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 / Lay Ekuakille, A; Vendramin, G; Trotta, Amerigo; De Rinaldis, M; Trabacca, A.. - (2008), pp. 44-48. (Intervento presentato al convegno MeMeA 2008 - IEEE International Workshop on Medical Measurements and Applications tenutosi a Ottawa, Canada nel May 9-10, 2008) [10.1109/MEMEA.2008.4542995].
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
