Electrocardiogram data mining based on frame classification by dynamic time warping matching |
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Authors: | Gong Zhang Witold Kinsner Bin Huang |
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Affiliation: | 1. St Boniface General Hospital , 409 Tache, Winnipeg, Canada umzhan00@hotmail.com;3. Department of Electrical and Computer Engineering , University of Manitoba , Manitoba, Canada;4. Micropilot Inc. , Stony Mountain, Manitoba, Canada |
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Abstract: | This paper presents an electrocardiogram (ECG) data mining scheme based on the ECG frame classification realised by a dynamic time warping (DTW) matching technique, which has been used successfully in speech recognition. We use the DTW to classify ECG frames because ECG and speech signals have similar non-stationary characteristics. The DTW mapping function is obtained by searching the frame from its end to start. A threshold is setup for DTW matching residual either to classify an ECG frame or to add a new class. Classification and establishment of a template set are carried out simultaneously. A frame is classified into a category with a minimal residual and satisfying a threshold requirement. A classification residual of 1.33% is achieved by the DTW for a 10-min ECG recording. |
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Keywords: | ECG data mining classification dynamic time warping |
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