The proposed ECG compression method presents the new beat segmentation algorithm. Because this proposed compression method uses the residual difference between original ECG signal beat and the reference ECG beat, the ECG signal must be separated into each beat before doing the compression process. That is the duty of beat segmentation process. Therefore, this process is important step of the selective Mapping Technique ECG compression method. The main goal of this work is to design the beat segmentation algorithm which is the most suitable for this compression method. And this proposed beat segmentation algorithm is designed to replace the complicated operation algorithm. Consequently, this proposed beat segmentation algorithm uses only simple operation such as accumulation and shift operation. And moreover, the decision rule is not complicated as the previous method. The test results show that more than half of tested signals return higher compression ratio (CR). In addition, almost quarter of tested signals have better performance of percent root mean square difference (PRD).Therefore this is the alternative method for the best comparing selection. Keywords-ECG; compression; beat segmentationReconstruction Compression . . . Fig. 4. The new model of compression method.
The electrocardiogram compression method presented in this research processes the residual signal which is the difference between the original signal and the reference signal. The residual signal is transformed to wavelet domain and then the redundant information is eliminated in wavelet domain. The selection of mother wavelet is one of main factor to maintain the important data in wavelet domain. The difference type of mother wavelet has its own shape and its own characteristic. Therefore this affects to the performance of compression. This work compares the efficiency of compression algorithm by using difference type of Mother Wavelet. The test shows that no mother wavelet which is the best for all ECG. Thereby, reducing the time consuming for selection the proper mother wavelet, the Best of Four Method is introduced. This algorithm uses four types of mother wavelet to be competitors, 'db1', 'db2', 'db9' and 'bior2.4'. The result shows that the selected mother wavelet types have the good performance on overall tested signals. Moreover, the 'db1' mother wavelet has the best performance on more than a half of all signals.
This research is concerned with a dynamic mapping electrocardiogram (ECG) compression method that effectively reduces the percent root mean square difference (PRD) and at the same time achieves the satisfactorily high compression ratio (CR). The distinctive characteristic of the proposed technique lies in its applicability to both the regular and irregular ECG signals, compared to existing techniques that are solely applicable to the regular signal. Specifically, in the dynamic mapping, the Period Scaling technique is first applied and the Dynamic Time Warping (DTW) technique is then triggered if the signal error exceeds the maximum beat error. The signal error exceeding the maximum beat error indicates an irregular ECG signal. In the assessment, the proposed technique was applied to a total of 42 MIT-BIH ECG signals. The experiments were conducted using a maximum beat error of 1% and various threshold criteria sets by varying EPEAC and EPEDC1, EPEDC2, EPEDC3 in the ranges of 90-99% and 50-99%, respectively, where EPEAC and EPEDC1-3 are Energy Packing Efficiency's approximation coefficient and detailed coefficients. The results indicate that the threshold sets of 99% for EPEAC and 80-90% equally for EPEDC1, EPEDC2 and EPEDC3 contribute to less than 1% PRD values and the satisfactorily high CR levels of 4.6-11. Moreover, this research descriptively compared the ECG signal numbers 100 (regular), 117 and 228 (irregular) with regard to the signal compression performances.
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