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Lookup NU author(s): Simon Stuttaford, Dr Matthew DysonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 The Author(s). Published by IOP Publishing Ltd.Objective. The objective of this study was to assess the impact of delayed feedback training on the retention of novel myoelectric skills, and to demonstrate the use of this training approach in the home environment. Approach. We trained limb-intact participants to use a motor learning-based upper-limb prosthesis control scheme called abstract decoding. A delayed feedback paradigm intended to prevent within-trial adaptation and to facilitate motor learning was used. We conducted two multi-day experiments. Experiment 1 was a laboratory-based study consisting of two groups trained over a 4 day period with concurrent or delayed feedback. An additional follow-up session took place after 18 days to assess the retention of motor skills. Experiment 2 was a home-based pilot study that took place over five consecutive days to investigate delayed feedback performance when using bespoke training structures. Main Results. Approximately 35 000 trials were collected across both experiments. Experiment 1 found that the retention of motor skills for the delayed feedback group was significantly better than that of their concurrent feedback counterparts. In addition, the delayed feedback group improved their retention of motor skills across days, whereas the concurrent feedback group did not. Experiment 2 demonstrated that by using a bespoke training protocol in an environment that is more conducive to learning, it is possible for participants to become highly accurate in the absence of feedback. Significance. These results show that with delayed feedback training, it is possible to retain novel myoelectric skills. Using abstract decoding participants can activate four distinct muscle patterns without using complex algorithms. The accuracy achieved in the pilot study supports the feasibility of motor learning-based upper-limb prosthesis control after home-based myoelectric training.
Author(s): Stuttaford SA, Dupan SSG, Nazarpour K, Dyson M
Publication type: Article
Publication status: Published
Journal: Journal of Neural Engineering
Year: 2023
Volume: 20
Issue: 3
Print publication date: 01/06/2023
Online publication date: 09/05/2023
Acceptance date: 16/03/2023
Date deposited: 30/05/2023
ISSN (print): 1741-2560
ISSN (electronic): 1741-2552
Publisher: Institute of Physics
URL: https://doi.org/10.1088/1741-2552/acc4ea
DOI: 10.1088/1741-2552/acc4ea
PubMed id: 36928264
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