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Extracting simultaneous and proportional neural control information for multiple-DOF prostheses from the surface electromyographic signal.

Authors
  • Jiang, Ning
  • Englehart, Kevin B
  • Parker, Philip A
Type
Published Article
Journal
IEEE Transactions on Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers
Publication Date
Apr 01, 2009
Volume
56
Issue
4
Pages
1070–1080
Identifiers
DOI: 10.1109/TBME.2008.2007967
PMID: 19272889
Source
Medline
License
Unknown

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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