Non-contact estimation of heart rate and oxygen saturation using ambient light

Abstract

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.

Keywords: (100.2960) Image analysis; (100.7410) Wavelets; (170.3880) Medical and biological imaging.

Fig. 1

Flow diagram of the proposed method.

Fig. 2

Decomposition with 1D DT-CWT to obtain approximation (A) and detail (D) coefficients at different levels. DT-CWT uses two Real DWT trees to implement its real (tree a) and imaginary (tree b) parts. L represents lowpass filters and H represents highpass filters.

Fig. 3

Face (a) and skin detection (b).

Fig. 4

Raw green signal (top) and processed signal (bottom). In order to improve the visibility of the variations the mean value of the raw green signal is subtracted.

Fig. 5

The lines represent the mean and 95% limits of agreement.

Fig. 6

Bland Altman plot for experiments with intensive care unit patients.

Fig. 7

Reference oxygen saturation vs estimated ratios.

Fig. 8

Oxygen saturation experiments with healthy volunteers.

Fig. 9

Oxygen saturation experiments with PICU patients.