We tested the feasibility of measuring fat thickness using a miniaturized chip LED sensor module, testing 12 healthy female subjects. The module consisted of a single detector and four sources at four different source-detector distances (SD). A segmental curve-fitting procedure was applied, using an empirical algorithm obtained by Monte-Carlo simulation, and fat thicknesses were estimated. These thicknesses were compared to computed-tomography (CT) results; the correlation coefficient between CT and optical measurements was 0.932 for bicep sites. The mean percentage error between the two measurements was 13.12%. We conclude that fat thickness can be efficiently measured using the simple sensor module.

We tested the feasibility of noninvasive fat thickness measurements by using a diffuse optical method with variable source-detector pairs. A light source module composed of 770 nm low-power chip LEDs and a photodetector were used in this study. The tissue phantoms are composed of a fat and a muscle layer made with gels with appropriate absorption/scattering coefficients. The fat thickness was varied from several to 30 mm. Based on this preliminary study, it is concluded that the noninvasive fat thickness measurement is possible with proper curve fitting procedure.

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We measured the fat thickness noninvasively by using a diffuse optical method for tissuesimulating phantoms and human tissues. A light source module composed of 770 nm low-power chip LEDs and a photo-detector were used in this study. The optical tissue phantoms were composed of a fat and a muscle layer made with gels with appropriate absorption/scattering coefficients. The fat thickness was varied from several to 30 mm. After a proper calibration procedure, we used this system to conduct human studies. Based on this preliminary study, noninvasive fat thickness measurements are possible with a simple curve-fitting procedure.