DEVELOPMENT OF A SOFTWARE FOR ECG DATA COMPRESSION

Abstract

ECG is a graphic record of the electrical potentials produced by the electro-mechanical activity of the heart. ECG signal and its parameters have to be detected from various time varying or. nonstationary physiological signals in a random noise background.The need for ECG data compression arises in order to extract relevant information from a plethora of cardiographic data. ECG data compression entails the reduction in the number of sample points required to generate an ECG wave without losing its information content. Data compression is required for various regions which include the economic utilization of storage space for ECG data bases e and the transmission of digitized ECGs to an ECG processing and recording establishment via telephone. There are various techniques of data compression which are applied in different Cilnical situations. In this study three methods have been used. In the 'Modified AZTEC with variable threshold' the data are compressed and stored as a line.`L he average of a particular set of data show the magnitude of line while no. of data in a set represent length of the line. In 'DPCM prediction and entropy encoding' Method. error between actual sample and predicted sample is transmitted irrespect of actual sample itself. Huffman encoding is used. In Method of `Fourier descriptors'1Fast Fourier transform (FFT) and inverse fast fourier transform (IFT) has been applied. This method is resistance to noise. The results show that the Fourier Descriptor Method yields the greatest advantage in a ctin-ical situation where the ECG wave is not deviating significantly from its initial characteristics. The prediction and encoding method also give good result, Whereas the modified AZTEC does not give good result.