ECG Signal Compression Techniques for Data Storage and Qualitative Analysis

ECG (electrocardiogram) is a test that measures the electrical activity of the heart. The information obtained from an electrocardiogram can be used to discover different types of heart disease. It may be useful to see how well the patient is r esponding to treatment. An ECG trace is a digitized version of a continuous signal. To reduce the loss in ECG signal we have used some efficient techniques in our project. Various techniques can be used for compression like the Fast Fourier Transform (FFT), Discrete Cos ine Transform (DCT), Discrete Wavelet Transform (DWT) etc. ECG signal being used in a wide variety of biomedical applications requires accurate results, less power requirements, faster results and low cost maintenance. Therefore compression plays a very import ant role in acquiring these purposes without losing the original information. In general, most of the introduced ECG compression techniques have inaccuracy and random behavior of error. Hence a new technique was proposed called as Discrete Wavelet Transform (DWT). Also from the results and computations that we have performed in our project we come to a conclusion that DWT is a better compression technique than DCT since it has better accuracy and also it correlates very well with the subjective tests. Index terms-Accuracy, compression, Discrete Cosine Transform (DCT), Discrete Wavelet Transforms (DWT), fast, percent root mean square difference (PRD) and without losing original information