The Feature Extraction to Determine the Wave’s Peaks in the Electrocardiogram Graphic Image

Abstract

Abstract-The electrocardiogram (ECG) will create the characteristic in the form of the wave's peak pattern. The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of feature extraction will be useful to help to detect certain case, including the determination of PQRST peaks according to the ECG print-out. This study makes a method to determine the ECG peaks (PQRST), the heart rate, and ST-deviation according to the ECG graphic image. The input data is in the form of ECG graphic image which is derived from the ECG 12 lead record. This study employs segmentation method (grayscale and binary), morphology (dilation and erosion), and produce the graphic image which is read as the ECG signal in the pre-processing stage, and use the Pan-Tompkins algorithm for the feature extraction method. The result of the peak determination is validated by cardiologists. The validation shows that the result of up and down deflection computation from the isoelectric of each P, Q, R, S, and T wave has represented the ECG calculation clinically; including the calculation to determine the R-R interval, heart rate, and STdeviation.

Image Analysis of 12 Lead Electrocardiogram Using Wavelet Transformation

“…ECG graphic image data is obtained from the scanning data of ECG recordings. The process of data preparation and pre-processing is similar to that done by [8].…”

“…Pre-processing is done by: Segmentation (gray scale and binary), Morphology (Dilation and Erosion), as well as changes to ECG graphic image, while feature extraction is to find the peaks of PQRST, Heart Rate (HR) and ST-Deviation [8]. Conducted the study by implementing a one-dimensional analysis approach (duration of the heart cycle) of heart rate variability to multidimensional analysis (shape parameters and peak location of the heart cycle) analysis of heart parameters [9].…”

“…Research conducted by [8], detects PQRST peak search, heart rate and ST deviation, in which ECG image data is captured by scan. The computational results show upward and downward deflection of the isoelectric P, Q, R, S respectively and T waves represent clinical EKG calculations.…”

“…The computational results show upward and downward deflection of the isoelectric P, Q, R, S respectively and T waves represent clinical EKG calculations. Research [8] allows to be expanded to a broader extent to extract its features, resulting in more accurate results of ECG information.…”

“…This study proposes to find the smallest MSE value of wavelet decomposition using Daubechies order 1 (db1(Haar)) using image data of ECG 12 lead. Pre-processing is done with several steps including: Segmentation (grayscale and binary), Morphology (Dilation and Erosion), as well as changes to ECG graphic image [8]…”