DocumentCode :
2970416
Title :
Modified Kohonen´s self-organizing feature map and its application to automatic sleep cycle recognition
Author :
Blanchet, Max ; Yoshizawa, Shuji ; Amari, Shun-Ichi
Author_Institution :
Tokyo Univ., Japan
Volume :
3
fYear :
1993
fDate :
25-29 Oct. 1993
Firstpage :
2476
Abstract :
In order to increase the adaptive ability of the Kohonen´s self-organizing feature map algorithm, we modify the updating rule of its partition boundary. The modified algorithm, together with the genetic algorithm, is applied to the detection of the REM (rapid eye movement) cycle of the sleep, which is said to be related to comfortableness of the sleep. We used the heart-rate alone (not EEG) and succeeded to achieve a high detection accuracy.
Keywords :
genetic algorithms; medical signal processing; pattern recognition; self-organising feature maps; Kohonen self-organizing feature map; automatic sleep cycle recognition; genetic algorithm; heart-rate; neural nets; rapid eye movement detection; Algorithm design and analysis; Computer vision; Data structures; Electroencephalography; Electrooculography; Envelope detectors; Genetic algorithms; Laboratories; Partitioning algorithms; Sleep;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
Type :
conf
DOI :
10.1109/IJCNN.1993.714226
Filename :
714226
Link To Document :
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