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Non-invasive decoding of the motoneurons: A guided source separation method based on convolution kernel compensation with clustered initial points

Author
Mohebian, M.; Marateb, H.R.; Karimimehr, S.; Mañanas, M.A.; Kranjec, J.; Holobar, A.
Type of activity
Journal article
Journal
Frontiers in computational neuroscience
Date of publication
2019-04-01
Volume
13
First page
14-1
Last page
14-14
DOI
10.3389/fncom.2019.00014
Repository
http://hdl.handle.net/2117/133614 Open in new window
URL
https://www.frontiersin.org/articles/10.3389/fncom.2019.00014/full Open in new window
Abstract
Despite the progress in understanding of neural codes, the studies of the cortico-muscular coupling still largely rely on interferential electromyographic (EMG) signal or its rectification for the assessment of motor neuron pool behavior. This assessment is non-trivial and should be used with precaution. Direct analysis of neural codes by decomposing the EMG, also known as neural decoding, is an alternative to EMG amplitude estimation. In this study, we propose a fully-deterministic hybrid surfa...
Citation
Mohebian, M. [et al.]. Non-invasive decoding of the motoneurons: A guided source separation method based on convolution kernel compensation with clustered initial points. "Frontiers in computational neuroscience", 1 Abril 2019, vol. 13, p. 14-1-14-14.
Group of research
BIOART - Biosignal Analysis for Rehabilitation and Therapy
CREB - Biomedical Engineering Research Centre

Participants

  • Mohebian, Mohammad Reza  (author)
  • Marateb, Hamid Reza  (author)
  • Karimimehr, Saeed  (author)
  • Mañanas Villanueva, Miguel Angel  (author)
  • Kranjec, Jernej  (author)
  • Holobar, Ales  (author)

Attachments