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A camera-based imaging system was previously developed for mapping venous blood oxygenation in human skin. However, several limitations were realized in later applications, which could lead to either significant bias in the estimated oxygen saturation value or poor spatial resolution in the map of the oxygen saturation. To overcome these issues, an upgraded system was developed using improved modeling and image processing algorithms. In the modeling, Monte Carlo (MC) simulation was used to verify the effectiveness of the ratio-to-ratio method for semi-infinite and two-layer skin models, and then the relationship between the venous oxygen saturation and the ratio-to-ratio was determined. The improved image processing algorithms included surface curvature correction and motion compensation. The curvature correction is necessary when the imaged skin surface is uneven. The motion compensation is critical for the imaging system because surface motion is inevitable when the venous volume alteration is induced by cuff inflation. In addition to the modeling and image processing algorithms in the upgraded system, a ring light guide was used to achieve perpendicular and uniform incidence of light. Cross-polarization detection was also adopted to suppress surface specular reflection. The upgraded system was applied to mapping of venous oxygen saturation in the palm, opisthenar and forearm of human subjects. The spatial resolution of the oxygenation map achieved is much better than that of the original system. In addition, the mean values of the venous oxygen saturation for the three locations were verified with a commercial near-infrared spectroscopy system and were consistent with previously published data.

A method of non-contact mapping of venous oxygen saturation (SvO 2 ) is presented. A CCD camera is used to image skin tissue illuminated alternately by a red (660 nm) and an infrared (800 nm) LED light source. Low cuff pressures of 30–40 mmHg are applied to induce a venous blood volume change with negligible change in the arterial blood volume. A hybrid model combining the Beer–Lambert law and the light diffusion model is developed and used to convert the change in the light intensity to the change in skin tissue absorption coefficient. A simulation study incorporating the full light diffusion model is used to verify the hybrid model and to correct a calculation bias. SvO 2 in the fingers, palm, and forearm for five volunteers are presented and compared with results in the published literature. Two-dimensional maps of venous oxygen saturation are given for the three anatomical regions.