From Experimental Investigations with Laser Bio-Photometry to Statistical Models Applied for the Normal and Pathological Tissue

Abstract

The aim of this paper is to implement a mathematical predictor algorithm to estimate the health-state evolution versus some measurable index. A relatively new medical tool was used for patients monitoring: the laser close infrared spectrum (850nm) for in vivo interaction with the human tissues. As a main statistic variable was considered the average reflection coefficient, ARC. The determined ARC coefficient in the intact tissues is an index of the health-state, having a range between 55,7 to 68 mW + 2,1 mW, being very stable in time. The determined average reflection coefficient in the pathologically modified tissues constantly decreases from 58 up to 42 mW + 3,4 mW and varies in time according to the evolution of the pathological process. However, the overlap for the ARC ranges occurs among diseases that induce uncertain diagnosis. Therefore a statistical algorithm is favorable. The laser bio-photometry provides the experimental tables that are processed to compute the statistical parameters and to establish a statistic variable. The developed Evaluation function, E, allows the pathological processes finding, besides to the evaluation and monitoring of their evolution.