An efficient visibility graph similarity algorithm and its application for sleep stages classification

Zhu, Guohun and Li, Yan and Wen, Peng Paul (2012) An efficient visibility graph similarity algorithm and its application for sleep stages classification. In: 2012 International Conference on Brain Informatics (BI 2012), 4-7 Dec 2012, Macao.

Abstract

This paper presents an efficient horizontal visibility directed graph similarity algorithm (HVDS) by taking the advantages of two synchronization measuring methods in graph theory: phase locking value (PLV) and visibility graph similarity (VGS). It develops a new linear horizontal visibility graph constructing algorithm, analyzes its constructing complexity, and tests its feature performance via the sleep stages identification application. Six features are extracted, separately, from HVDS, PLV and VGS as the input to a support vector machine to classify the seven sleep stages. 11,120 data segments are used for the experiments with each segment lasts 30 seconds. The training sets are selected from a single subject and the testing sets are selected from multiple subjects. 10-cross-validation is employed to evaluate the performances of the PLV, VGS and HVDS methods. The experimental results show that the PLV, VGS and HVDS algorithms produce an average classification accuracy of 72.3%, 81.5% and 82.6%, respectively. The speed of the HVDS is 39 times faster than the VGS algorithm.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published as Lecture Notes in Computer Science, Vol. 7670. Permanent restricted access to published version due to publisher copyright policy.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 09 Apr 2013 23:21
Last Modified: 04 May 2016 02:40
Uncontrolled Keywords: computational complexity, phase locking value, horizontal visibility; directed graph similarity, classification sleep stage, synchronization
Fields of Research : 11 Medical and Health Sciences > 1199 Other Medical and Health Sciences > 119999 Medical and Health Sciences not elsewhere classified
01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics
09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
08 Information and Computing Sciences > 0803 Computer Software > 080301 Bioinformatics Software
11 Medical and Health Sciences > 1117 Public Health and Health Services > 111714 Mental Health
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1007/978-3-642-35139-6_18
URI: http://eprints.usq.edu.au/id/eprint/22906

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