The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal
Abstract
A novel signal processing algorithm for the surface electromyogram (EMG) is proposed to extract simultaneous and proportional control information for multiple DOFs. The algorithm is based on a generative model for the surface EMG. The model assumes that synergistic muscles share spinal neural drives, which correspond to the intended activations of different DOFs of natural movements and are embedded within the surface EMG. A DOF-wise nonnegative matrix factorization (NMF) is developed to estimate neural control information from the multichannel surface EMG. It is shown, both by simulation and experimental studies, that the proposed algorithm is able to extract the multidimensional control information simultaneously. A direct application of the proposed method would be providing simultaneous and proportional control of multifunction myoelectric prostheses.
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Cites
The Integrative Action of the Nervous System.
Sherrington, C. (1907) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-190734120-00021 · Cited by 4,136
Models of recruitment and rate coding organization in motor-unit pools.
Fuglevand, A. J., Winter, D. A., & Patla, A. E. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.70.6.2470 · Cited by 988 · cited 1×
“plemented using the exponential threshold method described in [35].”
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Cited by
Farina, D., Jiang, N., Rehbaum, H., Holobar, A., Graimann, B., Dietl, H., & Aszmann, O. C. (2014) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2014.2305111 · Cited by 992
Self-citationProgress and prospects of the human–robot collaboration
Ajoudani, A., Zanchettin, A. M., Ivaldi, S., Albu-Schäffer, A., Kosuge, K., & Khatib, O. (2018) · Autonomous Robots · doi:10.1007/s10514-017-9677-2 · Cited by 832
Control of upper limb prostheses: terminology and proportional myoelectric control-a review
Fougner, A., Stavdahl, Ø., Kyberd, P. J., Losier, Y. G., & Parker, P. A. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2196711 · Cited by 495
Self-citationMyoelectric 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
Myoelectric Control of Artificial Limbs—Is There a Need to Change Focus? [In the Spotlight]
Jiang, N., Dosen, S., Muller, K.-R., & Farina, D. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2203480 · Cited by 434
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Metadata
- Authors
- Jiang, N., Englehart, K. B., & Parker, P. A.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2009-04
- Volume
- 56
- Issue
- 4
- Pages
- 1070-1080
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2097292795
- Cited by
- 450
- References
- 2
- FWCI
- 6.40
- Type
- journal article
- Language
- en
- Open access
- closed
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