A patient adapting heartbeat classifier using ECG morphology and heart-beat interval features
Item Type:Journal Article
Citation:deChazal P. and Reilly R.B. 'A patient adapting heartbeat classifier using ECG morphology and heart-beat interval features' in IEEE Transactions on Biomedical Engineering, 53, (12), 2006, pp. 2535 - 2543.
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An adaptive system for the automatic processing of the electrocardiogram (ECG) for the classification of heartbeats into one of the five beat classes recommended by ANSI/AAMI EC57:1998 standard is presented. The heartbeat classification system processes an incoming recording with a global-classifier to produce the first set of beat annotations. An expert then validates and if necessary corrects a fraction of the beats of the recording. The system then adapts by first training a local-classifier using the newly annotated beats and combines this with the global-classifier to produce an adapted classification system. The adapted system is then used to update beat annotations. The results of this study show that the performance of a patient adaptable classifier increases with the amount of training of the system on the local record. Crucially, the performance of the system can be significantly boosted with a small amount of adaptation even when all beats used for adaptation are from a single class. This study illustrates the ability to provide highly beneficial automatic arrhythmia monitoring and is an improvement on previously reported results for automated heartbeat classification systems.
Author: REILLY, RICHARD
Type of material:Journal Article
Availability:Full text available