Wearable seismocardiography for the beat-to-beat assessment of cardiac intervals during sleep
Seismocardiogram (SCG) can be detected during sleep by a textile-based wearable system. This pilot study preliminarily explores the feasibility of a beat-to-beat estimation of cardiac mechanical features (RR interval, RRI, Pre-Ejection Period, PEP, Isovolumic Contraction Time, ICT, Left Ventricular...
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          | Published in | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2014; pp. 6089 - 6091 | 
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| Main Authors | , , , , , , , | 
| Format | Conference Proceeding Journal Article | 
| Language | English | 
| Published | 
        United States
          IEEE
    
        2014
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1094-687X 1557-170X  | 
| DOI | 10.1109/EMBC.2014.6945018 | 
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| Summary: | Seismocardiogram (SCG) can be detected during sleep by a textile-based wearable system. This pilot study preliminarily explores the feasibility of a beat-to-beat estimation of cardiac mechanical features (RR interval, RRI, Pre-Ejection Period, PEP, Isovolumic Contraction Time, ICT, Left Ventricular Ejection Time, LVET, Isovolumic Relaxation Time, IRT) from the joint ECG and SCG assessment during sleep. The analysis of two 30-min sleep data segments from one healthy subject, indicated that 1) respiration largely influence the dynamics of most of the parameters; 2) variability of cardiac intervals is only marginally influenced by the RRI variability; 3) appreciable spectral power at frequencies <;0.1 is only observed in the RRI spectrum and not in the spectra of the other indexes; 4) IRT has a broadband variability, that is clearly different from the dynamics of the other indexes. These findings represent the very first description of the beat-to-beat variability of cardiac mechanical indexes. Further investigations on a larger population are in progress to confirm the present results. | 
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| ISSN: | 1094-687X 1557-170X  | 
| DOI: | 10.1109/EMBC.2014.6945018 |