Experimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go test

Detalhes bibliográficos
Autor(a) principal: Ponciano, Vasco
Data de Publicação: 2020
Outros Autores: Pires, Ivan, Ribeiro, Fernando Reinaldo, Villasana, Maria, Teixeira, M.C.C, Zdravevski, Eftim
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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spelling 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
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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