Quantitative Deconvolution of Human Thermal Infrared Emittance
The bioheat transfer models conventionally employed in etiology of human thermal infrared (TIR) emittance rely upon two assumptions: universal graybody emissivity and significant transmission of heat from subsurface tissue layers. In this study, a series of clinical and laboratory experiments were designed and carried out to conclusively evaluate the validity of the two assumptions. Results obtained from the objective analyses of TIR images of human facial and tibial regions demonstrated significant variations in spectral thermophysical properties at different anatomic locations on human body. The limited validity of the two assumptions signifies need for quantitative deconvolution of human TIR emittance in clinical, psychophysiological, and critical applications. A novel approach to joint inversion of the bioheat transfer model is also introduced, exploiting the deterministic temperature dependence of proton resonance frequency (PRF) in low-lipid human soft tissue for characterisation of the relationship between subsurface 3-D tissue temperature profiles and corresponding TIR emittance.
affective computing bioheat-transfer modeling clinical infrared imaging human infrared emittance skin emissivity