Embedding and retrieving patient's identification and compression of ECG signal

Abstract

In this paper, the authors propose a new ECG compression algorithm which embeds patient's identification inside the ECG data. The compressed file contains only ASCII characters. The proposed scheme also allows the decompression technique where the original ECG waveform can be exactly reconstructed and retrieve patient's identification from the ECG signal. The whole module has been applied to various ECG data of all the 12 leads taken from PTB diagnostic database (PTB-DB) of physioNet (www.physionet.org) and gives a highly compressed result that can be stored using far less digital space without distorting important ECG characteristics which are essential for proper medical diagnosis. Moreover, the compression, embedding, decompression and retrieving of data are achieved in a series of sequential, simplistic logical processes that can be easily executed. It is observed that the proposed algorithm gives a high compression ratio (CR=7.3593, an excellent Quality Score (QS=1362) and very low difference between original and reconstructed ECG signal (PRD=O.0054).