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Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults
Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the acquisition of diverse data. This study focuses o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349529/ https://www.ncbi.nlm.nih.gov/pubmed/32575650 http://dx.doi.org/10.3390/s20123481 |
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author | Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro Teixeira, Maria Zdravevski, Eftim |
author_facet | Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro Teixeira, Maria Zdravevski, Eftim |
author_sort | Ponciano, Vasco |
collection | PubMed |
description | Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the acquisition of diverse data. This study focuses on the analysis of the data collected from the mobile devices sensors and a pressure sensor connected to a Bitalino device for the measurement of the Timed-Up and Go test. The data acquisition was performed within different environments from multiple individuals with distinct types of diseases. Then this data was analyzed to estimate the various parameters of the Timed-Up and Go test. Firstly, the pressure sensor is used to extract the reaction and total test time. Secondly, the magnetometer sensors are used to identify the total test time and different parameters related to turning around. Finally, the accelerometer sensor is used to extract the reaction time, total test time, duration of turning around, going time, return time, and many other derived metrics. Our experiments showed that these parameters could be automatically and reliably detected with a mobile device. Moreover, we identified that the time to perform the Timed-Up and Go test increases with age and the presence of diseases related to locomotion. |
format | Online Article Text |
id | pubmed-7349529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73495292020-07-14 Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro Teixeira, Maria Zdravevski, Eftim Sensors (Basel) Article Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the acquisition of diverse data. This study focuses on the analysis of the data collected from the mobile devices sensors and a pressure sensor connected to a Bitalino device for the measurement of the Timed-Up and Go test. The data acquisition was performed within different environments from multiple individuals with distinct types of diseases. Then this data was analyzed to estimate the various parameters of the Timed-Up and Go test. Firstly, the pressure sensor is used to extract the reaction and total test time. Secondly, the magnetometer sensors are used to identify the total test time and different parameters related to turning around. Finally, the accelerometer sensor is used to extract the reaction time, total test time, duration of turning around, going time, return time, and many other derived metrics. Our experiments showed that these parameters could be automatically and reliably detected with a mobile device. Moreover, we identified that the time to perform the Timed-Up and Go test increases with age and the presence of diseases related to locomotion. MDPI 2020-06-19 /pmc/articles/PMC7349529/ /pubmed/32575650 http://dx.doi.org/10.3390/s20123481 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro Teixeira, Maria Zdravevski, Eftim Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title | Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title_full | Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title_fullStr | Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title_full_unstemmed | Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title_short | Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults |
title_sort | mobile computing technologies for health and mobility assessment: research design and results of the timed up and go test in older adults |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349529/ https://www.ncbi.nlm.nih.gov/pubmed/32575650 http://dx.doi.org/10.3390/s20123481 |
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