Paper Info
Title
Neuronal Spectral Analysis of EEG and Expert Knowledge Integration for Automatic Classification of Sleep Stages
Abstract
Being able to analyze and interpret signal coming from electroencephalogram (EEG) recording can be of high interest for many applications including medical diagnosis and Brain-Computer Interfaces. Indeed, human experts are today able to extract from this signal many hints related to physiological as well as cognitive states of the recorded subject and it would be very interesting to perform such task automatically but today no completely automatic system exists. In previous studies, we have compared human expertise and automatic processing tools, including artificial neural networks (ANN), to better understand the competences of each and determine which are the difficult aspects to integrate in a fully automatic system. In this paper, we bring more elements to that study in reporting the main results of a practical experiment which was carried out in an hospital for sleep pathology study. An EEG recording was studied and labeled by a human expert and an ANN. We describe here the characteristics of the experiment, both human and neuronal procedure of analysis, compare their performances and point out the main limitations which arise from this study.
Year
Venue
Keywords
2005
Clinical Orthopaedics and Related Research
medical diagnosis,artificial neural network,artificial intelligent,brain computer interface
Field
DocType
Volume
Data mining,Competence (human resources),Knowledge integration,Computer science,Brain–computer interface,Artificial intelligence,Artificial neural network,Cognition,Medical diagnosis,Electroencephalography,Sleep Stages,Machine learning
Journal
abs/cs/051
Issue
Citations 
PageRank 
11
2
0.62
References 
Authors
0
5
Name
Order
Citations
PageRank
Kerkeni Nizar120.96
Frédéric Alexandre28215.94
Mohamed Hédi Bedoui332.00
Laurent Bougrain4317.22
Mohamed Dogui521.64