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Conference Paper: A novel dot-plot algorithm for surface EMG signal segment identification

TitleA novel dot-plot algorithm for surface EMG signal segment identification
Authors
KeywordsDot-plot analysis
Segmentation
Time series analysis
Surface EMG
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6598376
Citation
The 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Shenzhen, China, 12-14 June 2015. In Conference Proceedings, 2015, p. 1-6 How to Cite?
AbstractSegmentation of surface EMG signal often involve in many scenarios including motion classification in robotic prostheses and motion segment identification. Many of them require a threshold that is predefined or a training data set. The objective of this paper is to find a way to perform segmentation without a threshold or training data set. Dot plot analysis has been widely used in bioinformatics to identify similar segments between proteins or DNA. The philosophy behind dot plot analysis can be applied to perform surface EMG signal segmentation. The properties of the new algorithm is examined. The major advantage of the dot-plot segmentation algorithm is that threshold is no long need to be estimated, instead the minimal length of a segment in a time series signal need to be declared.
Persistent Identifierhttp://hdl.handle.net/10722/213564
ISBN

 

DC FieldValueLanguage
dc.contributor.authorSit, ECY-
dc.contributor.authorHu, Y-
dc.date.accessioned2015-08-05T08:02:56Z-
dc.date.available2015-08-05T08:02:56Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Shenzhen, China, 12-14 June 2015. In Conference Proceedings, 2015, p. 1-6-
dc.identifier.isbn978-1-4799-6092-7-
dc.identifier.urihttp://hdl.handle.net/10722/213564-
dc.description.abstractSegmentation of surface EMG signal often involve in many scenarios including motion classification in robotic prostheses and motion segment identification. Many of them require a threshold that is predefined or a training data set. The objective of this paper is to find a way to perform segmentation without a threshold or training data set. Dot plot analysis has been widely used in bioinformatics to identify similar segments between proteins or DNA. The philosophy behind dot plot analysis can be applied to perform surface EMG signal segmentation. The properties of the new algorithm is examined. The major advantage of the dot-plot segmentation algorithm is that threshold is no long need to be estimated, instead the minimal length of a segment in a time series signal need to be declared.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6598376-
dc.relation.ispartofIEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications-
dc.rightsIEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications. Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectDot-plot analysis-
dc.subjectSegmentation-
dc.subjectTime series analysis-
dc.subjectSurface EMG-
dc.titleA novel dot-plot algorithm for surface EMG signal segment identification-
dc.typeConference_Paper-
dc.identifier.emailHu, Y: yhud@hku.hk-
dc.identifier.authorityHu, Y=rp00432-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CIVEMSA.2015.7158632-
dc.identifier.hkuros247340-
dc.identifier.spage1-
dc.identifier.epage6-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 150805-

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