Heart rate variability estimation with joint accelerometer and gyroscope sensing

dc.contributor.authorOlli Lahdenoja
dc.contributor.authorTero Hurnanen
dc.contributor.authorMojtaba Jafari Tadi
dc.contributor.authorMikko Pänkäälä
dc.contributor.authorTero Koivisto
dc.contributor.organizationfi=Technology Research Center TRC|en=Technology Research Center TRC|
dc.contributor.organizationfi=kliininen laitos|en=Department of Clinical Medicine|
dc.contributor.organization-code1.2.246.10.2458963.20.58905910210
dc.contributor.organization-code1.2.246.10.2458963.20.61334543354
dc.contributor.organization-code2609060
dc.converis.publication-id17391066
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/17391066
dc.date.accessioned2022-10-28T13:54:26Z
dc.date.available2022-10-28T13:54:26Z
dc.description.abstract<p>This paper describes a method for estimation of heart rate (HR) and heart rate variability (HRV) with accelerometers and gyroscopes. We denote this joint seismocardiography (SCG) and gyrocardiography (GCG) approach as SCG/GCG. In principle, SCG which is a well known method measures the linear mechanical movements of the heart and GCG is a new technique which measures angular motion due to the chest micro-vibrations caused by myocardial rotation. As electrocardiography (ECG), they can also be performed in non-invasive manner using a device in contact to subjects skin, for example. Our method extracts HRV parameters based on single-axis and multi-axes autocorrelation analysis (1-AC and 6-AC) of all simultaneously captured SCG/GCG axes. The results of each axes are combined to maintain reliable HR- and HRV. We validate our results with a comparison study between simultaneous ECG and SCG/GCG recordings using a study group of 29 healthy male volunteers. The study provides a promising approach for HRV estimation with modern wearable devices.<br /></p>
dc.format.pagerange717
dc.format.pagerange720
dc.identifier.eisbn978-1-5090-0895-7
dc.identifier.isbn978-1-5090-0896-4
dc.identifier.issn2325-887X
dc.identifier.jour-issn2325-8861
dc.identifier.olddbid185100
dc.identifier.oldhandle10024/168194
dc.identifier.urihttps://www.utupub.fi/handle/11111/41940
dc.identifier.urlhttp://ieeexplore.ieee.org/document/7868843/
dc.identifier.urnURN:NBN:fi-fe2021042715733
dc.language.isoen
dc.okm.affiliatedauthorLahdenoja, Olli
dc.okm.affiliatedauthorHurnanen, Tero
dc.okm.affiliatedauthorJafari Tadi, Mojtaba
dc.okm.affiliatedauthorPänkäälä, Mikko
dc.okm.affiliatedauthorKoivisto, Tero
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline217 Medical engineeringen_GB
dc.okm.discipline222 Other engineering and technologiesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline217 Lääketieteen tekniikkafi_FI
dc.okm.discipline222 Muu tekniikkafi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.conferenceComputers in Cardiology (CinC)
dc.relation.doi10.22489/CinC.2016.209-166
dc.relation.ispartofjournalComputing in Cardiology
dc.relation.volume43
dc.source.identifierhttps://www.utupub.fi/handle/10024/168194
dc.titleHeart rate variability estimation with joint accelerometer and gyroscope sensing
dc.title.bookComputing in Cardiology Conference (CinC), 2016
dc.year.issued2016

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