Computer algorithms for evaluating the quality of ECGs in real time

ECG, measuring body-surface electrical waves generated in the heart, is the golden standard for diagnosis of various cardiovascular diseases. The 2011 Physionet challenge visions mobile phones that can be used to collect and analyse ECG records. Such devices are particularly useful in underdeveloped regions, which have a large population size but lack adequate primary care capacity. Signals collected using mobile phones can be sent via mobile network to experienced doctors for further diagnosis. In response to Physionet 2011 challenge, we explore various time series techniques for their potentials in evaluating quality of an ECG, including time domain analysis, frequency domain analysis, joint time-frequency analysis, self correlation, cross correlation, and entropy analysis. Two algorithms are developed based on these techniques. The first algorithm consists of multi-stage tests. A record that passes all tests is regarded as of acceptable quality. In the second algorithm, results from various analyses are assembled into a matrix, which measures the regularity of the ECG. The quality of the ECG is then measured by the spectrum radius of the Matrix of Regularity. Since spectrum radius is continuous, the results can lead to continuous grades of ECGs. The algorithms are tested using training data from Physionet. Influences of various parameters are examined.