Two-Dimensional Processing of Multichannel ECG Signals for Efficient Exploitation of Inter and Intra-Channel Correlation

Electrocardiogram signals acquired through different channels from the body surface are termed as Multichannel ECG (MECG) signals. They are obtained by projecting the same heart potential in different directions and hence share common information with each other. In this work a new two-dimensional (2-D) approach is proposed for MECG signal processing in order to exploit the correlated structure between the channels efficiently. Different channel data are arranged in a 2-D form giving them an image type arrangement and then 2-D discrete cosine transform (DCT) is applied in a blockwise manner over the whole data. The 2-D processing of MECG data ensures the efficient utilization of both inter-lead correlation (across the columns) and intra-lead correlation (across the rows). Since neighboring ECG samples across the channels are more correlated due to slowly varying nature of ECGs, blockwise processing of MECG data gives an effective way to exploit this. To quantify the performance of the proposed algorithm, it is evaluated on a compression platform. Each block after DCT transformation is undergone through a uniform scale zero-zone quantizer and entropy encoder to get the compressed bit streams. Performance metrics used are the compression ratio (CR) , and widely used distortion measure, root mean square difference (PRD).