Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric prostheses
Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric prostheses
The efferent control chain for an upper-limb myoelectric prosthesis can be separated into 3 key areas: signal generation, signal acquisition, and device response. Data were collected from twenty trans-radial myoelectric prosthesis users using their own clinically prescribed devices, to establish the relative impact of these potential control factors on user performance (user functionality and everyday prosthesis usage). By identifying the key factor(s), we can guide future developments to ensure clinical impact. Skill in generating muscle signals was assessed via reaction times and signal tracking. To assess the predictability of signal acquisition, we inspected reaction time spread and undesired hand activations. As a measure of device response, we recorded the electromechanical delay between electrode stimulation and the onset of hand movement. Results suggest abstract measures of skill in controlling muscle signals are poorly correlated with performance. Undesired activations of the hand or incorrect responses were correlated with almost all kinematics and gaze measures suggesting unpredictability is a key factor. Significant correlations were also found between several measures of performance and the electromechanical delay; however, unexpectedly, longer electromechanical delays correlated with better performance. Future research should focus on exploring causes of unpredictability, their relative impacts on performance and interventions to address this.
Chadwell, A.
c337930e-a6b5-43e3-8ca5-eed1d2d71340
Kenney, L.
67e5d27a-3331-4eeb-85f2-1f85bb103252
Thies, S.
233b0fa4-7a7d-4081-8e5b-5cb6126a8981
Head, John
cf34a318-8e41-41c4-af54-b3d970dfd24f
Galpin, A.
c3157315-5bd6-4123-9044-a379ebc7ae62
Baker, R.
a7c4bd4b-0e2f-4246-8883-0a4b658615aa
8 February 2021
Chadwell, A.
c337930e-a6b5-43e3-8ca5-eed1d2d71340
Kenney, L.
67e5d27a-3331-4eeb-85f2-1f85bb103252
Thies, S.
233b0fa4-7a7d-4081-8e5b-5cb6126a8981
Head, John
cf34a318-8e41-41c4-af54-b3d970dfd24f
Galpin, A.
c3157315-5bd6-4123-9044-a379ebc7ae62
Baker, R.
a7c4bd4b-0e2f-4246-8883-0a4b658615aa
Chadwell, A., Kenney, L., Thies, S., Head, John, Galpin, A. and Baker, R.
(2021)
Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric prostheses.
Scientific Reports, 11, [3300].
(doi:10.1038/s41598-021-82764-6).
Abstract
The efferent control chain for an upper-limb myoelectric prosthesis can be separated into 3 key areas: signal generation, signal acquisition, and device response. Data were collected from twenty trans-radial myoelectric prosthesis users using their own clinically prescribed devices, to establish the relative impact of these potential control factors on user performance (user functionality and everyday prosthesis usage). By identifying the key factor(s), we can guide future developments to ensure clinical impact. Skill in generating muscle signals was assessed via reaction times and signal tracking. To assess the predictability of signal acquisition, we inspected reaction time spread and undesired hand activations. As a measure of device response, we recorded the electromechanical delay between electrode stimulation and the onset of hand movement. Results suggest abstract measures of skill in controlling muscle signals are poorly correlated with performance. Undesired activations of the hand or incorrect responses were correlated with almost all kinematics and gaze measures suggesting unpredictability is a key factor. Significant correlations were also found between several measures of performance and the electromechanical delay; however, unexpectedly, longer electromechanical delays correlated with better performance. Future research should focus on exploring causes of unpredictability, their relative impacts on performance and interventions to address this.
This record has no associated files available for download.
More information
Accepted/In Press date: 17 December 2020
Published date: 8 February 2021
Identifiers
Local EPrints ID: 481185
URI: http://eprints.soton.ac.uk/id/eprint/481185
ISSN: 2045-2322
PURE UUID: 286f07b2-2ea6-4b63-a61f-d0f941a23ad4
Catalogue record
Date deposited: 17 Aug 2023 16:58
Last modified: 17 Mar 2024 04:21
Export record
Altmetrics
Contributors
Author:
A. Chadwell
Author:
L. Kenney
Author:
S. Thies
Author:
John Head
Author:
A. Galpin
Author:
R. Baker
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics