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.