Intra-subject approach for gait-event prediction by neural network interpretation of EMG signals

Abstract Background Machine learning models were satisfactorily implemented for estimating gait events from surface electromyographic (sEMG) signals during walking. Most of them are based on inter-subject approaches for data preparation. Aim of the study is to propose an intra-subject approach for b...

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Hlavní autoři:	Francesco Di Nardo, Christian Morbidoni, Guido Mascia, Federica Verdini, Sandro Fioretti
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2020-07-01
Edice:	BioMedical Engineering OnLine
Témata:	Surface EMG Machine learning Neural networks Gait-phase classification Ground walking Intra-subject data
On-line přístup:	http://link.springer.com/article/10.1186/s12938-020-00803-1
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