A Novel Technique for ECG Morphology Interpretation and Arrhythmia Detection Based on Time Series Signal Extracted from Scanned ECG Record

Cardiovascular disease (CVD) is the one of the biggest health problem in Indian and around the world as well. Electrocardiogram is a traditional method used for the diagnosis of heart diseases for about a century. Maintaining and retrieving patient history during a course of treatment is a essential but a laborious process. More particularly, over a decade ago thermal ECG records were stored physically, off late, due to advancement in technology; it has been stored as scanned ECG images. Storing the scanned ECG trace images requires considerable storage space. This necessitated the development of an automated solution capable of storing the ECG digitally, retrieving it quickly and detecting cardiac arrhythmia automatically. Majority of the ECG’s clinical information is said to be found in the intervals and amplitudes defined by its features (characteristic wave peaks and time durations).According to author’s knowledge, very few researchers [Lawson et al., 1995, Silva et al., Wang et al., 2009, Chebil et.al., 2008, Kao et al.,2001] have approached the extraction of ECG digital time series signal from scanned ECG trace images. Lawson et al., chose a scanning resolution of 200 dpi and used global thresholds to separate the ECG trace from the background grid lines. The low resolution results in loss of data accuracy and global thresholds results in missing pixels which are replenished by linear interpolation. Fabio Badilini et al., 2005 developed an application for extraction of the ECG trace from the image. But the method requires the user to fix anchor points for missing peaks and thus the accuracy comes down. Shen et al., separated the ECG trace from the background grids using the histogram. The missing pixels are replenished by checking the value of the pixel in the original image. This is a tedious process. Kao et al., employed a color filter to remove the background gridlines in the color image. There was a problem of missing pixels in the process which was replenished by linear interpolation. Jalel Chebil et al., performed a comparative study of the extracted trace accuracy by scanning the image at various resolutions. Global thresholds and median filtering were employed to remove background grids. The threshold to separate the trace from the background should be selected based on the nature of the image to avoid any