Autonomous jerk oscillator with sine nonlinearity and logistic map for sEMG encryption

Abstract

This research discusses the dynamical behaviors of the autonomous jerk oscillator with sine nonlinearity (AJOSN) and its application to secure s-EMG (Surface ElectroMyoGraphic) data. The AJOSN has two or no-equilibrium points, and the stability of the two equilibrium points indicates that one is stable and the other is unstable. The AJOSN reveals fast-spiking and periodic bursting, relaxing and periodic oscillations, hidden chaotic attractors and coexisting attractors. The numerical analysis results are validated by the Field Programmable Gate Array (FPGA) implementation. Finally, the AJOSN’s chaotic behavior coupled with the logistic map is exploited to encrypt the s-EMG signals. The proposed encryption and decryption method consists of simultaneously encrypting the sEMG signal. The sEMG signal, once transformed into 2D as a grayscale image, undergoes first encryption based on the chaotic signal generated by the AJOSN (Autonomous jerk oscillator with sine nonlinearity) model. The encrypted signal obtained from this first part is called ‘Jerk encrypted signal.’ The second part is to encrypt the ‘Jerk Encrypted Signal’ by the chaotic logistics map. The encryption and decryption results obtained are quite encouraging and offer a great prospect.