Szczegóły publikacji

Opis bibliograficzny

Determining heart rate beat-to-beat from smartphone seismocardiograms: preliminary studies / Szymon Sieciński, Paweł Kostka // W: Innovations in biomedical engineering : [proceedings of the Innovations in Biomedical Engineering - IBE’ 2017 conference : Zabrze, Poland, October 19–20, 2017] / eds. Marek Gzik [et al.]. — Cham, Switzerland : Springer International Publishing, cop. 2018. — ( Advances in Intelligent Systems and Computing ; ISSN  2194-5357 ; vol. 623 ). — ISBN: 978-3-319-70062-5; e-ISBN: 978-3-319-70063-2. — S. 133–140. — Bibliogr. s. 139–140, Abstr. — Publikacja dostępna online od: 2017-10-24. — Sz. Sieciński - afiliacja: Silesian University of Technology, Zabrze

Autorzy (2)

  • Sieciński Szymon
  • Kostka Paweł S.

Słowa kluczowe

heart rate variabilitysmartphoneAO detectionseismocardiography

Dane bibliometryczne

ID BaDAP164591
Data dodania do BaDAP2026-02-04
Tekst źródłowyURL
DOI10.1007/978-3-319-70063-2_15
Rok publikacji2018
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaSpringer
Czasopismo/seriaAdvances in Intelligent Systems and Computing

Abstract

In the last decade the development of high quality, sensitive and inexpensive accelerometers has been seen, which in combination with low cost computational power provided the reasons for reconsidering analysis of cardiovascular vibrations in clinical practice. Seismocardiography (SCG) is a non-invasive method of analyzing and recording vibrations generated by heart activity and blood motion. Mobile devices offer the possibility to monitor health parameters. Various applications have been proposed for SCG, including HRV (heart rate variability) analysis. Our aim is to determine location of AO points of SCG to achieve heart rate (HR) changes in time. Proposed algorithm consists of calculating total acceleration value, signal preprocessing, peak finding, computing time between consecutive AO peaks and converting to heart rate. Algorithm performance was measured as true positive (TP), false positive (FP), false negative (FN) rates, sensitivity (Se) and positive predictive value (PPV) on 833 beats collected from 4 subjects. We achieved average Se = 0.868 and PPV = 0.737 and in the best case Se = 0.995 and PPV = 0.974. The obtained results are encouraging and indicate the possibility of measuring heart rate beat-to-beat accurately in rest conditions.

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#164581Data dodania: 4.2.2026
Heart beat detection from smartphone SCG signals: comparison with previous study on HR estimation / Szymon Sieciński, Paweł Kostka // W: Innovations in biomedical engineering : [Proceedings of 15th International Scientific Conference Innovations in Biomedical Engineering : October 18–20, 2018, Katowice, Poland] / eds. Ewaryst Tkacz, [et al.]. — Cham : Springer Nature Switzerland, cop. 2019. — ( Advances in Intelligent Systems and Computing ; ISSN  2194-5357 ; vol. 925 ). — ISBN: 978-3-030-15471-4; e-ISBN: 978-3-030-15472-1. — S. 123–130. — Bibliogr., Abstr. — Publikacja dostępna online od: 2019-08-15. — Sz. Sieciński - afiliacja: Silesian University of Technology, Zabrze
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#164589Data dodania: 4.2.2026
Influence of gravitational offset removal on heart beat detection performance from Android smartphone seismocardiograms / Szymon Sieciński, Paweł Kostka // W: Information Technology in Biomedicine : 6th international conference, ITIB'2018 : Kamień Śląski, Poland, June 18–20, 2018 : proceedings / eds. Ewa Pietka, [et al.]. — Cham: Springer International Publishing, cop. 2019. — ( Advances in Intelligent Systems and Computing ; ISSN  2194-5357 ; vol. 762 ). — ISBN: 978-3-319-91210-3; e-ISBN: 978-3-319-91211-0. — S. 337–344. — Bibliogr., Abstr. — Publikacja dostępna online od: 2018-06-06. — Sz. Sieciński - afiliacja: Silesian University of Technology, Zabrze