Abstract:
Cardiovascular disease (CVD) is the leading cause of death throughout the world. Since electrocardiogram-reports (ECG) have a great CVD predicting potential, the demand for their real-time analysis is high. Although algorithms are present to perform analysis, most countries still use analogue acquisition systems that can only output a printed trace. It is necessary to extract the signal from these printouts to perform analysis. With time, as the reports pile up and the trace fades from the printout, the task becomes increasingly difficult. The method presented specifically focuses on extracting signals from faded traces. Due to the large variability of scans, it is difficult to automate this task completely. In this paper, we propose several tools for ECG extraction while maintaining a minimum user involvement requirement. The proposed method was tested on a dataset of 550 trace snippets and comparative analysis shows an average accuracy of 96%.
