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Neuron’s spikes noise level classification using hidden markov models
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posted on 2014-01-01, 00:00 authored by Sherif Haggag, Shady MohamedShady Mohamed, Asim BhattiAsim Bhatti, Hussein Haggag, Saeid NahavandiConsidering that the uncertainty noise produced the decline in the quality of collected neural signal, this paper proposes a signal quality assessment method for neural signal. The method makes an automated measure to detect the noise levels in neural signal. Hidden Markov Models were used to build a classification model that classifies the neural spikes based on the noise level associated with the signal. This neural quality assessment measure will help doctors and researchers to focus on the patterns in the signal that have high signal to noise ratio and carry more information.
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Title of book
Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part IIIVolume
8836Series
Lecture notes in computer scienceChapter number
61Pagination
501 - 508Publisher
SpringerPlace of publication
Berlin, GermanyPublisher DOI
ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319126425Language
engPublication classification
B Book chapter; B1 Book chapterCopyright notice
2014, SpringerExtent
83Editor/Contributor(s)
C Loo, K Yap, K Wong, A Teoh, K HuangUsage metrics
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