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Neuron’s spikes noise level classification using hidden markov models

chapter
posted on 2014-01-01, 00:00 authored by Sherif Haggag, Shady MohamedShady Mohamed, Asim BhattiAsim Bhatti, Hussein Haggag, Saeid NahavandiSaeid Nahavandi
Considering 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.

History

Title of book

Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part III

Volume

8836

Series

Lecture notes in computer science

Chapter number

61

Pagination

501 - 508

Publisher

Springer

Place of publication

Berlin, Germany

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319126425

Language

eng

Publication classification

B Book chapter; B1 Book chapter

Copyright notice

2014, Springer

Extent

83

Editor/Contributor(s)

C Loo, K Yap, K Wong, A Teoh, K Huang