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dc.contributor.authorUskovas, Gediminas
dc.contributor.authorValinevicius, Algimantas
dc.contributor.authorZilys, Mindaugas
dc.contributor.authorNavikas, Dangirutis
dc.contributor.authorFrivaldský, Michal
dc.contributor.authorPrauzek, Michal
dc.contributor.authorKonečný, Jaromír
dc.contributor.authorAndriukaitis, Darius
dc.date.accessioned2022-05-27T08:14:05Z
dc.date.available2022-05-27T08:14:05Z
dc.date.issued2022
dc.identifier.citationElectronics. 2022, vol. 11, issue 3, art. no. 484.cs
dc.identifier.issn2079-9292
dc.identifier.urihttp://hdl.handle.net/10084/146222
dc.description.abstractThis article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhythms, heart valve opening and closing disorders, and monitoring of patients' breathing. This article refers to the seismocardiogram hypothesis that the measurements of a seismocardiogram could be used to identify drivers' heart problems before they reach a critical condition and safely stop the vehicle by informing the relevant departments in a nonclinical manner. The proposed system works without an electrocardiogram, which helps to detect heart rhythms more easily. The estimation of the heart rate (HR) is calculated through automatically detected aortic valve opening (AO) peaks. The system is composed of two micro-electromechanical systems (MEMSs) to evaluate physiological parameters and eliminate the effects of external interference on the entire system. The few digital filtering methods are discussed and benchmarked to increase seismocardiogram efficiency. As a result, the fourth adaptive filter obtains the estimated HR = 65 beats per min (bmp) in a still noisy signal (SNR = -11.32 dB). In contrast with the low processing benefit (3.39 dB), 27 AO peaks were detected with a 917.56-ms peak interval mean over 1.11 s, and the calculated root mean square error (RMSE) was 0.1942 m/s(2) when the adaptive filter order is 50 and the adaptation step is equal to 0.933.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesElectronicscs
dc.relation.urihttps://doi.org/10.3390/electronics11030484cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectarrhythmiacs
dc.subjectdriving restrictionscs
dc.subjectadaptive digital filtercs
dc.subjectnoninvasive methodcs
dc.subjectheart ratecs
dc.titleDriver cardiovascular disease detection using seismocardiogramcs
dc.typearticlecs
dc.identifier.doi10.3390/electronics11030484
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume11cs
dc.description.issue3cs
dc.description.firstpageart. no. 484cs
dc.identifier.wos000756033400001


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.