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Augmented feedback for powered wheelchair training in a virtual environment
BACKGROUND: Powered wheelchair (PW) driving is a complex activity and requires the acquisition of several skills. Given the risks involved with PW use, safe and effective training methods are needed. Virtual reality training allows users to practice difficult tasks in a safe environment. An addition...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339295/ https://www.ncbi.nlm.nih.gov/pubmed/30658668 http://dx.doi.org/10.1186/s12984-019-0482-3 |
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author | Bigras, Catherine Kairy, Dahlia Archambault, Philippe S. |
author_facet | Bigras, Catherine Kairy, Dahlia Archambault, Philippe S. |
author_sort | Bigras, Catherine |
collection | PubMed |
description | BACKGROUND: Powered wheelchair (PW) driving is a complex activity and requires the acquisition of several skills. Given the risks involved with PW use, safe and effective training methods are needed. Virtual reality training allows users to practice difficult tasks in a safe environment. An additional benefit is that augmented feedback can be provided to optimize learning. The purpose of this study was to investigate whether providing augmented feedback during powered wheelchair simulator training results in superior performance, and whether skills learned in a virtual environment transfer to real PW driving. METHODS: Forty healthy young adults were randomly allocated to two groups: one received augmented feedback during simulator training while the control group received no augmented feedback. PW driving performance was assessed at baseline in both the real and virtual environment (RE and VE), after training in VE and two days later in VE and RE (retention and transfer tests). RESULTS: Both groups showed significantly better task completion time and number of collisions in the VE after training and these results were maintained two days later. The transfer test indicated better performance in the RE compared to baseline for both groups. Because time and collisions interact, a post-hoc 2D Kolmogonov-Smirnov test was used to investigate the differences in the speed-accuracy distributions for each group; a significant difference was found for the group receiving augmented feedback, before and after training, whereas the difference was not significant for the control group. There were no differences at the retention test, suggesting that augmented feedback was most effective during and immediately after training. CONCLUSIONS: PW simulator training is effective in improving task completion time and number of collisions. A small effect of augmented feedback was seen when looking at differences in the speed-accuracy distributions, highlighting the importance of accounting for the speed-accuracy tradeoff for PW driving. |
format | Online Article Text |
id | pubmed-6339295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63392952019-01-23 Augmented feedback for powered wheelchair training in a virtual environment Bigras, Catherine Kairy, Dahlia Archambault, Philippe S. J Neuroeng Rehabil Research BACKGROUND: Powered wheelchair (PW) driving is a complex activity and requires the acquisition of several skills. Given the risks involved with PW use, safe and effective training methods are needed. Virtual reality training allows users to practice difficult tasks in a safe environment. An additional benefit is that augmented feedback can be provided to optimize learning. The purpose of this study was to investigate whether providing augmented feedback during powered wheelchair simulator training results in superior performance, and whether skills learned in a virtual environment transfer to real PW driving. METHODS: Forty healthy young adults were randomly allocated to two groups: one received augmented feedback during simulator training while the control group received no augmented feedback. PW driving performance was assessed at baseline in both the real and virtual environment (RE and VE), after training in VE and two days later in VE and RE (retention and transfer tests). RESULTS: Both groups showed significantly better task completion time and number of collisions in the VE after training and these results were maintained two days later. The transfer test indicated better performance in the RE compared to baseline for both groups. Because time and collisions interact, a post-hoc 2D Kolmogonov-Smirnov test was used to investigate the differences in the speed-accuracy distributions for each group; a significant difference was found for the group receiving augmented feedback, before and after training, whereas the difference was not significant for the control group. There were no differences at the retention test, suggesting that augmented feedback was most effective during and immediately after training. CONCLUSIONS: PW simulator training is effective in improving task completion time and number of collisions. A small effect of augmented feedback was seen when looking at differences in the speed-accuracy distributions, highlighting the importance of accounting for the speed-accuracy tradeoff for PW driving. BioMed Central 2019-01-18 /pmc/articles/PMC6339295/ /pubmed/30658668 http://dx.doi.org/10.1186/s12984-019-0482-3 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Bigras, Catherine Kairy, Dahlia Archambault, Philippe S. Augmented feedback for powered wheelchair training in a virtual environment |
title | Augmented feedback for powered wheelchair training in a virtual environment |
title_full | Augmented feedback for powered wheelchair training in a virtual environment |
title_fullStr | Augmented feedback for powered wheelchair training in a virtual environment |
title_full_unstemmed | Augmented feedback for powered wheelchair training in a virtual environment |
title_short | Augmented feedback for powered wheelchair training in a virtual environment |
title_sort | augmented feedback for powered wheelchair training in a virtual environment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339295/ https://www.ncbi.nlm.nih.gov/pubmed/30658668 http://dx.doi.org/10.1186/s12984-019-0482-3 |
work_keys_str_mv | AT bigrascatherine augmentedfeedbackforpoweredwheelchairtraininginavirtualenvironment AT kairydahlia augmentedfeedbackforpoweredwheelchairtraininginavirtualenvironment AT archambaultphilippes augmentedfeedbackforpoweredwheelchairtraininginavirtualenvironment |