Brain computer interfacing: Applications and challenges
Reads0
Chats0
TLDR
The application areas that could benefit from brain waves in facilitating or achieving their goals are shown and major usability and technical challenges that face brain signals utilization in various components of BCI system are discussed.About:
This article is published in Egyptian Informatics Journal.The article was published on 2015-07-01 and is currently open access. It has received 397 citations till now. The article focuses on the topics: Usability.read more
Citations
More filters
Journal ArticleDOI
Brain computer interface: control signals review
TL;DR: A review to the state-of-the-art work in the field of BCI on the Brain control signals, their types and classifications and the current BCI technology in terms of hardware and software is reviewed.
Journal ArticleDOI
EEG-Based Brain-Computer Interfaces for Communication and Rehabilitation of People with Motor Impairment: A Novel Approach of the 21 st Century.
Ioulietta Lazarou,Spiros Nikolopoulos,Panagiotis C. Petrantonakis,Ioannis Kompatsiaris,Magda Tsolaki +4 more
TL;DR: This work reviews the research on non-invasive, electroencephalography (EEG)-based BCI systems for communication and rehabilitation and focuses on the approaches intended to help severely paralyzed and locked-in patients regain communication using three different BCI modalities: slow cortical potentials, sensorimotor rhythms and P300 potentials.
Journal ArticleDOI
Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review
Mamunur Rashid,Norizam Sulaiman,Anwar P. P. Abdul Majeed,Rabiu Muazu Musa,Ahmad Fakhri Ab. Nasir,Bifta Sama Bari,Sabira Khatun +6 more
TL;DR: This article provides a comprehensive review of the state-of-the-art of a complete BCI system and a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics.
Journal ArticleDOI
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers.
TL;DR: The frontiers of applying deep learning for non-invasive brain signals analysis are provided, by summarizing a large number of recent publications, and the potential real-world applications which benefit not only disabled people but also normal individuals are reported.
Journal ArticleDOI
Deep Learning in the Biomedical Applications: Recent and Future Status
TL;DR: This paper reviews the major deep learning concepts pertinent to biomedical applications and concludes with a critical discussion, interpretation and relevant open challenges of the Omics and the BBMI.
References
More filters
Journal ArticleDOI
Event-related EEG/MEG synchronization and desynchronization: basic principles.
TL;DR: Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously.
Journal ArticleDOI
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Leigh R. Hochberg,Leigh R. Hochberg,Mijail D. Serruya,Gerhard Friehs,Gerhard Friehs,Jon A. Mukand,Jon A. Mukand,Maryam Saleh,Abraham H. Caplan,Almut Branner,David Chen,Richard D. Penn,John P. Donoghue +12 more
TL;DR: Initial results for a tetraplegic human using a pilot NMP suggest that NMPs based upon intracortical neuronal ensemble spiking activity could provide a valuable new neurotechnology to restore independence for humans with paralysis.
Journal ArticleDOI
A review of classification algorithms for EEG-based brain–computer interfaces
TL;DR: This paper compares classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG) in terms of performance and provides guidelines to choose the suitable classification algorithm(s) for a specific BCI.
Journal ArticleDOI
Brain Computer Interfaces, a Review
TL;DR: The state-of-the-art of BCIs are reviewed, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface.
Book
Toward brain-computer interfacing
TL;DR: This book was set in LaTex by the authors and was printed and bound in the United States of America Library of Congress Cataloging-in-Publication Data Towards Brain-Computer Interfacing.