Matrix of regularity for improving the quality of ECGs.

The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of abnormalities of the heart. However, the ECG is susceptible to artifacts, which may lead to wrong diagnosis and thus mistreatment. It is a clinical challenge of great significance differentiating ECG artifacts from patterns of diseases. We propose a computational framework, called the matrix of regularity, to evaluate the quality of ECGs. The matrix of regularity is a novel mechanism to fuse results from multiple tests of signal quality. Moreover, this method can produce a continuous grade, which can more accurately represent the quality of an ECG. When tested on a dataset from the Computing in Cardiology/PhysioNet Challenge 2011, the algorithm achieves up to 95% accuracy. The area under the receiver operating characteristic curve is 0.97. The developed framework and computer program have the potential to improve the quality of ECGs collected using conventional and portable devices.