Non-contact measurement of physiological parameters, like pulse rate variability (PRV), has numerous applications in medicine and affective computing. PRV is an informative measure of autonomic nervous system activity. Spectral estimation from unevenly sampled, non-stationary data is integral to pulse rate variability frequency-domain analysis. We present the first comparison of results of PRV computation using the Lomb-Scargle method and Bayesian Spectral Estimation. The Lomb-Scargle method performs well, even in the presence of missing beats. However, the Bayesian Spectral Estimation method has advantages when tracking changes in amplitude and frequency. We illustrate these characteristics with results from synthetic data and real non-contact imaging photoplethysmography measurements.

Download full-text PDF

Source
http://dx.doi.org/10.1109/EMBC.2018.8512420DOI Listing

Publication Analysis

Top Keywords

spectral estimation
16
pulse rate
12
rate variability
12
lomb-scargle method
8
bayesian spectral
8
spectral
4
estimation methods
4
methods evaluating
4
evaluating ippg
4
ippg pulse
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!