9,142 Hits in 9.7 sec

MATLAB-Based Tools for BCI Research [chapter]

Arnaud Delorme, Christian Kothe, Andrey Vankov, Nima Bigdely-Shamlo, Robert Oostenveld, Thorsten O. Zander, Scott Makeig
2010 Brain-Computer Interfaces  
), 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

Natasha Padfield, Jaime Zabalza, Huimin Zhao, Valentin Masero, Jinchang Ren
2019 Sensors  
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]

Marie-Constance Corsi, Mario Chavez, Denis Schwartz, Laurent Hugueville, Ankit N. Khambhati, Danielle S. Bassett, Fabrizio De Vico Fallani
2018 arXiv   pre-print
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]

Francisco Sepulveda
2011 Advances in Robot Navigation  
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]

Inês Isabel Pimentel Oliveira, Nuno Manuel Guimarães
2013 Lecture Notes in Computer Science  
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

Hyo Suk Nam, Eunjeong Park, Ji Hoe Heo
2013 Journal of Stroke  
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

Ricardo Chavarriaga, Melanie Fried-Oken, Sonja Kleih, Fabien Lotte, Reinhold Scherer
2016 Brain-Computer Interfaces  
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]

Melissa Quek, Johannes Höhne, Roderick Murray-Smith, Michael Tangermann
2012 Towards Practical Brain-Computer Interfaces  
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

Cody Canning, Matthias Scheutz
2013 Journal of Human-Robot Interaction  
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

YoungJae Song, Francisco Sepulveda
2017 Journal of Neural Engineering  
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

Théophile Demazure, Alexander Karran, Pierre-Majorique Léger, Élise Labonté-LeMoyne, Sylvain Sénécal, Marc Fredette, Gilbert Babin
2021 Business & Information Systems Engineering  
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

Hanaa Salem, Gamal Attiya, Nawal El-Fishawy
2015 International Journal of Computer Applications  
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

Fabrizio Balducci, Costantino Grana, Rita Cucchiara
2016 The Visual Computer  
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

M F Mridha, Sujoy Chandra Das, Muhammad Mohsin Kabir, Aklima Akter Lima, Md Rashedul Islam, Yutaka Watanobe
2021 Sensors  
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]

Tarik Al-ani, Dalila Tr
2010 Intelligent and Biosensors  
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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