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Blind biosignal classification framework based on DTW algorithm
Chao S.; Wong F.; Lam H.-L.; Vai M.-I.
2011-11-07
Conference Name2011 International Conference on Machine Learning and Cybernetics
Source PublicationProceedings - International Conference on Machine Learning and Cybernetics
Volume4
Pages1684-1689
Conference Date10-13 July 2011
Conference PlaceGuilin, China
Abstract

Biosignal is a noninvasive measurement of the status of internal organism, such as electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG), etc. With machine learning techniques, these biosignals are normally classified into one of a number of disease categories. Hence, they are ideally suited to support clinician in making diagnostic decision. However, if a given biosignal is an unknown type, none of the existing classification algorithms can be considered workable. In this paper, an intelligent framework that is able to automatically identify ECG from an unknown biosignal is described. In which, the first phase of the research is illustrated in detail, which focuses on classifying an unknown biosignal into ECG or other categories, by employing dynamic time warping (DTW), combined with clustering algorithm. The proposed framework consists of two major components: biosignal template construction and classification process. Biosignal template construction includes biosignal acquisition and segmentation, template optimization and management; while the classification process involves several sub-processes: biosignal preprocessing, biosignal pattern matching and majority voting. The experimental results demonstrate the effectiveness of the framework as well as the classification methodology. © 2011 IEEE.

KeywordBiosignal Classification Clustering Data Mining Dynamic Time Warping (Dtw)
DOI10.1109/ICMLC.2011.6017023
URLView the original
Language英语
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Chao S.,Wong F.,Lam H.-L.,et al. Blind biosignal classification framework based on DTW algorithm[C],2011:1684-1689.
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