Szczegóły publikacji
Opis bibliograficzny
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
Autorzy (2)
- Sieciński Szymon
- Kostka Paweł S.
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164581 |
|---|---|
| Data dodania do BaDAP | 2026-02-04 |
| DOI | 10.1007/978-3-030-15472-1_14 |
| Rok publikacji | 2019 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Advances in Intelligent Systems and Computing |
Abstract
Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular activity as vibrations transmitted to the chest wall. Mobile devices offer the possibility to monitor health parameters thanks to embedded sensors. Various applications have been proposed for SCG, including heart rate calculation. Our aim is to detect heart beat on seismocardiograms using improved algorithm and compare its performance with results obtained in previous study. Algorithm proposed in this study consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was measured as sensitivity (Se) and positive predictive value (PPV) of beat detection on 4 signals acquired from 4 subjects. We achieved average Se= 0.994 and PPV= 0.966 and in the best case Se= 0.995 and PPV= 0.970. Results prove major improvement of beat detection from smartphone seismocardiograms since the previous study.
