ECG Quality Assessment Based on Image Processing Techniques

This work is motivated by the Physionet/Computing in Cardiology Challenge 2011, “Improving the quality of ECGs collected using mobile phones”. The advancement of cell phone technology makes it possible to collect, analyze, and transmit vital physiological signals in real time, promising to a new era of tele-health care. However, noises and artifacts can lead to false readings and thus misdiagnosis. Unlike common methods based on time series analysis techniques, we analyze the quality of the 12-lead ECG using image processing techniques. Various image patterns are used as features to distinguish between low- and high-quality signals. When tested on a data set from the Physionet Challenge 2011, the analyses yield up to 94.36% accuracy. The work here provides an interesting alternative for ECG quality evaluation. The technique will have particular use for ECGs scanned from paper recordings.