The Mixture of Experts (MOE) approach, combining a global classifier with a patient-specific local classifier trained on 5 minutes of data, significantly enhanced ECG beat classification performance.
Arrhythmia (n=33)
Mixture of Experts (MOE) ECG beat classifier vs Global Expert (GE) classifier
ECG beat classification performance
We present a "mixture-of-experts" (MOE) approach to develop customized electrocardiogram (ECG) beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. A small customized classifier is developed based on brief, patient-specific ECG data. It is then combined with a global classifier, which is tuned to a large ECG database of many patients, to form a MOE classifier structure. Tested with MIT/BIH arrhythmia database, we observe significant performance enhancement using this approach.
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Yu Hen Hu
University of Wisconsin–Madison
Shubha Deepti Palreddy
Veris Technologies (United States)
W.J. Tompkins
Electrophysiology
IEEE Transactions on Biomedical Engineering
University of Wisconsin–Madison
University of Wisconsin System
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Hu et al. (Wed,) conducted a other in Arrhythmia (n=33). Mixture of Experts (MOE) ECG beat classifier vs. Global Expert (GE) classifier was evaluated on ECG beat classification performance. The Mixture of Experts (MOE) approach, combining a global classifier with a patient-specific local classifier trained on 5 minutes of data, significantly enhanced ECG beat classification performance.
synapsesocial.com/papers/6a1565ab5347fbb1739fb82e — DOI: https://doi.org/10.1109/10.623058