Brain-computer Interfaces : Current Trends and Applications

Hassanien, Aboul Ella (EDT); Azar, Ahmad Taher (EDT)

ISBN 10: 3319379976 ISBN 13: 9783319379975

Editorial: Springer, 2016

Idioma: Ingl�s

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Detalles bibliogr�ficos

T�tulo

Brain-computer Interfaces : Current Trends and Applications

Editor

Springer

Fecha de publicaci�n

2016

Idioma

Ingl�s

ISBN 10

3319379976

ISBN 13

9783319379975

Encuadernaci�n

Encuadernaci�n de tapa blanda

Estado

As New

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Sinopsis

The success of a BCI system depends as much on the system itself as on the user’s ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity.

The book is basically divided into three parts. The first part of the book covers the basic concepts and overviews of Brain Computer Interface. The second part describes new theoretical developments of BCI systems. The third part covers views on real applications of BCI systems.

De la contraportada

The success of a BCI system depends as much on the system itself as on the user s ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity.

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