
Non-contact estimation of heart rate and oxygen saturation using ambient light
Author(s) -
Ufuk Bal
Publication year - 2014
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.6.000086
Subject(s) - rgb color model , artificial intelligence , oxygen saturation , computer vision , color space , computer science , heart rate , photoplethysmogram , wavelet , pattern recognition (psychology) , biomedical engineering , medicine , oxygen , chemistry , organic chemistry , filter (signal processing) , blood pressure , image (mathematics) , radiology
We propose a robust method for automated computation of heart rate (HR) from digital color video recordings of the human face. In order to extract photoplethysmographic signals, two orthogonal vectors of RGB color space are used. We used a dual tree complex wavelet transform based denoising algorithm to reduce artifacts (e.g. artificial lighting, movement, etc.). Most of the previous work on skin color based HR estimation performed experiments with healthy volunteers and focused to solve motion artifacts. In addition to healthy volunteers we performed experiments with child patients in pediatric intensive care units. In order to investigate the possible factors that affect the non-contact HR monitoring in a clinical environment, we studied the relation between hemoglobin levels and HR estimation errors. Low hemoglobin causes underestimation of HR. Nevertheless, we conclude that our method can provide acceptable accuracy to estimate mean HR of patients in a clinical environment, where the measurements can be performed remotely. In addition to mean heart rate estimation, we performed experiments to estimate oxygen saturation. We observed strong correlations between our SpO2 estimations and the commercial oximeter readings.