2010) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2010.2085429 · Cited by 403
Metadata
- Authors
- Hargrove, L. J., Englehart, K., & Hudgins, B.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2007-05
- Volume
- 54
- Issue
- 5
- Pages
- 847-853
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2133530044
- Cited by
- 518
- References
- 2
- FWCI
- 13.94
- Type
- journal article
- Language
- en
- Open access
- closed
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