Classification of cardiac rhythm using heart rate dynamical measures: validation in MIT-BIH databases

Journal of Electrocardiology
Marta CarraraM Ferrario

Abstract

Identification of atrial fibrillation (AF) is a clinical imperative. Heartbeat interval time series are increasingly available from personal monitors, allowing new opportunity for AF diagnosis. Previously, we devised numerical algorithms for identification of normal sinus rhythm (NSR), AF, and SR with frequent ectopy using dynamical measures of heart rate. Here, we wished to validate them in the canonical MIT-BIH ECG databases. We tested algorithms on the NSR, AF and arrhythmia databases. When the databases were combined, the positive predictive value of the new algorithms exceeded 95% for NSR and AF, and was 40% for SR with ectopy. Further, dynamical measures did not distinguish atrial from ventricular ectopy. Inspection of individual 24hour records showed good correlation of observed and predicted rhythms. Heart rate dynamical measures are effective ingredients in numerical algorithms to classify cardiac rhythm from the heartbeat intervals time series alone.

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Citations

Jun 7, 2016·Computer Methods and Programs in Biomedicine·Manuel GarcíaJosé J Rieta
Mar 16, 2017·Critical Care Medicine·Travis J MossJ Randall Moorman
Jun 23, 2018·Physiological Measurement·Jessica Keim-MalpassMatthew T Clark
Jul 22, 2019·Journal of Clinical Monitoring and Computing·Jessica Keim-MalpassJ Randall Moorman
Jul 17, 2020·Critical Care Explorations·Jacob N BlackwellJ Randall Moorman
Oct 30, 2021·Physiological Measurement·Wei Zhong, Weibin Zhao

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