DocumentCode :
1860272
Title :
Characterization and Design of EEG Classifier: Uncertainty and Modeling
Author :
Lay-Ekuakille, Aime ; Vendramin, Giuseppe ; Trotta, Amerigo ; Rinaldis, MartaDe ; Trabacca, Antonio
Author_Institution :
Dipt. dTngegneria dell´´Innovazione, Salento Univ., Lecce
fYear :
2008
fDate :
9-10 May 2008
Firstpage :
44
Lastpage :
48
Abstract :
EEG signals reveal interesting information about human being´s cerebral activity. Nowadays information contents can help physicians especially in rehabilitation operations, that is, it is possible to design specific biomedical experimentation in order to help patients to retrieve acceptable and good conditions of their physical apparatus or specific areas of them. In this paper, preliminary criteria of designing and implementing an EEG classification are proposed. A modeling of classification rules is also described.
Keywords :
electroencephalography; medical signal processing; patient rehabilitation; pattern classification; signal classification; EEG classifier characterization; EEG classifier design; classification rule modeling; human cerebral activity; rehabilitation operations; Biomedical measurements; Blood; Brain modeling; Electrodes; Electroencephalography; Epilepsy; Frequency; Humans; Scalp; Uncertainty; Adaptive filtering; BCI (Brain Computer Interface); EEG Signal processing; Epilepsy; Muscular dystrophy; WAI (Web Accessibility Initiative); biomedical instrumentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Measurements and Applications, 2008. MeMeA 2008. IEEE International Workshop on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-1937-1
Electronic_ISBN :
978-1-4244-1938-8
Type :
conf
DOI :
10.1109/MEMEA.2008.4542995
Filename :
4542995
Link To Document :
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