AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm

Abstract

Abstract The proliferation of tele‐healthcare services at an accelerated rate raises concerns over the management,security and privacy of the patient's confidential data (an individual's personal details and medical biography) during its transmission and storage. To resolve these issues, amalgamation of three fundamental techniques of remote healthcare systems, that is, signal compression, data hiding and encryption, are proposed. The proposed approach applies the recently developed adaptive Fourier decomposition (AFD) technique to decompose the electrocardiogram signal in terms of adaptively selected basis functions from the orthogonal rational function that performs a high fidelity compression. Later, chaotic map‐based steganography and encryption are proposed on the AFD coefficients to secure the confidential information and the signal itself. The performance of the three processes is evaluated in terms of distortion (both statistical and clinical), compression [(compression ratio (CR) and quality score], steganography [embedding capacity (EC), bit error rate], and encryption (sensitivity, predictivity, correlation coefficient). By implementing on 48 records of Massachusetts Institute of Technology‐Beth Israel Hospital arrhythmia database and varying N from 15 to 120, the proposed work achieves average CR, EC, and percentage residual difference of 62.39–11.79, 7 × 10−3–6 × 10−2 and 3.77–0.32, respectively, with a highly linear relationship among them. The results explicitly display the competency of the proposed technique in comparison with the existing techniques that are available currently.

Keywords

• data compression
• data encapsulation
• electrocardiography
• health care
• medical signal processing
• rational functions