Unsupervised Heart Rate Variability Estimation from Ballistocardiograms
نویسندگان
چکیده
We propose and evaluate an unsupervised method for the estimation of heart rate variability (HRV) indices from ballistocardiograms (BCGs) recorded by a bed-mounted, electromechanical film (EMFi) sensor during sleep. After estimating the beat-to-beat intervals from the BCGs, short-term timeand frequency-domain HRV indices are computed and compared to an ECG reference. We evaluated signals recorded overnight from 8 subjects (approx. 212.000 heart beats). Our results show a good correlation (> 0.9) between BCGand ECGderived HRV indices and suggest that unsupervised longterm HRV monitoring using BCGs is indeed feasible.
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تاریخ انتشار 2012