Szczegóły publikacji
Opis bibliograficzny
Heart rate variability analysis on electrocardiograms, seismocardiograms and gyrocardiograms of healthy volunteers and patients with valvular heart diseases / Szymon Sieciński, Ewaryst Janusz Tkacz, Paweł Stanisław Kostka // Sensors [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1424-8220 . — 2023 — vol. 23 iss. 4 art. no. 2152, s. 1–17. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 14–17, Abstr. — Publikacja dostępna online od: 2023-02-14. — Sz. Sieciński – afiliacja: Silesian University of Technology, Zabrze
Autorzy (3)
- Sieciński Szymon
- Tkacz Ewaryst
- Kostka Paweł S.
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164550 |
|---|---|
| Data dodania do BaDAP | 2026-01-27 |
| Tekst źródłowy | URL |
| DOI | 10.3390/s23042152 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Sensors |
Abstract
Heart rate variability (HRV) is the physiological variation in the intervals between consecutive heartbeats that reflects the activity of the autonomic nervous system. This parameter is traditionally evaluated based on electrocardiograms (ECG signals). Seismocardiography (SCG) and/or gyrocardiography (GCG) are used to monitor cardiac mechanical activity; therefore, they may be used in HRV analysis and the evaluation of valvular heart diseases (VHDs) simultaneously. The purpose of this study was to compare the time domain, frequency domain and nonlinear HRV indices obtained from electrocardiograms, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) in healthy volunteers and patients with valvular heart diseases. An analysis of the time domain, frequency domain and nonlinear heart rate variability was conducted on electrocardiograms and gyrocardiograms registered from 29 healthy male volunteers and 30 patients with valvular heart diseases admitted to the Columbia University Medical Center (New York City, NY, USA). The results of the HRV analysis show a strong linear correlation with the HRV indices calculated from the ECG, SCG and GCG signals and prove the feasibility and reliability of HRV analysis despite the influence of VHDs on the SCG and GCG waveforms.
