Abstract
Heart rate variability (HRV) is a physiological variation of intervals between consecutive heart beats that reflects the activity of the autonomic nervous system. This parameter is traditionally evaluated on the basis of electrocardiograms (ECG signals). Because seismocardiography (SCG) registers cardiac mechanical activity, it may be used in HRV analysis and the evaluation of valvular heart diseases (VHDs) simultaneously. In our study, our objective was to compare HRV indices in the time and frequency domain obtained from seismocardiograms (SCG signals) in healthy volunteers and patients with valvular heart diseases. The results of the HRV analysis indicate that there are significant differences between the HRV indices obtained from the seismocardiograms in healthy volunteers and patients with VHD, This shows the feasibility and validity of HRV analysis based on seismocardiograms in healthy volunteers and patients with VHD.
| Original language | English |
|---|---|
| Title of host publication | 2022 Computing in Cardiology, CinC 2022 |
| Publisher | IEEE Computer Society |
| ISBN (Electronic) | 9798350300970 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 2022 Computing in Cardiology, CinC 2022 - Tampere, Finland Duration: 4 Sept 2022 → 7 Sept 2022 |
Publication series
| Name | Computing in Cardiology |
|---|---|
| Volume | 49 |
| ISSN (Print) | 2325-8861 |
| ISSN (Electronic) | 2325-887X |
Conference
| Conference | 2022 Computing in Cardiology, CinC 2022 |
|---|---|
| Country/Territory | Finland |
| City | Tampere |
| Period | 4/09/22 → 7/09/22 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- General Computer Science
- Cardiology and Cardiovascular Medicine
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