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State-of-the-Art in BCI Research: BCI Award 2010 [chapter]

Christoph Guger et al.
2011 Recent Advances in Brain-Computer Interface Systems  
A clinical study of motor imagery-based braincomputer interface for upper limb robotic rehabilitation, in Proc. EMBC, pp. 5981-5984.  ...  Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface, in Proc. IJCNN'08, pp. 2391-2398.  ...  Regarding brain-computer-interfaces, we have taken steps towards a non-invasive, highbandwidth, brain-computer-interface (BCI).  ... 
doi:10.5772/15017 fatcat:ztqjqr72sfhezl2m44pupzdlqy

State of the Art in BCI Research: BCI Award 2011 [chapter]

Christoph Guger, Brendan Allison, Günter Edlinger
2013 SpringerBriefs in Electrical and Computer Engineering  
A clinical study of motor imagery-based braincomputer interface for upper limb robotic rehabilitation, in Proc. EMBC, pp. 5981-5984.  ...  Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface, in Proc. IJCNN'08, pp. 2391-2398.  ...  Regarding brain-computer-interfaces, we have taken steps towards a non-invasive, highbandwidth, brain-computer-interface (BCI).  ... 
doi:10.1007/978-3-642-36083-1_1 fatcat:uzdzk36aencnvpyxq5lcufkmne

BCI-Based Consumers' Choice Prediction From EEG Signals: An Intelligent Neuromarketing Framework

Fazla Rabbi Mashrur, Khandoker Mahmudur Rahman, Mohammad Tohidul Islam Miya, Ravi Vaidyanathan, Syed Ferhat Anwar, Farhana Sarker, Khondaker A. Mamun
2022 Frontiers in Human Neuroscience  
Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how customers react to marketing stimuli.  ...  This work proposes a machine learning framework for predicting consumers' purchase intention (PI) and affective attitude (AA) from analyzing EEG signals.  ...  Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how customers react to marketing stimuli.  ... 
doi:10.3389/fnhum.2022.861270 pmid:35693537 pmcid:PMC9177951 fatcat:bxm3bljhizbetcindddajhynue

EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

Madiha Tariq, Pavel M. Trivailo, Milan Simic
2018 Frontiers in Human Neuroscience  
Over recent years, brain-computer interface (BCI) has emerged as an alternative communication system between the human brain and an output device.  ...  As a novel contribution, the reviewed BCI control paradigms for wearable LL and assistive-robots are presented by a general control framework fitting in hierarchical layers.  ...  ACKNOWLEDGMENTS Authors acknowledge the financial support received for this research provided by RMIT University Ph.D. International Scholarship (RPIS).  ... 
doi:10.3389/fnhum.2018.00312 pmid:30127730 pmcid:PMC6088276 fatcat:us3lwc23uvh47javazpf4ynm3y

Musical NeuroPicks: a consumer-grade BCI for on-demand music streaming services [article]

Fotis Kalaganis, Nikos Laskaris (1 and 3) AIIA Lab, Department of Informatics, Aristotle University of Thessaloniki, School of Music Studies, Aristotle University of Thessaloniki, Neuroinformatics GRoup, Aristotle University of Thessaloniki)
2017 arXiv   pre-print
We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener's subjective experience of music into scores that can be  ...  The second method, NeuroPicksVQ, offers prompt predictions of lower credibility and relies on a custom-built version of vector quantization procedure that facilitates a novel parameterization of the music-modulated  ...  Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.  ... 
arXiv:1709.01116v1 fatcat:mikhy4vfyfhn7kwrvka3cpgnsm

Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review

Haroon Khan, Noman Naseer, Anis Yazidi, Per Kristian Eide, Hafiz Wajahat Hassan, Peyman Mirtaheri
2021 Frontiers in Human Neuroscience  
Fusing EEG and fNIRS is a well-known and established methodology proven to enhance braincomputer interface (BCI) performance in terms of classification accuracy, number of control commands, and response  ...  In this article, we aim to shed light on the recent development in the analysis of human gait using a hybrid EEG-fNIRS-based BCI system.  ...  In recent years, brain-computer interface (BCI) development has played a vital role in investigating musculoskeletal gait and brain dysfunction disorders.  ... 
doi:10.3389/fnhum.2020.613254 pmid:33568979 pmcid:PMC7868344 fatcat:syxy7hu74fdj7e3azv7etcglya

Discriminative Codewaves: A Symbolic Dynamics Approach To Ssvep Recognition For Asynchronous Bci,

Konstantinos Georgiadis, Nikos Laskaris, Spiros Nikolopoulos, Ioannis Kompatsiaris
2017 Zenodo  
Steady-state visual evoked potential (SSVEP) is a very popular approach to establishing a communication pathway in braincomputer interfaces (BCIs), without any training requirements for the user.  ...  Our approach relies on (but not restricted to) single sensor traces, incorporates a novel description of brainwaves based on semi-supervised learning, and its great advantage stems from its potential for  ...  The partitioning of reconstructed phase space has been introduced as a simple and efficient strategy for effective description of brain-response dynamics [34] .  ... 
doi:10.5281/zenodo.1293841 fatcat:zlk3ndhnj5fh3ja5q7uczcjxau

Editorial: Error-related potentials: Challenges and applications

Gabriel Pires, Gabriel Pires, Miguel Castelo-Branco, Miguel Castelo-Branco, Christoph Guger, Giulia Cisotto
2022 Frontiers in Human Neuroscience  
of another person or an intelligent agent ("observation ErrP") or during the interaction with a Brain-Computer Interface (BCI) when the feedback is not the expected one ("interaction ErrP").  ...  ErrPs have already been applied as a proof-ofconcept in several applications, for detection and correction of BCI choices to increase reliability, to adapt BCI systems over time, or to make artificial  ...  Funding This work has been financially supported by Portuguese Foundation For Science and Technology (FCT) under grants B-RELIABLE: PTDC/EEIAUT/30935/2017 and BCI-CONNECT: PTDC/PSIGER/30852/2017.  ... 
doi:10.3389/fnhum.2022.984254 pmid:35927997 pmcid:PMC9343991 doaj:024f3260e25f44deb0a90ed58dcc1688 fatcat:sobxjyoqu5a77k4mbrztavpea4

Towards a Better Understanding of Human Reading Comprehension with Brain Signals

Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
2022 Proceedings of the ACM Web Conference 2022  
To this end, we propose a Uni ed framework for EEG-based Reading Comprehension Modeling (UERCM).  ...  These ndings imply that brain signals are valuable feedback for enhancing human-computer interactions during reading comprehension.  ...  With the advances of portable brain-computer interface (BCI) equipment, Liu et al. [33] suggest applying BCI in real-life settings.  ... 
doi:10.1145/3485447.3511966 fatcat:kfdheqkg6ndbtgesuwjuix5554

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

José Del R. Millán
2010 Frontiers in Neuroscience  
In recent years, new research has brought the field of electroencephalogram (EEG)-based brain-computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated  ...  prototypes such as brain-controlled wheelchairs, keyboards, and computer games.  ...  Buch et al. (2008) have shown that six out of eight chronic stroke patients suffering from a handplegia learned to control a magnetoencephalography-based BCI by MI.  ... 
doi:10.3389/fnins.2010.00161 pmid:20877434 pmcid:PMC2944670 fatcat:ncevpqe5afcplizxleit5kwx3i

Designing for uncertain, asymmetric control: Interaction design for brain–computer interfaces

J. Williamson, R. Murray-Smith, B. Blankertz, M. Krauledat, K.-R. Müller
2009 International Journal of Human-Computer Studies  
Brain-computer interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by thought.  ...  In particular, the asymmetry of feedback and control channels is highlighted as a key design constraint, which is especially obvious in current noninvasive brain-computer interfaces.  ...  Background:Brain-computer interfaces Brain-computer interfaces (BCIs) translate brain signals into control signals without intermediate motor action.  ... 
doi:10.1016/j.ijhcs.2009.05.009 fatcat:m5wbw5sehbag7o65jbb77vgwii

An Introductory Tutorial on Brain–Computer Interfaces and Their Applications

Andrea Bonci, Simone Fiori, Hiroshi Higashi, Toshihisa Tanaka, Federica Verdini
2021 Electronics  
Recent advances in biomedical engineering, computer science, and neuroscience are making braincomputer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental  ...  , ethical and legal issues related to braincomputer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications.  ...  A potential solution for restoring functions and to overcome motor impairments is to provide the brain with a new, nonmuscular communication and control channel, a direct brain-computer interface (BCI)  ... 
doi:10.3390/electronics10050560 fatcat:g2d57exmcbghlkf2rekmgdjhae

Fusion Convolutional Neural Network for Cross-Subject EEG Motor Imagery Classification

Karel Roots, Yar Muhammad, Naveed Muhammad
2020 Computers  
Braincomputer interfaces (BCIs) can help people with limited motor abilities to interact with their environment without external assistance.  ...  A major challenge in electroencephalogram (EEG)-based BCI development and research is the cross-subject classification of motor imagery data.  ...  Introduction A brain-computer interface (BCI) is a system that implements human-computer communication by interpreting brain signals.  ... 
doi:10.3390/computers9030072 fatcat:7ksnx6jo5jff3jkeorof6r7r3i

How does artificial intelligence contribute to iEEG research? [article]

Julia Berezutskaya, Anne-Lise Saive, Karim Jerbi, Marcel van Gerven
2022 arXiv   pre-print
We explain key machine learning concepts, specifics of processing and modeling iEEG data and details of state-of-the-art iEEG-based neurotechnology and brain-computer interfaces.  ...  identification of event-driven brain states for the development of clinical brain-computer interface systems (AI-iEEG for neurotechnology).  ...  We thank Mariska Vansteensel, Jordy Thielen, Linda Geerligs and Pieter Kubben for their helpful comments on the initial version of the manuscript.  ... 
arXiv:2207.13190v1 fatcat:kgc7gfhnpnhmpo2woh3nwk2hka

Brain–Computer Interfacing Using Functional Near-Infrared Spectroscopy (fNIRS)

Kogulan Paulmurugan, Vimalan Vijayaragavan, Sayantan Ghosh, Parasuraman Padmanabhan, Balázs Gulyás
2021 Biosensors  
Recent advancements in braincomputer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function.  ...  Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration  ...  Introduction A brain-computer interface (BCI) is a system that acquires signals from the brain, translates the signals, and outputs to devices in order to enact a desired action [1] .  ... 
doi:10.3390/bios11100389 pmid:34677345 pmcid:PMC8534036 fatcat:c6k3tj7ghngbfkwl3i3ntwq5he
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