An Integrated Approach Using Chaotic Map & Sample Value Difference Method for Electrocardiogram Steganography and OFDM Based Secured Patient Information Transmission.

This paper presents a patient's confidential data hiding scheme in electrocardiogram (ECG) signal and its subsequent wireless transmission. Patient's confidential data is embedded in ECG (called stego-ECG) using chaotic map and the sample value difference approach. The sample value difference approach effectually hides the patient's confidential data in ECG sample pairs at the predefined locations. The chaotic map generates these predefined locations through the use of selective control parameters. Subsequently, the wireless transmission of the stego-ECG is analyzed using the Orthogonal Frequency Division Multiplexing (OFDM) system in a Rayleigh fading scenario for telemedicine applications. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through the statistical and clinical performance measures. Statistical measures comprise of Percentage Root-mean-square Difference (PRD), Peak Signal to Noise Ratio (PSNR), and Kulback-Leibler Divergence (KL-Div), etc. while clinical metrics includes wavelet Energy Based Diagnostic Distortion (WEDD) and Wavelet based Weighted PRD (WWPRD). The various channel Signal-to-Noise Ratio scenarios are simulated for wireless communication of stego-ECG in OFDM system. The proposed method over all the 48 records of MIT-BIH arrhythmia database resulted in average, PRD = 0.26, PSNR = 55.49, KL-Div = 3.34 × 10-6, WEDD = 0.02, and WWPRD = 0.10 with secret data size of 21Kb. Further, a comparative analysis of proposed method and recent existing works was also performed. The results clearly, demonstrated the superiority of proposed method.

A joint application of optimal threshold based discrete cosine transform and ASCII encoding for ECG data compression with its inherent encryption.

In this paper, a joint use of the discrete cosine transform (DCT), and differential pulse code modulation (DPCM) based quantization is presented for predefined quality controlled electrocardiogram (ECG) data compression. The formulated approach exploits the energy compaction property in transformed domain. The DPCM quantization has been applied to zero-sequence grouped DCT coefficients that were optimally thresholded via Regula-Falsi method. The generated sequence is encoded using Huffman coding. This encoded series is further converted to a valid ASCII code using the standard codebook for transmission purpose. Such a coded series possesses inherent encryption capability. The proposed technique is validated on all 48 records of standard MIT-BIH database using different measures for compression and encryption. The acquisition time has been taken in accordance to that existed in literature for the fair comparison with contemporary state-of-art approaches. The chosen measures are (1) compression ratio (CR), (2) percent root mean square difference (PRD), (3) percent root mean square difference without base (PRD1), (4) percent root mean square difference normalized (PRDN), (5) root mean square (RMS) error, (6) signal to noise ratio (SNR), (7) quality score (QS), (8) entropy, (9) Entropy score (ES) and (10) correlation coefficient (r x,y ). Prominently the average values of CR, PRD and QS were equal to 18.03, 1.06, and 17.57 respectively. Similarly, the mean encryption metrics i.e. entropy, ES and r x,y were 7.9692, 0.9962 and 0.0113 respectively. The novelty in combining the approaches is well justified by the values of these metrics that are significantly higher than the comparison counterparts.