Artificial intelligence for automatic classification of needle EMG signals: A scoping review.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
PMID: 38246117

Abstract

OBJECTIVE: This scoping review provides an overview of artificial intelligence (AI), including machine and deep learning techniques, in the interpretation of clinical needle electromyography (nEMG) signals.

Authors

  • S de Jonge
    Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
  • W V Potters
    Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands; TrianecT, Padualaan 8, Utrecht, The Netherlands.
  • C Verhamme
    Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands. Electronic address: c.verhamme@amsterdamumc.nl.

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