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Classification of cardiac rhythm using heart rate dynamical measures: validation in MIT-BIH databases
Marta Carrara1, Luca Carozzi1, Travis J Moss2
1Department of Electronics, Information and Bioengineering, Politecnico di Milano, P.zza Leonardo da Vinci 32, Milan, Italy.
Background:
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.
Goal:
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.
Methods:
We tested algorithms on the NSR, AF and arrhythmia databases.
Results:
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.
Conclusion:
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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