Digitization of ECG Paper Records using MATLAB
Priyanka R. K. Shrivastava1, Shraddha Panbude2, Geeta Narayanan3
1Priyanka R. K. Shrivastava, Student, Department of EXTC, Vidyalankar Institute of Technology Wadala E, Mumbai (Maharashtra), India.
2Prof. Shraddha Panbude, Associate Professor, EXTC, Vidyalankar Institute of Technology Wadala E, Mumbai (Maharashtra), India.
3Geeta Narayanan, Associate Professor, EXTC, Vidyalankar Institute of Technology Wadala E, Mumbai (Maharashtra), India.
Manuscript received on 12 November 2014 | Revised Manuscript received on 22 November 2014 | Manuscript Published on 30 November 2014 | PP: 1-3 | Volume-4 Issue-6, November 2014 | Retrieval Number: F1843114614/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Electrocardiogram (ECG) is the most important and widely used method to study the heart related diseases. The detailed study of ECG graph by the medical practitioner helps him to understand and identify the condition of the heart. Based on the information retrieved from the ECG graph the patient can be given proper treatment. The person having a medical history of heart ailments will have to maintain a record of all the ECG papers for timely analysis and diagnosis of the diseases. This process requires large storage space and extensive manual effort. The conventional technique of visual analysis to inspect the ECG signals by doctors or physicians are not effective and time consuming. Therefore, an automatic system which involves digital signal integration and analysis is required. In this study a MATLAB-based tool is being designed to convert electrocardiography (ECG) information from paper charts into digital ECG signals. Here we develop a method that involves processing of ECG paper records by an efficient and iterative set of digital image processing techniques for the conversion of ECG paper image data to time series digitized signal form, resulting in convenient storage and retrieval of ECG information. In addition, this tool can be used to potentially integrate digitized ECG information with digital ECG analysis programs and with the patient’s electronic medical record.
Keywords: ECG, Compression, Segmentation, Image Retrieval, Digitization. Laplacian Filtering.
Scope of the Article: Image Processing and Pattern Recognition