Research On ECG Signal Compression Based On Wavelet Coefficient Prediction

Cardiovascular disease is one of the main diseases threatening people’s life, and electro cardiogram(as ECG signal) can reflect the human heart to provide detailed diagnostic information on the surface activity of heart disease patients. Therefore, the patient clinical ECG examination is of important significance to the diagnosis of heart diseases. With the popularization and application of computer technology, in order to analysis more accurate data for clinical doctors to provide, for multi lead ECG measuring instrument is more and more widely used, but also on the clinical ECG signal collected by the sampling frequency, sampling accuracy requirements are higher and more accurate and requires a longer sampling time. It would require more storage space and faster transmission speed, and further reduce the ECG data storage space, plays an important role in the processing and transmission of ECG data.Because the ECG data is an important basis for the diagnosis of the doctor to the patient, according to ECG signal compression in the pursuit of maximum compression ratio and reduce the distortion of the ECG data is also very important. Therefore, the lossless compression of ECG signal diagnosis has become an important research direction of the current in the biomedical engineering. High compression ratio and low distortion two considerations are based on prediction of ECG signal discrete wavelet coefficients algorithm. The ECG signal is the heart of fluctuation, every heart contraction and relaxation is a cardiac cycle, so each heartbeat signal has a high correlation and periodic. According to the characteristics:first, the ECG signal by using continuous wavelet transform modulus maxima method to detect R wave position was accurate for each cardiac cycle in ECG signals; then six level discrete wavelet transform of ECG signal; according to the characteristics of discrete wavelet coefficients after transformation, with dead zone quantizer the reasonable quantification; then an adaptive template for optimal linear prediction of quantized coefficients; finally the error coding by adaptive arithmetic coder.This paper first introduces the research status at home and abroad in recent decades ECG signal compression,and then in-depth study, based on the principle of wavelet transform and adaptive Context model is adaptive digital multidimensional time series prediction signal is applied to image lossless coding, and then analyzed the structure characteristics of ECG cycle, signal with dead zone uniform quantizer is given the results of experiments and analysis, the experiment scheme, experimental data from the MIT-BIH arrhythmia data base. The experimental results show that the compression effect prediction method based on ECG signal period is significantly improved.