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A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation
BACKGROUND: Gait disorders are common among older adults. With an increase in the use of technology among older adults, a mobile phone app provides a solution for older adults to self-monitor their gait quality in daily life. OBJECTIVE: This study aimed to develop a gait-monitoring mobile phone app...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284482/ https://www.ncbi.nlm.nih.gov/pubmed/32452821 http://dx.doi.org/10.2196/14453 |
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author | Zhong, Runting Rau, Pei-Luen Patrick |
author_facet | Zhong, Runting Rau, Pei-Luen Patrick |
author_sort | Zhong, Runting |
collection | PubMed |
description | BACKGROUND: Gait disorders are common among older adults. With an increase in the use of technology among older adults, a mobile phone app provides a solution for older adults to self-monitor their gait quality in daily life. OBJECTIVE: This study aimed to develop a gait-monitoring mobile phone app (Pocket Gait) and evaluate its acceptability and usability among potential older users. METHODS: The app was developed to allow older adults to track their gait quality, including step frequency, acceleration root mean square (RMS), step regularity, step symmetry, and step variability. We recruited a total of 148 community-dwelling older adults aged 60 years and older from two cities in China: Beijing and Chongqing. They walked in three ways (single task, dual task, and fast walking) using a smartphone with the gait-monitoring app installed and completed an acceptability and usability survey after the walk test. User acceptability was measured by a questionnaire including four quantitative measures: perceived ease of use, perceived usefulness, ease of learning, and intention to use. Usability was measured using the System Usability Scale (SUS). Interviews were conducted with participants to collect open-ended feedback questions. RESULTS: Task type had a significant effect on all gait parameters, namely, step frequency, RMS, step variability, step regularity, and step symmetry (all P values <.001). Age had a significant effect on step frequency (P=.01), and region had a significant effect on step regularity (P=.04). The acceptability of the gait-monitoring app was positive among older adults. Participants identified the usability of the system with an overall score of 59.7 (SD 10.7) out of 100. Older adults from Beijing scored significantly higher SUS compared with older adults from Chongqing (P<.001). The age of older adults was significantly associated with their SUS score (P=.048). Older adults identified improvements such as a larger font size, inclusion of reference values for gait parameters, and inclusion of heart rate and blood pressure monitoring. CONCLUSIONS: This mobile phone app is a health management tool for older adults to self-manage their gait quality and prevent adverse outcomes. In the future, it will be important to take factors such as age and region into consideration while designing a mobile phone–based gait assessment app. The feedback of the participants would help to design more elderly-friendly products. |
format | Online Article Text |
id | pubmed-7284482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-72844822020-06-19 A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation Zhong, Runting Rau, Pei-Luen Patrick JMIR Mhealth Uhealth Original Paper BACKGROUND: Gait disorders are common among older adults. With an increase in the use of technology among older adults, a mobile phone app provides a solution for older adults to self-monitor their gait quality in daily life. OBJECTIVE: This study aimed to develop a gait-monitoring mobile phone app (Pocket Gait) and evaluate its acceptability and usability among potential older users. METHODS: The app was developed to allow older adults to track their gait quality, including step frequency, acceleration root mean square (RMS), step regularity, step symmetry, and step variability. We recruited a total of 148 community-dwelling older adults aged 60 years and older from two cities in China: Beijing and Chongqing. They walked in three ways (single task, dual task, and fast walking) using a smartphone with the gait-monitoring app installed and completed an acceptability and usability survey after the walk test. User acceptability was measured by a questionnaire including four quantitative measures: perceived ease of use, perceived usefulness, ease of learning, and intention to use. Usability was measured using the System Usability Scale (SUS). Interviews were conducted with participants to collect open-ended feedback questions. RESULTS: Task type had a significant effect on all gait parameters, namely, step frequency, RMS, step variability, step regularity, and step symmetry (all P values <.001). Age had a significant effect on step frequency (P=.01), and region had a significant effect on step regularity (P=.04). The acceptability of the gait-monitoring app was positive among older adults. Participants identified the usability of the system with an overall score of 59.7 (SD 10.7) out of 100. Older adults from Beijing scored significantly higher SUS compared with older adults from Chongqing (P<.001). The age of older adults was significantly associated with their SUS score (P=.048). Older adults identified improvements such as a larger font size, inclusion of reference values for gait parameters, and inclusion of heart rate and blood pressure monitoring. CONCLUSIONS: This mobile phone app is a health management tool for older adults to self-manage their gait quality and prevent adverse outcomes. In the future, it will be important to take factors such as age and region into consideration while designing a mobile phone–based gait assessment app. The feedback of the participants would help to design more elderly-friendly products. JMIR Publications 2020-05-26 /pmc/articles/PMC7284482/ /pubmed/32452821 http://dx.doi.org/10.2196/14453 Text en ©Runting Zhong, Pei-Luen Patrick Rau. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 26.05.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Zhong, Runting Rau, Pei-Luen Patrick A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title | A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title_full | A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title_fullStr | A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title_full_unstemmed | A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title_short | A Mobile Phone–Based Gait Assessment App for the Elderly: Development and Evaluation |
title_sort | mobile phone–based gait assessment app for the elderly: development and evaluation |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284482/ https://www.ncbi.nlm.nih.gov/pubmed/32452821 http://dx.doi.org/10.2196/14453 |
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