| Title |
Robust pulse rate variability analysis from reflection and transmission photoplethysmographic signals / |
| Authors |
Peralta, Elena ; Lázaro, Jesús ; Gil, Eduardo ; Bailón, Raquel ; Marozas, Vaidotas |
| DOI |
10.22489/CinC.2017.205-286 |
| ISBN |
9781538645550 |
| eISBN |
9781538666302 |
| Full Text |
|
| Is Part of |
Computing in cardiology (CinC): September 24-27, 2017, Rennes, France.. Piscataway, NJ : IEEE, 2017. vol. 44, p. 1-4.. eISSN 2325-887X. ISBN 9781538645550. eISBN 9781538666302 |
| Keywords [eng] |
forehead ; fingers ; heart rate variability ; electrocardiography ; frequency-domain analysis ; Microsoft Windows ; reflection |
| Abstract [eng] |
Finger and forehead pulse photoplethysmographic (PPG) signals are compared as a surrogate for the electrocardiogram (ECG) in Heart Rate Variability (HRV) analysis during tilt table test. PPG signals are usually corrupted by motion artifacts. In this work, robust algorithms for pulse rate estimation have been applied. Classical time and frequency domain indices in the low frequency (LF) and high frequency (HF) bands have been estimated from pulse rate variability (PRV) derived from both PPG signals. These PRV indices have been compared with those obtained from the reference HRV derived from the ECG. The relative error (median/interquartile range) between PRV and HRV indices are comparable during early and later supine position in the forehead and finger signals (5.27/7.95% vs 5.88/7.87% in the LF band, 6.84/13.23% vs 7.08/12.50% in the HF band, 2.86/4.58% and 3.17/4.43% in the SDSD index during early supine position in the forehead and finger, respectively). The relative error indices estimated during the tilt were higher than during supine position, with slightly better performance in the forehead than in the finger (9.60/11.68% vs 5.28/18.64% in the LF band, 23.35/37.07% vs 35.94/81.95% in the HF band, 5.97/18.82% vs 12.71/49.03% in the SDSD index, during tilt in the forehead and finger, respectively). These results suggest that recordings on the forehead seem to provide better performance for the PRV analysis in non-stationarity environments. |
| Published |
Piscataway, NJ : IEEE, 2017 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2017 |
| CC license |
|
