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.

Characterization and Design of EEG Classifier: Uncertainty and Modeling

TROTTA, Amerigo;
2008

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.
MeMeA 2008 - IEEE International Workshop on Medical Measurements and Applications
978-1-4244-1937-1
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/14582
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