Brain Computer Interfaces for Silent Speech

Date

2017-05-01

Author

TABAR, Yousef Rezaei
Halıcı, Uğur

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

145
views

0
downloads

Brain Computer Interface (BCI) systems provide control of external devices by using only brain activity. In recent years, there has been a great interest in developing BCI systems for different applications. These systems are capable of solving daily life problems for both healthy and disabled people. One of the most important applications of BCI is to provide communication for disabled people that are totally paralysed. In this paper, different parts of a BCI system and different methods used in each part are reviewed. Neuroimaging devices, with an emphasis on EEG (electroencephalography), are presented and brain activities as well as signal processing methods used in EEG-based BCIs are explained in detail. Current methods and paradigms in BCI based speech communication are considered.

Subject Keywords

Single-trial eeg, Random neural-networks, Bci-competition-iii;, Virtual keyboard, Classification, Communication, Movement, Design, Identification, Patterns

URI

https://hdl.handle.net/11511/37736

Journal

EUROPEAN REVIEW

DOI

https://doi.org/10.1017/s1062798716000569

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Brain Computer Interfaces Halıcı, Uğur (null; 2015-11-12) Brain Computer Interface (BCI) systems provide control of external devices by using only brain activity. In recent years, there has been a great interest in developing BCI systems for different applications. These systems are capable of solving daily life problems for both healthy and disabled people. One of the most important applications of BCI is to provide communication for disabled people that are totally paralysed. In this paper, different parts of a BCI system and different methods used in each part ...
Analysis and classification of spelling paradigm EEG data and an attempt for optimization of channels used Yıldırım, Asil; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2010) Brain Computer Interfaces (BCIs) are systems developed in order to control devices by using only brain signals. In BCI systems, different mental activities to be performed by the users are associated with different actions on the device to be controlled. Spelling Paradigm is a BCI application which aims to construct the words by finding letters using P300 signals recorded via channel electrodes attached to the diverse points of the scalp. Reducing the letter detection error rates and increasing the speed of...
Neural networks with piecewise constant argument and impact activation Yılmaz, Enes; Akhmet, Marat; Department of Scientific Computing (2011) This dissertation addresses the new models in mathematical neuroscience: artificial neural networks, which have many similarities with the structure of human brain and the functions of cells by electronic circuits. The networks have been investigated due to their extensive applications in classification of patterns, associative memories, image processing, artificial intelligence, signal processing and optimization problems. These applications depend crucially on the dynamical behaviors of the networks. In t...
Prototype Hardware Design for Brain Computer Interface Applications Erdogan, Balkar; Akinci, Berna; Acar, Erman; Usakli, Ali Buelent; Gençer, Nevzat Güneri (2009-01-01) Brain Computer Interface (BCI) is an alternative communication pathway between the human brain and outside world in which only the brain activity is interpreted in a special way. These systems are based on the electrical activity of the brain that can be measured via Electroencephalography (EEG) devices. BCI enables people with severe motor disorders (like ALS) to communicate with their environment or control a wheelchair for their movement by using the EEG signals. In this study, a prototype data acquisito...
Application of Wiener Deconvolution Model in P300 Spelling Paradigm Erdogan, Balkar; Gençer, Nevzat Güneri (2009-01-01) Spelling Paradigm first introduced by Farwell and Donchin, is one of the Brain Computer Interface (BCI) applications that enables paralyzed people to communicate with their environment. In such a problem, user needs to focus on the characters which are randomly flashed row or column-wise on the computer screen in a small period of time. The accuracy in spelling words is the main problem in this scheme and the duration of the correct prediction is quite important. The purpose of this work is twofold: to anal...

Citation Formats

Y. R. TABAR and U. Halıcı, “Brain Computer Interfaces for Silent Speech,” EUROPEAN REVIEW, pp. 208–230, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37736.