NDLI: Blind biosignal classification framework based on DTW algorithm

Content Provider	IEEE Xplore Digital Library
Author	Sam Chao Fai Wong Heng-Leong Lam Mang-I Vai
Copyright Year	2011
Description	Author affiliation: Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau (Sam Chao; Fai Wong; Heng-Leong Lam) \|\| Department of Electrical and Electronics Engineering, Faculty of Science and Technology, University of Macau, Macau (Mang-I Vai)
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.
Starting Page	1684
Ending Page	1689
File Size	238891
Page Count	6
File Format	PDF
ISBN	9781457703058
ISSN	21601348
e-ISBN	9781457703089
DOI	10.1109/ICMLC.2011.6017023
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Classification algorithms Clustering algorithms Electroencephalography Heuristic algorithms Time series analysis Machine learning Clustering Biosignal Classification Data mining Dynamic time warping (DTW)
Content Type	Text
Resource Type	Article

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