A Comparative Study between SVM and Fuzzy Inference System for the Automatic Prediction of Sleep Stages and the Assessment of Sleep Quality

A Comparative Study between SVM and Fuzzy Inference System for the Automatic Prediction of Sleep Stages and the Assessment of Sleep Quality

This paper compares two supervised learning algorithms for predicting the sleep stages based on the human brain activity. The first step of the presented work regards feature extraction from real human electroencephalography (EEG) data together with its corresponding sleep stages that are utilized f...

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Bibliographic Details
Main Authors: John Gialelis, Chris Panagiotou, Ioakeim Samaras, Petros Chondros, Dimitris Karadimas
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2015-11-01
Series:EAI Endorsed Transactions on Pervasive Health and Technology
Subjects:
eeg
sleep stages
svm
fis
Online Access:http://eudl.eu/doi/10.4108/icst.pervasivehealth.2015.259248

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