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Novel Use of a Smartphone to Measure Standing Balance
BACKGROUND: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers, and patients measure standing balance. Utilizing the inherent sensors in every smartphone, a mobile...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454555/ https://www.ncbi.nlm.nih.gov/pubmed/28582247 http://dx.doi.org/10.2196/rehab.4511 |
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author | Shah, Nirtal Aleong, Rosanne So, Ivan |
author_facet | Shah, Nirtal Aleong, Rosanne So, Ivan |
author_sort | Shah, Nirtal |
collection | PubMed |
description | BACKGROUND: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers, and patients measure standing balance. Utilizing the inherent sensors in every smartphone, a mobile application was developed to provide a method of objectively measuring standing balance. OBJECTIVE: We aimed to determine if a mobile phone application, which utilizes the phone’s accelerometer, can quantify standing balance. METHODS: Three smartphones were positioned simultaneously above the participants’ malleolus and patella and at the level of the umbilicus. Once secured, the myAnkle application was initiated to measure acceleration. Forty-eight participants completed 8 different balance exercises separately for the right and left legs. Accelerometer readings were obtained from each mobile phone and mean acceleration was calculated for each exercise at each ankle and knee and the torso. RESULTS: Mean acceleration vector magnitude was reciprocally transformed to address skewness in the data distribution. Repeated measures ANOVAs were completed using the transformed data. A significant 2-way interaction was revealed between exercise condition and the body position of the phone (P<.001). Post-hoc tests indicated higher acceleration vector magnitude for exercises of greater difficulty. ANOVAs at each body position were conducted to examine the effect of exercise. The results revealed the knee as the location most sensitive for the detection of differences in acceleration between exercises. The accelerometer ranking of exercise difficulty showed high agreement with expert clinical rater rankings (kappa statistic>0.9). CONCLUSIONS: The myAnkle application revealed significantly greater acceleration magnitude for exercises of greater difficulty. Positioning of the mobile phone at the knee proved to be the most sensitive to changes in accelerometer values due to exercise difficulty. Application validity was shown through comparison with clinical raters. As such, the myAnkle app has utility as a measurement tool for standing balance. |
format | Online Article Text |
id | pubmed-5454555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-54545552017-06-07 Novel Use of a Smartphone to Measure Standing Balance Shah, Nirtal Aleong, Rosanne So, Ivan JMIR Rehabil Assist Technol Original Paper BACKGROUND: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers, and patients measure standing balance. Utilizing the inherent sensors in every smartphone, a mobile application was developed to provide a method of objectively measuring standing balance. OBJECTIVE: We aimed to determine if a mobile phone application, which utilizes the phone’s accelerometer, can quantify standing balance. METHODS: Three smartphones were positioned simultaneously above the participants’ malleolus and patella and at the level of the umbilicus. Once secured, the myAnkle application was initiated to measure acceleration. Forty-eight participants completed 8 different balance exercises separately for the right and left legs. Accelerometer readings were obtained from each mobile phone and mean acceleration was calculated for each exercise at each ankle and knee and the torso. RESULTS: Mean acceleration vector magnitude was reciprocally transformed to address skewness in the data distribution. Repeated measures ANOVAs were completed using the transformed data. A significant 2-way interaction was revealed between exercise condition and the body position of the phone (P<.001). Post-hoc tests indicated higher acceleration vector magnitude for exercises of greater difficulty. ANOVAs at each body position were conducted to examine the effect of exercise. The results revealed the knee as the location most sensitive for the detection of differences in acceleration between exercises. The accelerometer ranking of exercise difficulty showed high agreement with expert clinical rater rankings (kappa statistic>0.9). CONCLUSIONS: The myAnkle application revealed significantly greater acceleration magnitude for exercises of greater difficulty. Positioning of the mobile phone at the knee proved to be the most sensitive to changes in accelerometer values due to exercise difficulty. Application validity was shown through comparison with clinical raters. As such, the myAnkle app has utility as a measurement tool for standing balance. JMIR Publications Inc. 2016-03-29 /pmc/articles/PMC5454555/ /pubmed/28582247 http://dx.doi.org/10.2196/rehab.4511 Text en ©Nirtal Shah, Rosanne Aleong, Ivan So. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 29.03.2016. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Rehabilitation and Assistive Technology, is properly cited. The complete bibliographic information, a link to the original publication on http://rehab.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Shah, Nirtal Aleong, Rosanne So, Ivan Novel Use of a Smartphone to Measure Standing Balance |
title | Novel Use of a Smartphone to Measure Standing Balance |
title_full | Novel Use of a Smartphone to Measure Standing Balance |
title_fullStr | Novel Use of a Smartphone to Measure Standing Balance |
title_full_unstemmed | Novel Use of a Smartphone to Measure Standing Balance |
title_short | Novel Use of a Smartphone to Measure Standing Balance |
title_sort | novel use of a smartphone to measure standing balance |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454555/ https://www.ncbi.nlm.nih.gov/pubmed/28582247 http://dx.doi.org/10.2196/rehab.4511 |
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