Prediction of Heat Generation and Tissue Thermal Diffusivity During Laser Hair Removal

Abstract

During laser hair removal, monitoring the temperature field of hair follicles is needed to ensure patient safety. To determine this temperature field at any time, parameters such as heat energy and thermal diffusivity of tissue should be obtained. The aim of this paper is to apply numerical optimization schemes for the estimation of these parameters during laser hair removal. Levenberg-Marquardt and Gauss-Newton methods were applied to estimate the parameters. Once these parameters are found, the temperature field at any time can easily be determined by numerically solving the 2D heat diffusion equation. The estimation methods were tested with random initial values, larger and smaller than the target true value. Results showed that these algorithms are accurate to estimate the target unknown parameters. The temperature distribution obtained by using these predicted parameters could help dermatologists during hair removal procedures. Moreover, the prediction of required heat energy could aid clinicians to select a laser source with appropriate wavelength and pulse width.