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Online Intramuscular EMG Decomposition with Varying Number of Active Motor Units

Abstract : This paper deals with the online decomposition of intramuscular electromyographic (iEMG) signals. A Markov model is proposed, which takes into account a varying number of firing motor neurons. A Bayes filter detects online the firing motor units by using a dictionary of approximated motor unit action potentials waveforms, and estimates precisely the action potential shapes and the respective firing rates. The method was tested on both simulated and experimental signals.
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https://hal.archives-ouvertes.fr/hal-01074903
Contributor : Éric Le Carpentier <>
Submitted on : Wednesday, October 15, 2014 - 5:57:13 PM
Last modification on : Tuesday, September 21, 2021 - 4:12:12 PM
Long-term archiving on: : Friday, January 16, 2015 - 10:50:47 AM

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Eric Le Carpentier, Yannick Aoustin, Jonathan Monsifrot, Dario Farina. Online Intramuscular EMG Decomposition with Varying Number of Active Motor Units. International Conference on NeuroRehabilitation (Replace, Repair, Restore, Relieve - Bridging Clinical and Engineering Solutions in Neurorehabilitation), Jun 2014, Aalborg, pp.303 - 311, ⟨10.1007/978-3-319-08072-7_50⟩. ⟨hal-01074903⟩

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