ECG DATA COMPRESSION USING SIGNAL TRANSFORMATION TECHNIQUES

Abstract

Electrocardiogram (ECG) is a graphical representation of the electromechanical activity of the cardiac system. It provides fast and reliable information to the expert cardiologist with respect to the functional aspects of the heart. The ECG is recorded in many situations, viz., to know the state of a patient under medical diagnosis and treatment, to keep a watch on the state of patients in the intensive cardiac care units, to know the response of the patient under medical treatment, to know the condition of cardiac system under stressed conditions, and to monitor the state of the ambulatory patients. The number of cardiac patients are increasing at an alarming rate and it is not possible for the existing number of cardiologists to take care of all the cardiac patients under all the conditions. By the ECG data acquisition and preprocessing large amount of data is produced. For the purpose of analysis and the interpretation by the cardiologist at the remote location and at the later stage of time, compression is required to save this large amount of data and it is also very necessary and useful to save the bandwidth of the transmitting channel while sending this data to remote location elsewhere. The work has been carried out in this thesis by using of four Frequency Transformation techniques viz. FFT, DST, DCT and DCT2 for the compression of Standard ECG Data and for the compilation of Performance Parameters like Compression Ratio and the Percentage Root Mean Square Difference. With the aim of improving the compression parameters i.e. having high value of Compression Ration(CR) while have the low value of Percentage Root Mean Square Difference(PRD) for the compressed signal with the condition that the reconstructed signal does not loose the clinically important parameters for the diagnosis purpose of ECG. It is found that results are better with DCT in terms of Percentage Root Mean Square Difference (PRD) and DCT2 in terms of Compression Ratio (CR). The Matlab program developed for Record no. 100 of standard MIT-BIH Arrhythmia database gives the Compression Ratio(CR) of as high as 95.7700 while having the Percentage Root Mean Square Difference(PRD) as low as 0.9382. The present study has also been used to compare the results of the program developed in the other existing techniques of data compression.