Title :
Sleep stages classification using wavelettransform & neural network
Author :
Jain, Vardhman Pukhraj ; Mytri, V.D. ; Shete, Virendra V. ; Shiragapur, B.K.
Author_Institution :
COE, MIT, Pune, India
Abstract :
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.
Keywords :
discrete wavelet transforms; electroencephalography; feature extraction; medical signal processing; neural nets; signal classification; sleep; statistics; EEG signal; EEG sleep stages classification; data point compression; dimensionality reduction; discrete wavelet transform; feature extraction; neural network; statistics; Biographies; Artificial Neural Network (ANN); Back Propagation Neural Network (BPN); DWT (Discrete Wavelet Transform); Electroencephalogram (EEG); Standard Deviation (SD);
Conference_Titel :
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-2176-2
Electronic_ISBN :
978-1-4577-2175-5
DOI :
10.1109/BHI.2012.6211508
