Abstract
Seismocardiogram (SCG) is the measure of the minute vibrations produced by the beating heart. We previously demonstrated that SCG, ECG and respiration could be recorded over the 24h during spontaneous behavior by a smart garment, the MagIC-SCG system. In the present case study we explored the feasibility of a beat-to-beat estimation of two indices of heart contractility, the Left Ventricular Ejection Time (LVET) and the electromechanical systole (QS2) from SCG and ECG recordings obtained by the MagIC-SCG device in one subject. We considered data collected during outdoor spontaneous behavior (while sitting in the metro and in the office) and in a laboratory setting (in supine and sitting posture, and during recovery after 100W and 140W cycling). LVET was estimated from SCG as the time interval between the opening and closure of the aortic valve, QS2 as the time interval between the Q wave of the ECG and the closure of the aortic valve. In every condition, LVET and QS2 could be estimated on a beat-to-beat basis from the SCG collected by the smart garment. LVET and QS2 are characterized by important beat-to-beat fluctuations, with standard deviations in the same order of magnitude of RR Interval. In all settings, spectral profiles are different for LVET, QS2 and RR Interval. This suggests that the biological mechanisms impinging on the heart exert a differentiated influence on the variability of each of these three indices.
Original language | English |
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Title of host publication | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
Pages | 7017-7020 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan Duration: Jul 3 2013 → Jul 7 2013 |
Other
Other | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 |
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Country/Territory | Japan |
City | Osaka |
Period | 7/3/13 → 7/7/13 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Biomedical Engineering
- Health Informatics