Diagnosis of cardiac deceases by Using ECG signal compression for cffective communication

An ECG contains diagnostic information related to cardiac activity. A method to compress diagnostic information without losing data is required to store and transmit them efficiently on a wireless personal area network (WPAN). As electrocardiogram (ECG) signals are generally sampled with a frequency of over 200 Hz, an ECG signal compression method for communications on WPAN, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, and T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes were extracted with the proposed method, which uses local extrema of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes were added according to the iterative vertex selection method. It was concluded that the vertexes selected by the proposed method preserved all feature points of the ECG signals. In addition, it was more efficient than the amplitude zone time epoch coding method.