Publication Details
Title: Sleep Stage Classification using Wavelet Transform and Neural Network
Author: E. Oropesa, H. L. Cycon, and M. Jobert
Group: ICSI Technical Reports
Date: March 1999
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1999/tr-99-008.pdf
Overview:
In this paper we present a new method to do automatic sleep stage classification. The algorithm consists of basically three modules. A wavelet packet transformation (WPT) applied to 30 seconds long epochs of EEG recordings to provide localized time-frequency information, a feature generator which quantifies the information and reduce the data set size, and an artificial neural network for doing optimal classification. The classification results compared to those of a human expert reached a 70 to 80% of agreement.
Bibliographic Information:
ICSI Technical Report TR-99-008
Bibliographic Reference:
E. Oropesa, H. L. Cycon, and M. Jobert. Sleep Stage Classification using Wavelet Transform and Neural Network. ICSI Technical Report TR-99-008, March 1999
Author: E. Oropesa, H. L. Cycon, and M. Jobert
Group: ICSI Technical Reports
Date: March 1999
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1999/tr-99-008.pdf
Overview:
In this paper we present a new method to do automatic sleep stage classification. The algorithm consists of basically three modules. A wavelet packet transformation (WPT) applied to 30 seconds long epochs of EEG recordings to provide localized time-frequency information, a feature generator which quantifies the information and reduce the data set size, and an artificial neural network for doing optimal classification. The classification results compared to those of a human expert reached a 70 to 80% of agreement.
Bibliographic Information:
ICSI Technical Report TR-99-008
Bibliographic Reference:
E. Oropesa, H. L. Cycon, and M. Jobert. Sleep Stage Classification using Wavelet Transform and Neural Network. ICSI Technical Report TR-99-008, March 1999