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

2020Journal article Open access
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dc.contributor.authorPonciano, Vasco Rafael Gaspar
dc.contributor.authorPires, Ivan M.
dc.contributor.authorRibeiro, Fernando Reinaldo
dc.contributor.authorVillasana, María Vanessa
dc.contributor.authorTeixeira, M.C.C.
dc.contributor.authorZdravevski, Eftim
dc.date.accessioned2020-09-16T09:47:46Z
dc.date.available2020-09-16T09:47:46Z
dc.date.issued2020
dc.description.abstractThe 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPonciano, 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/COMPUTERS9030067pt_PT
dc.identifier.doihttps://doi.org/10.3390/computers9030067pt_PT
dc.identifier.issn2073-431X
dc.identifier.urihttp://hdl.handle.net/10400.11/7248
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationUIDB/EEA/50008/2020pt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2073-431X/9/3/67pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectDiseasespt_PT
dc.subjectElectrocardiographypt_PT
dc.subjectElectroencephalographypt_PT
dc.subjectTimed-up and go testpt_PT
dc.subjectSensorspt_PT
dc.subjectMobile devicespt_PT
dc.subjectFeature detectionpt_PT
dc.subjectDiseasespt_PT
dc.subjectOlder adultspt_PT
dc.titleExperimental study for determining the parameters required for detecting ECG and EEG related diseases during the timed-up and go testpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue3pt_PT
oaire.citation.titleComputerspt_PT
oaire.citation.volume9pt_PT
person.familyNameSerrano Pires
person.familyNameReinaldo Silva Garcia Ribeiro
person.familyNameTeixeira
person.givenNameIvan Miguel
person.givenNameFernando
person.givenNameM.C.C.
person.identifier.ciencia-id211D-8B3D-0131
person.identifier.ciencia-id7B1C-D761-291D
person.identifier.ciencia-id0913-BC21-F66E
person.identifier.orcid0000-0002-3394-6762
person.identifier.orcid0000-0002-1225-3844
person.identifier.orcid0000-0002-8534-9484
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication53c92dfa-27be-4305-9b32-f3cf2e36a4f1
relation.isAuthorOfPublication165761b1-f958-4c13-b53f-ef0a4dde1d97
relation.isAuthorOfPublication5c53ae6c-7865-4ef1-adea-ea2fa221aee4
relation.isAuthorOfPublication.latestForDiscovery5c53ae6c-7865-4ef1-adea-ea2fa221aee4

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