Referenced Items are not available for this document.
In this paper the feature extraction of the EEG Signal is done by computing the Discrete Wavelet Transform. The wavelet transform coefficients compress the number of data points into few features. Various statistics were used to further reduce the dimensionality. The Classification of the EEG sleep stages is done by using neural network which provides more accurate sleep stage classification compared to other techniques.
Published in:
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Date of Conference: 5-7 Jan. 2012
- Page(s):
- 71 - 74
- E-ISBN :
- 978-1-4577-2175-5
- Print ISBN:
- 978-1-4577-2176-2
- INSPEC Accession Number:
- 12785529
- Conference Location :
- Hong Kong
- Digital Object Identifier :
- 10.1109/BHI.2012.6211508
- Product Type:
- Conference Publications
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