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MATLAB-Based Tools for BCI Research
[chapter]
2010
Brain-Computer Interfaces
Preserved Fulltext
), a new BCI package that uses the data structures and extends the capabilities of the widely used EEGLAB signal processing environment. ...
We illustrate the relative simplicity of coding BCI feature extraction and classification under MATLAB (The Mathworks, Inc.) using a minimalist BCI example, and then describe BCILAB (Team PhyPa, Berlin ...
MatRiver is optimized for speed of computation and display; EEG preprocessing and most event-related data classifications can be performed in less than 10 ms on contemporary (2009) hardware. ...
doi:10.1007/978-1-84996-272-8_14
dblp:series/hci/DelormeKVSOZM10
fatcat:joir362aibajbgznxcmcxjcl5e
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
2019
Sensors
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Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment ...
This paper reviews state-of-the-art signal processing techniques for MI EEG-based BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used. ...
Today, the ultimate frontier between humans and computers is being bridged through the use of brain-computer interfaces (BCIs), which enable computers to be intentionally controlled via the monitoring ...
doi:10.3390/s19061423
fatcat:msk42smb7bd6ljqk4pxv6jy3ce
Integrating EEG and MEG signals to improve motor imagery classification in brain-computer interfaces
[article]
2018
arXiv
pre-print
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imagery-based brain-computer interfaces (BCIs). ...
We applied our approach to a group of 15 healthy subjects and found a significant classification performance enhancement as compared to standard single-modality approaches in the alpha and beta bands. ...
Introduction Brain-computer interfaces (BCIs) exploit the ability of subjects to modulate their brain activity through intentional mental effort, such as in motor imagery (MI). ...
arXiv:1711.07258v2
fatcat:jagr3rkrkbf3pe7u6yunafn6hm
Brain-actuated Control of Robot Navigation
[chapter]
2011
Advances in Robot Navigation
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equipment, iii) computer memory and processing speed, and iv) the performance of pattern recognition algorithms. ...
Two main families of brain interfaces exist according to the usual terminology, although the terms are often used interchangeably as well: i) Brain-computer interfaces (or BCIs) usually refers to brain-tocomputer ...
P300 This approach falls under the event-related potential category. ...
doi:10.5772/17401
fatcat:7ajtyy7i5fbergz22tz34u4tn4
Practical Neurophysiological Analysis of Readability as a Usability Dimension
[chapter]
2013
Lecture Notes in Computer Science
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The rapid evolution and growing availability of low-cost, easier to use devices and the accumulated knowledge in feature extraction and processing algorithms allow us to foresee the practicality of this ...
This paper discusses opportunities and feasibility of integrating neurophysiologic analysis methods, based on electroencephalography (EEG), in the current landscape of usability evaluation methods. ...
While the later signals provide the proper information for studying brain responses and are actually the main source of "input" in BCI (Brain Computer Interfaces), see [22] [23] [24] , the former analysis ...
doi:10.1007/978-3-642-39062-3_12
fatcat:dv6ioij5onfl5p23hpyotlsb6y
Facilitating Stroke Management using Modern Information Technology
2013
Journal of Stroke
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A mobile telemedicine system for assessing the National Institutes of Health Stroke Scale scores has shown higher correlation and fast assessment comparing with face-to-face method. ...
A computerized in-hospital alert system using computerized physician-order entry was shown to be effective in reducing the time intervals from hospital arrival to medical evaluations and thrombolytic treatment ...
The process of the "Brain salvage through Emergent Stroke Therapy (BEST)" program using computerized physician order entry (CPOE) 1 . ...
doi:10.5853/jos.2013.15.3.135
pmid:24396807
pmcid:PMC3859007
fatcat:26hxrxcxuvhg7kbob2vsafvqee
Heading for new shores! Overcoming pitfalls in BCI design
2016
Brain-Computer Interfaces
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He holds a PhD in computational neuroscience from the EPFL (2005). His research focuses on robust brain-machine interfaces and multimodal human-machine interaction. ...
In particular, the study of brain correlates of cognitive processes such as error recognition, learning and decision-making. As well as their use for interacting with complex neuroprosthetic devices. ...
This paper only reflects the authors' views and funding agencies are not liable for any use that may be made of the information contained herein. ...
doi:10.1080/2326263x.2016.1263916
pmid:29629393
pmcid:PMC5884128
fatcat:qffjwjo4yrda5ii2snrkexdj5y
Designing Future BCIs: Beyond the Bit Rate
[chapter]
2012
Towards Practical Brain-Computer Interfaces
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The scope of this chapter is limited to applications where a Brain-Computer Interface (BCI) is used as an explicit interaction technique. ...
Computer Interaction (HCI). ...
Section 9.3 emphasizes the focus on neuroergonomic principles in addition to usability principles especially for paradigms using Event-Related Potentials (ERP). ...
doi:10.1007/978-3-642-29746-5_9
fatcat:evkbnyvacjcbda2fqg3x263mme
Functional Near-Infrared Spectroscopy in Human-Robot Interaction
2013
Journal of Human-Robot Interaction
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The technology has already been used for brain-robot interfaces to affect robots' behaviors and as an evaluation tool for assessing brain activity during interactions. ...
(HMI), brain-computer interface (BCI), brain-machine interface (BMI) ...
The authors would also like to thank Megan Strait for help with identifying the challenges of fNIRS signal processing and for providing Figure 3 . ...
doi:10.5898/jhri.2.3.canning
fatcat:xfkvug33gbh57m4rajhvwakh7m
A novel onset detection technique for brain–computer interfaces using sound-production related cognitive tasks in simulated-online system
2017
Journal of Neural Engineering
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Results showed that the proposed onset detection technique and TFP performance metric have good potential for use in spBCIs. ...
Band power and a digital wavelet transform were used for feature extraction, and the Davies-Bouldin index was used for feature selection. Classification was performed using LDA. Main results. ...
Thus, there were three main functional requirements: a) The interface should minimise visual event-related potentials (VEP). b) The computer must be able to time-stamp events. ...
doi:10.1088/1741-2552/14/1/016019
pmid:28091395
fatcat:jhcowc3hffhftmr36pabv3woxm
Enhancing Sustained Attention
2021
Business & Information Systems Engineering
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A brain-computer interface is a system which uses physiological signals output by the user as an input. ...
This manuscript presents a Brain-Computer Interface (BCI) prototype which seeks to combat decrements in sustained attention during monitoring tasks within an enterprise system. ...
These same frequency bands have shown potential in learning contexts to enhance engagement with passive brain-computer interfaces (Andujar and Gilbert 2013) . ...
doi:10.1007/s12599-021-00701-3
fatcat:nislyivtyfhxpcc6woseozs6si
A Survey of Multi-Agent based Intelligent Decision Support System for Medical Classification Problems
2015
International Journal of Computer Applications
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Intelligent decision support system an automated judgment that supports decision making is composed of human and computer interaction to help in decision making accuracy. ...
This paper is a survey of the recent research in multiagent and intelligent decision support systems to support for classification problems. ...
Coordinator agent helps as matchmaker agent that usages Naïve Bayesian learning method for gain general information and selects the best service supplier agent using matchmaking mechanism. ...
doi:10.5120/ijca2015905529
fatcat:aqy5tvs65bc5bfzlxrnqo3m3bq
Affective level design for a role-playing videogame evaluated by a brain–computer interface and machine learning methods
2016
The Visual Computer
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An empirical investigation with a brain-computer interface headset has been conducted: by extracting numerical data features, machine learning techniques classify the different activities of the gaming ...
This work studies the affective ludology and shows two different game levels for Neverwinter Nights 2 developed with the aim to manipulate emotions; two sets of affective design guidelines are presented ...
A Brain-Computer Interface is a system that measures brain electrical activity allowing to retrieve information about feelings and emotions. ...
doi:10.1007/s00371-016-1320-2
fatcat:aubzpuxbs5bprlioyiovqudjve
Brain-Computer Interface: Advancement and Challenges
2021
Sensors
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Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain based on neuroscience, signal processing, biomedical sensors, hardware, etc. ...
Then, each element of BCI systems, including techniques, datasets, feature extraction methods, evaluation measurement matrices, existing BCI algorithms, and classifiers, are explained concisely. ...
The Brain-Computer Interface (BCI) system has directly connected the human brain and the outside environment. The BCI is a real-time brain-machine interface that interacts with external parameters. ...
doi:10.3390/s21175746
pmid:34502636
pmcid:PMC8433803
fatcat:gt5v46mr5nhjvptosklmvq2ria
Signal Processing and Classification Approaches for Brain-Computer Interface
[chapter]
2010
Intelligent and Biosensors
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Hoffman and the EPFL-Brain-Computer team for the data and the software given in (Hoffman et al., 2008) that they were used in this work. The authors would like also to thank Dr. A. ...
Bashashati for his authorization to use or modify some figures given in the paper to illustrate some sections given in this chapter. Anderson, C.W. & Sijercic, Z. (1996). ...
Signal Processing and Classification Approaches for Brain-Computer Interface, Intelligent and Biosensors, Vernon S. ...
doi:10.5772/7032
fatcat:jusb6fypyncytbn4d6bdvdk2xe
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