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Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults

BACKGROUND: Wearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a hu...

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Autores principales: Schwenk, Michael, Grewal, Gurtej S, Honarvar, Bahareh, Schwenk, Stefanie, Mohler, Jane, Khalsa, Dharma S, Najafi, Bijan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290812/
https://www.ncbi.nlm.nih.gov/pubmed/25496052
http://dx.doi.org/10.1186/1743-0003-11-164
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author Schwenk, Michael
Grewal, Gurtej S
Honarvar, Bahareh
Schwenk, Stefanie
Mohler, Jane
Khalsa, Dharma S
Najafi, Bijan
author_facet Schwenk, Michael
Grewal, Gurtej S
Honarvar, Bahareh
Schwenk, Stefanie
Mohler, Jane
Khalsa, Dharma S
Najafi, Bijan
author_sort Schwenk, Michael
collection PubMed
description BACKGROUND: Wearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a human-computer interface designed for interactive training. METHODS: Senior living community residents (mean age 84.6) with confirmed fall risk were randomized to an intervention (IG, n = 17) or control group (CG, n = 16). The IG underwent 4 weeks (twice a week) of balance training including weight shifting and virtual obstacle crossing tasks with visual/auditory real-time joint movement feedback using wearable sensors. The CG received no intervention. Outcome measures included changes in center of mass (CoM) sway, ankle and hip joint sway measured during eyes open (EO) and eyes closed (EC) balance test at baseline and post-intervention. Ankle-hip postural coordination was quantified by a reciprocal compensatory index (RCI). Physical performance was quantified by the Alternate-Step-Test (AST), Timed-up-and-go (TUG), and gait assessment. User experience was measured by a standardized questionnaire. RESULTS: After the intervention sway of CoM, hip, and ankle were reduced in the IG compared to the CG during both EO and EC condition (p = .007-.042). Improvement was obtained for AST (p = .037), TUG (p = .024), fast gait speed (p = . 010), but not normal gait speed (p = .264). Effect sizes were moderate for all outcomes. RCI did not change significantly. Users expressed a positive training experience including fun, safety, and helpfulness of sensor-feedback. CONCLUSIONS: Results of this proof-of-concept study suggest that older adults at risk of falling can benefit from the balance training program. Study findings may help to inform future exercise interventions integrating wearable sensors for guided game-based training in home- and community environments. Future studies should evaluate the added value of the proposed sensor-based training paradigm compared to traditional balance training programs and commercial exergames. TRIAL REGISTRATION: http://www.clinicaltrials.govNCT02043834. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1743-0003-11-164) contains supplementary material, which is available to authorized users.
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spelling pubmed-42908122015-01-13 Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults Schwenk, Michael Grewal, Gurtej S Honarvar, Bahareh Schwenk, Stefanie Mohler, Jane Khalsa, Dharma S Najafi, Bijan J Neuroeng Rehabil Research BACKGROUND: Wearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a human-computer interface designed for interactive training. METHODS: Senior living community residents (mean age 84.6) with confirmed fall risk were randomized to an intervention (IG, n = 17) or control group (CG, n = 16). The IG underwent 4 weeks (twice a week) of balance training including weight shifting and virtual obstacle crossing tasks with visual/auditory real-time joint movement feedback using wearable sensors. The CG received no intervention. Outcome measures included changes in center of mass (CoM) sway, ankle and hip joint sway measured during eyes open (EO) and eyes closed (EC) balance test at baseline and post-intervention. Ankle-hip postural coordination was quantified by a reciprocal compensatory index (RCI). Physical performance was quantified by the Alternate-Step-Test (AST), Timed-up-and-go (TUG), and gait assessment. User experience was measured by a standardized questionnaire. RESULTS: After the intervention sway of CoM, hip, and ankle were reduced in the IG compared to the CG during both EO and EC condition (p = .007-.042). Improvement was obtained for AST (p = .037), TUG (p = .024), fast gait speed (p = . 010), but not normal gait speed (p = .264). Effect sizes were moderate for all outcomes. RCI did not change significantly. Users expressed a positive training experience including fun, safety, and helpfulness of sensor-feedback. CONCLUSIONS: Results of this proof-of-concept study suggest that older adults at risk of falling can benefit from the balance training program. Study findings may help to inform future exercise interventions integrating wearable sensors for guided game-based training in home- and community environments. Future studies should evaluate the added value of the proposed sensor-based training paradigm compared to traditional balance training programs and commercial exergames. TRIAL REGISTRATION: http://www.clinicaltrials.govNCT02043834. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1743-0003-11-164) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-13 /pmc/articles/PMC4290812/ /pubmed/25496052 http://dx.doi.org/10.1186/1743-0003-11-164 Text en © Schwenk et al.; licensee BioMed Central. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Schwenk, Michael
Grewal, Gurtej S
Honarvar, Bahareh
Schwenk, Stefanie
Mohler, Jane
Khalsa, Dharma S
Najafi, Bijan
Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title_full Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title_fullStr Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title_full_unstemmed Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title_short Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
title_sort interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290812/
https://www.ncbi.nlm.nih.gov/pubmed/25496052
http://dx.doi.org/10.1186/1743-0003-11-164
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