Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test
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/10400.11/7248 |
Resumo: | The use of smartphones, coupled with different sensors, makes it an attractive solution for measuring different physical and physiological features, allowing for the monitoring of various parameters and even identifying some diseases. The BITalino device allows the use of different sensors, including Electroencephalography (EEG) and Electrocardiography (ECG) sensors, to study different health parameters. With these devices, the acquisition of signals is straightforward, and it is possible to connect them using a Bluetooth connection. With the acquired data, it is possible to measure parameters such as calculating the QRS complex and its variation with ECG data to control the individual’s heartbeat. Similarly, by using the EEG sensor, one could analyze the individual’s brain activity and frequency. The purpose of this paper is to present a method for recognition of the diseases related to ECG and EEG data, with sensors available in off-the-shelf mobile devices and sensors connected to a BITalino device. The data were collected during the elderly’s experiences, performing the Timed-Up and Go test, and the different diseases found in the sample in the study. The data were analyzed, and the following features were extracted from the ECG, including heart rate, linear heart rate variability, the average QRS interval, the average R-R interval, and the average R-S interval, and the EEG, including frequency and variability. Finally, the diseases are correlated with different parameters, proving that there are relations between the individuals and the different health conditions. |
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Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go testDiseasesElectrocardiographyElectroencephalographyTimed-up and go testSensorsMobile devicesFeature detectionDiseasesOlder adultsThe use of smartphones, coupled with different sensors, makes it an attractive solution for measuring different physical and physiological features, allowing for the monitoring of various parameters and even identifying some diseases. The BITalino device allows the use of different sensors, including Electroencephalography (EEG) and Electrocardiography (ECG) sensors, to study different health parameters. With these devices, the acquisition of signals is straightforward, and it is possible to connect them using a Bluetooth connection. With the acquired data, it is possible to measure parameters such as calculating the QRS complex and its variation with ECG data to control the individual’s heartbeat. Similarly, by using the EEG sensor, one could analyze the individual’s brain activity and frequency. The purpose of this paper is to present a method for recognition of the diseases related to ECG and EEG data, with sensors available in off-the-shelf mobile devices and sensors connected to a BITalino device. The data were collected during the elderly’s experiences, performing the Timed-Up and Go test, and the different diseases found in the sample in the study. The data were analyzed, and the following features were extracted from the ECG, including heart rate, linear heart rate variability, the average QRS interval, the average R-R interval, and the average R-S interval, and the EEG, including frequency and variability. Finally, the diseases are correlated with different parameters, proving that there are relations between the individuals and the different health conditions.MDPIRepositório Científico do Instituto Politécnico de Castelo BrancoPonciano, VascoPires, IvanRibeiro, Fernando ReinaldoVillasana, MariaTeixeira, M.C.CZdravevski, Eftim2020-09-16T09:47:46Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/7248engPonciano, V., Pires, I. M., Ribeiro, F. R., Villasana, M. V., Teixeira, M. C., & Zdravevski, E. (2020). Experimental Study for Determining the Parameters Required for Detecting ECG and EEG Related Diseases During the Timed-Up and Go Test. Computers. ISSN 2073-431X. 9(3), 67. https://doi.org/10.3390/COMPUTERS90300672073-431Xhttps://doi.org/10.3390/computers9030067info: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:RCAAP2023-01-16T11:47:36Zoai:repositorio.ipcb.pt:10400.11/7248Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:37:48.440279Repositório 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 |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
title |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
spellingShingle |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test Ponciano, Vasco Diseases Electrocardiography Electroencephalography Timed-up and go test Sensors Mobile devices Feature detection Diseases Older adults |
title_short |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
title_full |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
title_fullStr |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
title_full_unstemmed |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
title_sort |
Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test |
author |
Ponciano, Vasco |
author_facet |
Ponciano, Vasco Pires, Ivan Ribeiro, Fernando Reinaldo Villasana, Maria Teixeira, M.C.C Zdravevski, Eftim |
author_role |
author |
author2 |
Pires, Ivan Ribeiro, Fernando Reinaldo Villasana, Maria Teixeira, M.C.C Zdravevski, Eftim |
author2_role |
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 Ribeiro, Fernando Reinaldo Villasana, Maria Teixeira, M.C.C Zdravevski, Eftim |
dc.subject.por.fl_str_mv |
Diseases Electrocardiography Electroencephalography Timed-up and go test Sensors Mobile devices Feature detection Diseases Older adults |
topic |
Diseases Electrocardiography Electroencephalography Timed-up and go test Sensors Mobile devices Feature detection Diseases Older adults |
description |
The use of smartphones, coupled with different sensors, makes it an attractive solution for measuring different physical and physiological features, allowing for the monitoring of various parameters and even identifying some diseases. The BITalino device allows the use of different sensors, including Electroencephalography (EEG) and Electrocardiography (ECG) sensors, to study different health parameters. With these devices, the acquisition of signals is straightforward, and it is possible to connect them using a Bluetooth connection. With the acquired data, it is possible to measure parameters such as calculating the QRS complex and its variation with ECG data to control the individual’s heartbeat. Similarly, by using the EEG sensor, one could analyze the individual’s brain activity and frequency. The purpose of this paper is to present a method for recognition of the diseases related to ECG and EEG data, with sensors available in off-the-shelf mobile devices and sensors connected to a BITalino device. The data were collected during the elderly’s experiences, performing the Timed-Up and Go test, and the different diseases found in the sample in the study. The data were analyzed, and the following features were extracted from the ECG, including heart rate, linear heart rate variability, the average QRS interval, the average R-R interval, and the average R-S interval, and the EEG, including frequency and variability. Finally, the diseases are correlated with different parameters, proving that there are relations between the individuals and the different health conditions. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-09-16T09:47:46Z 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/10400.11/7248 |
url |
http://hdl.handle.net/10400.11/7248 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ponciano, V., Pires, I. M., Ribeiro, F. R., Villasana, M. V., Teixeira, M. C., & Zdravevski, E. (2020). Experimental Study for Determining the Parameters Required for Detecting ECG and EEG Related Diseases During the Timed-Up and Go Test. Computers. ISSN 2073-431X. 9(3), 67. https://doi.org/10.3390/COMPUTERS9030067 2073-431X https://doi.org/10.3390/computers9030067 |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799130840683249664 |