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State-of-the-Art in BCI Research: BCI Award 2010
[chapter]
2011
Recent Advances in Brain-Computer Interface Systems
Preserved Fulltext
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]
2013
SpringerBriefs in Electrical and Computer Engineering
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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
2022
Frontiers in Human Neuroscience
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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
2018
Frontiers in Human Neuroscience
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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]
2017
arXiv
pre-print
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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
2021
Frontiers in Human Neuroscience
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Fusing EEG and fNIRS is a well-known and established methodology proven to enhance brain–computer 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,
2017
Zenodo
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Steady-state visual evoked potential (SSVEP) is a very popular approach to establishing a communication pathway in brain–computer 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
2022
Frontiers in Human Neuroscience
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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
2022
Proceedings of the ACM Web Conference 2022
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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
2010
Frontiers in Neuroscience
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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
2009
International Journal of Human-Computer Studies
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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
2021
Electronics
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Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental ...
, ethical and legal issues related to brain–computer 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
2020
Computers
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Brain–computer 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]
2022
arXiv
pre-print
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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)
2021
Biosensors
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Recent advancements in brain–computer 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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