Heart rate variability estimation with joint accelerometer and gyroscope sensing
| dc.contributor.author | Olli Lahdenoja | |
| dc.contributor.author | Tero Hurnanen | |
| dc.contributor.author | Mojtaba Jafari Tadi | |
| dc.contributor.author | Mikko Pänkäälä | |
| dc.contributor.author | Tero Koivisto | |
| dc.contributor.organization | fi=Technology Research Center TRC|en=Technology Research Center TRC| | |
| dc.contributor.organization | fi=kliininen laitos|en=Department of Clinical Medicine| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.58905910210 | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.61334543354 | |
| dc.contributor.organization-code | 2609060 | |
| dc.converis.publication-id | 17391066 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/17391066 | |
| dc.date.accessioned | 2022-10-28T13:54:26Z | |
| dc.date.available | 2022-10-28T13:54:26Z | |
| 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.pagerange | 717 | |
| dc.format.pagerange | 720 | |
| dc.identifier.eisbn | 978-1-5090-0895-7 | |
| dc.identifier.isbn | 978-1-5090-0896-4 | |
| dc.identifier.issn | 2325-887X | |
| dc.identifier.jour-issn | 2325-8861 | |
| dc.identifier.olddbid | 185100 | |
| dc.identifier.oldhandle | 10024/168194 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/41940 | |
| dc.identifier.url | http://ieeexplore.ieee.org/document/7868843/ | |
| dc.identifier.urn | URN:NBN:fi-fe2021042715733 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Lahdenoja, Olli | |
| dc.okm.affiliatedauthor | Hurnanen, Tero | |
| dc.okm.affiliatedauthor | Jafari Tadi, Mojtaba | |
| dc.okm.affiliatedauthor | Pänkäälä, Mikko | |
| dc.okm.affiliatedauthor | Koivisto, Tero | |
| dc.okm.discipline | 113 Computer and information sciences | en_GB |
| dc.okm.discipline | 217 Medical engineering | en_GB |
| dc.okm.discipline | 222 Other engineering and technologies | en_GB |
| dc.okm.discipline | 113 Tietojenkäsittely ja informaatiotieteet | fi_FI |
| dc.okm.discipline | 217 Lääketieteen tekniikka | fi_FI |
| dc.okm.discipline | 222 Muu tekniikka | fi_FI |
| dc.okm.internationalcopublication | not an international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A4 Conference Article | |
| dc.publisher.country | United States | en_GB |
| dc.publisher.country | Yhdysvallat (USA) | fi_FI |
| dc.publisher.country-code | US | |
| dc.relation.conference | Computers in Cardiology (CinC) | |
| dc.relation.doi | 10.22489/CinC.2016.209-166 | |
| dc.relation.ispartofjournal | Computing in Cardiology | |
| dc.relation.volume | 43 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/168194 | |
| dc.title | Heart rate variability estimation with joint accelerometer and gyroscope sensing | |
| dc.title.book | Computing in Cardiology Conference (CinC), 2016 | |
| dc.year.issued | 2016 |
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