Prediction of leg muscle activities from arm muscle activities in arm and leg cycling.
EMG-based control
hybrid arm and leg cycling
neural network
Journal
Anatomical record (Hoboken, N.J. : 2007)
ISSN: 1932-8494
Titre abrégé: Anat Rec (Hoboken)
Pays: United States
ID NLM: 101292775
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
revised:
31
03
2022
received:
12
12
2021
accepted:
05
05
2022
pubmed:
18
6
2022
medline:
22
3
2023
entrez:
17
6
2022
Statut:
ppublish
Résumé
Functional electrical stimulation (FES) driven leg cycling is usually controlled by previously established stimulation patterns. We investigated the potential utilization of a particular computational method for controlling electrical stimulation of lower limb muscles by real-time electromyography (EMG) signals of arm muscles during hybrid arm and leg cycling. In hybrid arm and leg cycling, arm cranking is performed voluntarily, while leg cycling is driven by FES. In this study, we investigate arm and leg cycling movements of able-bodied persons when both arm and leg cycling is performed voluntarily without FES. We present a neural network-based model in which the input of the neural network is given by a time series of upper limb muscle activities (EMG), and the output provides potential lower limb muscle activities. The particular neural network was a nonlinear autoregressive exogen (NARX) neural network. The measured EMG signals of the lower limb muscles were compared to the signals that were predicted by the neural network. The neural network was trained with data recorded from four participants. Our preliminary results show notable differences between the predicted and the experimentally measured lower limb muscle activities. The prediction was good only for 60% of the movement time. We conclude that-while including arm cycling in the movement-simpler control modalities or further consideration of applying machine-learning techniques has to be taken into account to improve voluntary upper limb-controlled FES assisted leg cycling.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
710-719Informations de copyright
© 2022 The Authors. The Anatomical Record published by Wiley Periodicals LLC on behalf of American Association for Anatomy.
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