Bio-Inspired Nonlinear Oscillator Based on ECG and EEG Bio-Emulator Signals

Abstract

Nonlinear signals have been extensively utilized in encryption and decryption applications, representing a significant area of research within chaos theory. Such signals are highly sensitive to initial conditions and system parameters; consequently, even minor variations in the underlying mathematical formulation can produce substantially different nonlinear waveforms, a phenomenon commonly referred to as the butterfly effect. Electrocardiographic (ECG) signals, which reflect the fundamental physiological activity of the human heart, and electroencephalographic (EEG) signals, which are closely related to cerebral activity and influenced by blood flow dynamics, also exhibit nonlinear characteristics due to their intrinsic nonlinear and complex structures. In this study, a novel bio-inspired nonlinear oscillator with two outputs is proposed, incorporating ECG and EEG signals. Unlike classical nonlinear oscillators reported in the literature, such as the Chua, Sprott, and Lorenz systems, which are primarily based on idealized mathematical models, the proposed oscillator integrates physiological signal dynamics. This integration enables the generation of distinct nonlinear signals corresponding to different heart rhythms for use in encryption and decryption processes, thereby enhancing the robustness and security of data transmission.