On the chaotic nature of biological signals using nonlinear data analysis methodology

Abstract

In this study, we analyze the characteristic of biological signals using nonlinear data analysis methodology. Biological signals are not linear so to get a more accurate portrait of nonlinear signals, we must analyze them with nonlinear analysis methods. The nonlinear analysis method is emerging as relatively new and rapidly growing in biomedical field. One of the most useful techniques in nonlinear data analysis is the concept of Lyapunov exponent. As we may know, Lyapunov exponent is often used to define whether a dynamical system is chaotic or not. If the system exhibits at least one positive Lyapunov exponent and is purely deterministic, then it is chaotic. In this work, we measure the finger pulse signal for twenty minutes in two different situations. Then, we analyze the finger pulse signal using nonlinear data analysis method. We extract and evaluate Lyapunov exponent parameters from the finger pulse signal. We finally find the positive value of Lyapunov exponent and confirm the existence of chaotic nature in biological systems.