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A new method based on wavelet and greedy pusuit analysis for neuro-spike detection
Duan J.; Chen L.; Chen C.L.P.
2014
Conference NameInternational Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)
Source PublicationICCSS 2014 - Proceedings: 2014 International Conference on Informative and Cybernetics for Computational Social Systems
Pages74-78
Conference DateOCT 09-10, 2014
Conference PlaceQingdao, PEOPLES R CHINA
Abstract

This paper introduces a novel greedy model for spike detection system aimed to neural signal obtained from the brain such as EEG, ECOG. This Presented algorithm combines wavelet transform and simultaneous orthogonal matching pursuit (SOMP). The proposed method is capable of data compression for spike detection. The spike detection experiment demonstrates the TPR in ROC curve is up to 98.76% and the compact factor reaches 42.52 when the length of window we used is 500. Moreover, our method is simple for low power system design and real-time hardware realization.

KeywordBio-signal Eeg Somp Spike Detection Wavelet Transform
DOI10.1109/ICCSS.2014.6961819
URLView the original
Language英語English
WOS IDWOS:000358127600014
Scopus ID2-s2.0-84916614259
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Duan J.,Chen L.,Chen C.L.P.. A new method based on wavelet and greedy pusuit analysis for neuro-spike detection[C], 2014, 74-78.
APA Duan J.., Chen L.., & Chen C.L.P. (2014). A new method based on wavelet and greedy pusuit analysis for neuro-spike detection. ICCSS 2014 - Proceedings: 2014 International Conference on Informative and Cybernetics for Computational Social Systems, 74-78.
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