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EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces

Brain–Computer Interfaces for Human Augmentation

Department of Otolaryngology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
Author to whom correspondence should be addressed.
Brain Sci. 2019, 9(2), 22;
Received: 21 January 2019 / Accepted: 22 January 2019 / Published: 24 January 2019
(This article belongs to the Special Issue Brain-Computer Interfaces for Human Augmentation)
Note: In lieu of an abstract, this is an excerpt from the first page.

The field of brain–computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into control signals for external devices for people with severe disabilities [...] View Full-Text
MDPI and ACS Style

Valeriani, D.; Cinel, C.; Poli, R. Brain–Computer Interfaces for Human Augmentation. Brain Sci. 2019, 9, 22.

AMA Style

Valeriani D, Cinel C, Poli R. Brain–Computer Interfaces for Human Augmentation. Brain Sciences. 2019; 9(2):22.

Chicago/Turabian Style

Valeriani, Davide, Caterina Cinel, and Riccardo Poli. 2019. "Brain–Computer Interfaces for Human Augmentation" Brain Sciences 9, no. 2: 22.

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