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

Di Rienzo, M., Vaini, E., Castiglioni, P., Lombardi, P., Parati, G., Lombardi, C., et al. (2014). Wearable seismocardiography for the beat-to-beat assessment of cardiac intervals during sleep. In 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Chicago, IL, USA, 26-30 Aug 2014 (pp. 6089-6091). Piscataway, NJ : IEEE [10.1109/EMBC.2014.6945018].

Wearable seismocardiography for the beat-to-beat assessment of cardiac intervals during sleep

Parati, G;Lombardi, C;
2014

Abstract

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
Capitolo o saggio
Seismocardiography, cardiac intervals
English
36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Chicago, IL, USA, 26-30 Aug 2014
2014
978-1-4244-7929-0
2014
IEEE
6089
6091
Di Rienzo, M., Vaini, E., Castiglioni, P., Lombardi, P., Parati, G., Lombardi, C., et al. (2014). Wearable seismocardiography for the beat-to-beat assessment of cardiac intervals during sleep. In 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Chicago, IL, USA, 26-30 Aug 2014 (pp. 6089-6091). Piscataway, NJ : IEEE [10.1109/EMBC.2014.6945018].
reserved
File in questo prodotto:
File Dimensione Formato  
Wearable seismocardiography-Conf Proc IEEE Eng Med Biol Soc 2014.pdf

Solo gestori archivio

Dimensione 689.4 kB
Formato Adobe PDF
689.4 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/69787
Citazioni
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 0
Social impact