A Chaos-based Visual Encryption Mechanism in Integrated ECG/EEG Medical Signals

In this paper, we have developed a chaos-based visual encryption mechanism which can be applied in the integrated electrocardiogram (ECG)/electroencephalography (EEG) medical signals. A main idea for using chaos sequence is to increase the un-predication compared with other kind of random sequences. Thus, we based on a values mapping of ID chaotic scrambler and a permutation scheme to achieve integrated ECG/EEG visual encryption. A way to realize the visual encryption mechanism is to scramble the signal values of the input integrated ECG/EEG signal by multiplying ID chaotic signal to randomize integrated ECG/EEG signal values, and then a chaotic address scanning order encryption is applied to the randomize reference values. Simulation results show when correct deciphering parameters are put in, the signal will be completely recovered, and the percent root-mean-square difference (PRD) values are 4.69 times 10^-15 % and 4.33 times 10^-15 % for ECG and EEG medical signals, respectively. As long as there is an input parameter error, for example, with 0.00000001% initial point error, it could make chaotic array, and the ECG and EEG medical signals will not be recovered back.