Artificial intelligence for automatic classification of needle EMG signals: A scoping review-Reference-Cited by-同舟云学术

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

Published:2024-03 Issue: Volume:159 Page:41-55
ISSN:1388-2457
Container-title:Clinical Neurophysiology
language:en
Short-container-title:Clinical Neurophysiology

Author:

de Jonge S.,Potters W.V.^ORCID,Verhamme C.^ORCID

Publisher

Elsevier BV

Reference77 articles.

1. Transparent muscle characterization using quantitative electromyography: different binarization mappings;AbdelMaseeh;IEEE Trans Neural Syst Rehabil Eng,2014

2. Prognosis and prognostic research: validating a prognostic model;Altman;BMJ,2009

3. An EMG-based feature extraction method using a normalized weight vertical visibility algorithm for myopathy and neuropathy detection;Artameeyanant;Springerplus,2016

4. Features based on intrinsic mode functions for classification of EMG signals Features based on intrinsic mode functions for classification of EMG signals 157;Bajaj;Int J Biomed Eng Technol,2015

5. Assessment of electromyograms using genetic algorithm and artificial neural networks;Bakiya;Evol Intell,2021

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