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...

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Main Authors: Vasco Ponciano, Ivan Miguel Pires, Fernando Reinaldo Ribeiro, María Vanessa Villasana, Rute Crisóstomo, Maria Canavarro Teixeira, Eftim Zdravevski
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/12/3481
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spelling doaj-56c01f7105604ac592dc66ed25dad7f02020-11-25T03:11:59ZengMDPI AGSensors1424-82202020-06-01203481348110.3390/s20123481Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older AdultsVasco Ponciano0Ivan Miguel Pires1Fernando Reinaldo Ribeiro2María Vanessa Villasana3Rute Crisóstomo4Maria Canavarro Teixeira5Eftim Zdravevski6R&D Unit in Digital Services, Applications and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, PortugalR&D Unit in Digital Services, Applications and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalFaculty of Health Sciences, Universidade da Beira Interior, 6200-506 Covilhã, PortugalPolytechnic Institute of Castelo Branco, 6000-084 Castelo Branco, PortugalUTC de Recursos Naturais e Desenvolvimento Sustentável, Polytechnique Institute of Castelo Branco, 6001-909 Castelo Branco, PortugalFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North MacedoniaDue 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.https://www.mdpi.com/1424-8220/20/12/3481Timed-Up and Go testsensorsmobile devicesaccelerometermagnetometerpressure sensor
collection DOAJ
language English
format Article
sources DOAJ
author Vasco Ponciano
Ivan Miguel Pires
Fernando Reinaldo Ribeiro
María Vanessa Villasana
Rute Crisóstomo
Maria Canavarro Teixeira
Eftim Zdravevski
spellingShingle Vasco Ponciano
Ivan Miguel Pires
Fernando Reinaldo Ribeiro
María Vanessa Villasana
Rute Crisóstomo
Maria Canavarro Teixeira
Eftim Zdravevski
Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults
Sensors
Timed-Up and Go test
sensors
mobile devices
accelerometer
magnetometer
pressure sensor
author_facet Vasco Ponciano
Ivan Miguel Pires
Fernando Reinaldo Ribeiro
María Vanessa Villasana
Rute Crisóstomo
Maria Canavarro Teixeira
Eftim Zdravevski
author_sort Vasco Ponciano
title 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_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_sort mobile computing technologies for health and mobility assessment: research design and results of the timed up and go test in older adults
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-06-01
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.
topic Timed-Up and Go test
sensors
mobile devices
accelerometer
magnetometer
pressure sensor
url https://www.mdpi.com/1424-8220/20/12/3481
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