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