Feature analysis for the reversible watermarked electrooculography signal using Low distortion Prediction-error Expansion

Abstract

At present, most of the hospitals and diagnostic centers globally, have started using wireless media for exchange of biomedical information (Electronic Patient Report or hospital logo) for mutual availability of therapeutic case studies. Exchange of information amongst various hospital and medical centers require high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information as multimedia content. Electrooculography (EOG) is a medical test that records the movements and position of the eyes. In this present work, Low distortion Prediction-error Expansion technique is used for watermark insertion and extraction in an EOG signal without devalorizing its diagnostic parameters. It can be seen that in this approach the correlation value of the original watermark and the extracted watermark is quite high. The Signal-to-Noise ratio (SNR) between the original EOG signal and the recovered EOG signal markedly improves which claims the robustness of the method. In the second part of the present work different features of the original EOG signal, watermarked EOG signal and recovered EOG signal are analysed.