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A patient-adaptable ECG beat classifier using a mixture of experts approach

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3 Author(s)
Yu Hen Hu ; Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA ; S. Palreddy ; W. J. Tompkins

Presents a "mixture-of-experts" (MOE) approach to develop customized electrocardiogram (EGG) 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, the authors observe significant performance enhancement using this approach.

Published in:

IEEE Transactions on Biomedical Engineering  (Volume:44 ,  Issue: 9 )