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Title: | ECG Beat Classification Using Cross-Wavelet And LVQ |
Authors: | DATTA, Saibal |
Keywords: | Publications Cross-Wavelet Spectrum Cross-Wavelet Coherence Spectrum LVQ Saibal Dutta |
Issue Date: | 10-Dec-2016 |
Abstract: | This paper describes an automatic classification system based on combination of cross-wavelet and Learning Vector Quantization (LVQ) for the purpose of automatic heartbeat detection. The feature extractor is based on cross-wavelet approach, using the time frequency information. The ANN classifier uses a Learning Vector Quantization (LVQ) method which classifies the ECG beats into two categories: normal beats and abnormal beats. The ECG (electrocardiogram) signals in the MIT-BIH arrhythmia database are adopted as reference data. Total 98530 heart beats are used for testing the above classifier. The total classification accuracy (TCA) was about 91.66%. |
URI: | http://hdl.handle.net/123456789/1181 |
ISBN: | 978 -93-86171-12-2 |
Appears in Collections: | Electrical Engineering (Publications) |
Files in This Item:
File | Description | Size | Format | |
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IC3_ECG BEAT CLASSIFICATION USING CROSS-WAVELET AND LVQ.pdf | 577.8 kB | Adobe PDF | View/Open |
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