Robust arrhythmia classifier using wavelet transform and support vector machine classification
The Electrocardiogram (ECG) is the most widely used signal in clinical practice for the assessment of cardiac condition. This paper presents a robust arrhythmia classifier based on the combination of wavelet transform and timing features, as well as support vector machine classification technique. T...
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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Published: |
2017
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/97277/ http://dx.doi.org/10.1109/CSPA.2017.8064959 |
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Institution: | Universiti Teknologi Malaysia |
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