A real-time direct method of measurement of AC skin impedance based on an artificial neural network approach

A fast direct method of measurement AC skin impedance based on an artificial neural network is presented in this paper. Conventional methods for determining AC skin impedance with a multi-frequency process resulting from off-line estimation are accurate but lack real time convenience. In this paper, a novel direct method which uses instantaneous input data of voltage and current as a function of time is desired. These data are subsequently processed with a discrete Fourier transform and an artificial neural network computation yielding a set of resistance and capacitance values of the components of the skin equivalent circuit. This technique is faster than the previous methods because it uses a real-time, online measurement and computation, and requires only one high frequency input signal