Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.11/7180 |
Resumo: | 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. |
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Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adultsTimed-up and go testSensorsMobile devicesAccelerometerMagnetometerPressure sensorFeature detectionDiseasesOlder adultsDue 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.MDPIRepositório Científico do Instituto Politécnico de Castelo BrancoPonciano, VascoPires, Ivan MiguelRibeiro, Fernando ReinaldoVillasana, María VanessaCrisóstomo, RuteCanavarro, M.C.Zdravevski, Eftim2020-07-07T09:25:20Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/7180engPONCIANO, Vasco [et al.] (2020) - Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults. Sensors. ISSN 1424-8220. Vol. 20, nº 12, p. 3481. DOI https://www.mdpi.com/1424-8220/20/12/34811424-822010.3390/s20123481info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-12T01:46:35Zoai:repositorio.ipcb.pt:10400.11/7180Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:37:45.094789Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
title |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
spellingShingle |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults Ponciano, Vasco Timed-up and go test Sensors Mobile devices Accelerometer Magnetometer Pressure sensor Feature detection Diseases Older adults |
title_short |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
title_full |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
title_fullStr |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
title_full_unstemmed |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
title_sort |
Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults |
author |
Ponciano, Vasco |
author_facet |
Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro, M.C. Zdravevski, Eftim |
author_role |
author |
author2 |
Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro, M.C. Zdravevski, Eftim |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico de Castelo Branco |
dc.contributor.author.fl_str_mv |
Ponciano, Vasco Pires, Ivan Miguel Ribeiro, Fernando Reinaldo Villasana, María Vanessa Crisóstomo, Rute Canavarro, M.C. Zdravevski, Eftim |
dc.subject.por.fl_str_mv |
Timed-up and go test Sensors Mobile devices Accelerometer Magnetometer Pressure sensor Feature detection Diseases Older adults |
topic |
Timed-up and go test Sensors Mobile devices Accelerometer Magnetometer Pressure sensor Feature detection Diseases Older adults |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07-07T09:25:20Z 2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.11/7180 |
url |
http://hdl.handle.net/10400.11/7180 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PONCIANO, Vasco [et al.] (2020) - Mobile computing technologies for health and mobility assessment: research design and results of the ttmed up and go test in older adults. Sensors. ISSN 1424-8220. Vol. 20, nº 12, p. 3481. DOI https://www.mdpi.com/1424-8220/20/12/3481 1424-8220 10.3390/s20123481 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799130840621383680 |