A novel method based on two cameras for accurate estimation of arterial oxygen saturation

BACKGROUND: Photoplethysmographic imaging (PPGi) that is based on camera allows acquiring photoplethysmogram and measuring physiological parameters such as pulse rate, respiration rate and perfusion level. It has also shown potential for estimation of arterial oxygen saturation (SaO(2)). However, there are some technical limitations such as optical shunting, different camera sensitivity to different light spectra, different AC-to-DC ratios (the peak-to-peak amplitude to baseline ratio) of the PPGi signal for different portions of the sensor surface area, the low sampling rate and the inconsistency of contact force between the fingertip and camera lens. METHODS: In this paper, we take full account of the above-mentioned design challenges and present an accurate SaO(2) estimation method based on two cameras. The hardware system we used consisted of an FPGA development board (XC6SLX150T-3FGG676 from Xilinx), with connected to it two commercial cameras and an SD card. The two cameras were placed back to back, one camera acquired PPGi signal from the right index fingertip under 660 nm light illumination while the other camera acquired PPGi signal from the thumb fingertip using an 800 nm light illumination. The both PPGi signals were captured simultaneously, recorded in a text file on the SD card and processed offline using MATLAB®. The calculation of SaO(2) was based on the principle of pulse oximetry. The AC-to-DC ratio was acquired by the ratio of powers of AC and DC components of the PPGi signal in the time–frequency domain using the smoothed pseudo Wigner–Ville distribution. The calibration curve required for SaO(2) measurement was obtained by linear regression analysis. RESULTS: The results of our estimation method from 12 subjects showed a high correlation and accuracy with those of conventional pulse oximetry for the range from 90 to 100%. CONCLUSIONS: Our method is suitable for mobile applications implemented in smartphones, which could allow SaO(2) measurement in a pervasive environment.