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A review of classification algorithms for EEG-based brain–computer interfaces

F Lotte, M Congedo, A Lécuyer, F Lamarche, B Arnaldi
<span title="2007-01-31">2007</span> <i title="IOP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tpqlgxji7rezlnmgkbv4hfla3a" style="color: black;">Journal of Neural Engineering</a> </i> &nbsp;
In this paper we review classification algorithms used to design Brain-Computer Interface (BCI) systems based on ElectroEncephaloGraphy (EEG).  ...  Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.  ...  Brain-Computer Interfaces seen as a pattern recognition system The very aim of BCI is to translate brain activity into a command for a computer.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1741-2560/4/2/r01">doi:10.1088/1741-2560/4/2/r01</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/17409472">pmid:17409472</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7i7bfzwymrcbfnbgelnmvshdai">fatcat:7i7bfzwymrcbfnbgelnmvshdai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923224821/https://hal.inria.fr/inria-00134950/document" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f0/36/f036e558ef61af23d163a107b6a8f01718177b8c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1741-2560/4/2/r01"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> iop.org </button> </a>

Multiband Common Spatial Pattern based EEG Classification for Brain-Computer Interface

Md. Sujan Ali, Mst. Jannatul Ferdous
<span title="">2017</span> <i title="IOSR Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vabuspdninc75epczdurccts4u" style="color: black;">IOSR Journal of Computer Engineering</a> </i> &nbsp;
Thispaper presents a novel method for electroencephalography (EEG) based motor imagery classification for brain computer interface (BCI) implementation using the potential features extracted bandspecific  ...  The recorded EEG signal is bandpass-filtered into multiple subbands to capture the related rhythmic components of brain signals. The CSP features are then extracted from each of these bands.  ...  Acknowledgements This research work supported by the Information and Communication Technology (ICT) division of the ministry of Post, Telecommunication and Information Technology, Bangladesh.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-1902059099">doi:10.9790/0661-1902059099</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gt45hzqyvjhevefchxr3vp7el4">fatcat:gt45hzqyvjhevefchxr3vp7el4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602121918/http://www.iosrjournals.org/iosr-jce/papers/Vol19-issue2/Version-5/P1902059099.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/83/33/83333b126b07cd90f4173d8c2fd2764766796f1b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-1902059099"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

An effective classification framework for brain-computer interface system design based on combining of fNIRS and EEG signals

Adi Alhudhaif
<span title="2021-05-06">2021</span> <i title="PeerJ"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zs2czkfyybggbpvr26rbyxpsjy" style="color: black;">PeerJ Computer Science</a> </i> &nbsp;
The brain-computer interface (BCI) is a relatively new but highly promising special field that is actively used in basic neuroscience.  ...  BCI includes interfaces for human-computer communication based directly on neural activity concerning mental processes. Fundamental BCI components consist of different units.  ...  BCI includes interfaces for human-computer communication based directly on neural activity concerning mental processes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7717/peerj-cs.537">doi:10.7717/peerj-cs.537</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34013040">pmid:34013040</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8114820/">pmcid:PMC8114820</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/o5yquxnnffhp7ipxcvnhtmct4e">fatcat:o5yquxnnffhp7ipxcvnhtmct4e</a> </span>
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Movement-Imagery Brain-Computer Interface: EEG Classification of Beta Rhythm Synchronization Based on Cumulative Distribution Function

Teruyoshi SASAYAMA, Tetsuo KOBAYASHI
<span title="">2011</span> <i title="Institute of Electronics, Information and Communications Engineers (IEICE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xosmgvetnbf4zpplikelekmdqe" style="color: black;">IEICE transactions on information and systems</a> </i> &nbsp;
We developed a novel movement-imagery-based braincomputer interface (BCI) for untrained subjects without employing machine learning techniques. The development of BCI consisted of several steps.  ...  It has also been demonstrated that the highest accuracy was achieved even though subjects had never participated in movement imageries. key words: electroencephalogram (EEG), brain-machine interface (BCI  ...  Introduction A brain-computer interface (BCI), also known as a brainmachine interface (BMI), is a system that enables communication using signals from the brain [1] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1587/transinf.e94.d.2479">doi:10.1587/transinf.e94.d.2479</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nhxkj3nc4ffnfpdru7wzzv4ay4">fatcat:nhxkj3nc4ffnfpdru7wzzv4ay4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181101050042/https://www.jstage.jst.go.jp/article/transinf/E94.D/12/E94.D_12_2479/_pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/38/fc/38fc3ed23d545f69238491b148a432e33d041eb1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1587/transinf.e94.d.2479"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

Abeer Al-Nafjan, Manar Hosny, Yousef Al-Ohali, Areej Al-Wabil
<span title="2017-12-01">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification.  ...  Using basic search settings, we input search terms and phrases, such as: affective or emotion; emotion detection or recognition; EEG or Electroencephalography; and, Brain-computer interface, Passive BCI  ...  Introduction A Brain Computer Interface (BCI) is a system that takes a biosignal, measured from a person, and predicts (in real-time) certain aspects of the person's cognitive state [1, 2] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app7121239">doi:10.3390/app7121239</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qsgvge5dl5gx3bthb5j63pir4m">fatcat:qsgvge5dl5gx3bthb5j63pir4m</a> </span>
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A review of adaptive feature extraction and classification methods for EEG-based brain-computer interfaces

Shiliang Sun, Jin Zhou
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qm5nunzmyva4tfjekdcm34uvhq" style="color: black;">2014 International Joint Conference on Neural Networks (IJCNN)</a> </i> &nbsp;
A brain-computer interface (BCI) is a system that allows its users to control external devices which are independent of peripheral nerves and muscles with brain activities.  ...  This paper reviews representative adaptive feature extraction and classification methods for EEG-based BCIs and further discusses some important open problems which can hopefully be useful to promote the  ...  INTRODUCTION A brain-computer interface (BCI) is a communication and control system in which messages or commands do not depend on the brain's normal output pathways of peripheral nerves and muscles [  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2014.6889525">doi:10.1109/ijcnn.2014.6889525</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ijcnn/SunZ14a.html">dblp:conf/ijcnn/SunZ14a</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hzg5xnit5rbxfhgpl4iyopyvr4">fatcat:hzg5xnit5rbxfhgpl4iyopyvr4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829211927/http://www.cst.ecnu.edu.cn/~slsun/pubs/BCIReview_IJCNN14.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/57/69/5769887df830d16def30e4af2a0d7207636ff434.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2014.6889525"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

F Lotte, L Bougrain, A Cichocki, M Clerc, M Congedo, A Rakotomamonjy, F Yger
<span title="2018-04-16">2018</span> <i title="IOP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tpqlgxji7rezlnmgkbv4hfla3a" style="color: black;">Journal of Neural Engineering</a> </i> &nbsp;
Introduction A brain-computer interface (BCI) can be defined as a system that translates the brain activity patterns of a user into messages or commands for an interactive application, this activity being  ...  In many applications such as computer vision, biomedical engineering or brain-computer interfaces, this hypothesis is often violated.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1741-2552/aab2f2">doi:10.1088/1741-2552/aab2f2</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29488902">pmid:29488902</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7brd44bmqnegzov6mi4idtwjbi">fatcat:7brd44bmqnegzov6mi4idtwjbi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190426230631/https://iopscience.iop.org/article/10.1088/1741-2552/aab2f2/pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1b/ce/1bce068e58218dc20e73bc596e236f05fd89e667.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1741-2552/aab2f2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> iop.org </button> </a>

EEG-Based Classification of Motor Imagery Tasks Using Fractal Dimension and Neural Network for Brain-Computer Interface

M. PHOTHISONOTHAI, M. NAKAGAWA
<span title="2008-01-01">2008</span> <i title="Institute of Electronics, Information and Communications Engineers (IEICE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xosmgvetnbf4zpplikelekmdqe" style="color: black;">IEICE transactions on information and systems</a> </i> &nbsp;
SUMMARY In this study, we propose a method of classifying a spontaneous electroencephalogram (EEG) approach to a brain-computer interface.  ...  (FD), neural network, independent component analysis Introduction A novel communication channel between a human brain and a computer is called a brain-computer interface (BCI).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/ietisy/e91-d.1.44">doi:10.1093/ietisy/e91-d.1.44</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xu3bvybphvdhznhfwi52oephoe">fatcat:xu3bvybphvdhznhfwi52oephoe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181103164405/https://www.jstage.jst.go.jp/article/transinf/E91.D/1/E91.D_1_44/_pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/11/43/114380dffeeacb17fe9c682d6635dfe1cfe2db74.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/ietisy/e91-d.1.44"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Motor imagery classification in Brain computer interface (BCI) based on EEG signal by using machine learning technique

N. E. Md Isa, A. Amir, M. Z. Ilyas, M. S. Razalli
<span title="2019-03-01">2019</span> <i title="Institute of Advanced Engineering and Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mwj5yys4mnek7al64kpw5psjqi" style="color: black;">Bulletin of Electrical Engineering and Informatics</a> </i> &nbsp;
This paper focuses on classification of motor imagery in Brain Computer Interface (BCI) by using classifiers from machine learning technique.  ...  The BCI system consists of two main steps which are feature extraction and classification.  ...  ACKNOWLEDGEMENTS The Dataset 1 of BCI Competition IV is provided by Berlin BCI group (Germany).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11591/eei.v8i1.1402">doi:10.11591/eei.v8i1.1402</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wuc74ooibfavhnxwatpsm72cmm">fatcat:wuc74ooibfavhnxwatpsm72cmm</a> </span>
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Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment

Dong Wen, Peilei Jia, Qiusheng Lian, Yanhong Zhou, Chengbiao Lu
<span title="2016-07-08">2016</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xyafp6gbr5et3ghi4kqddnyolm" style="color: black;">Frontiers in Aging Neuroscience</a> </i> &nbsp;
SRC methods have been used to analyze the EEG signals of epilepsy, cognitive impairment and brain computer interface (BCI), which made rapid progress including the improvement in computational accuracy  ...  At present, the sparse representation-based classification (SRC) has become an important approach in electroencephalograph (EEG) signal analysis, by which the data is sparsely represented on the basis  ...  ), Alzheimer's disease (AD) and brain computer interface (BCI) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnagi.2016.00172">doi:10.3389/fnagi.2016.00172</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27458376">pmid:27458376</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4937019/">pmcid:PMC4937019</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vn5jpvjzfnejvgmtojqngbtcru">fatcat:vn5jpvjzfnejvgmtojqngbtcru</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830040013/https://fjfsdata01prod.blob.core.windows.net/articles/files/186601/pubmed-zip/.versions/1/.package-entries/fnagi-08-00172/fnagi-08-00172.pdf?sv=2015-12-11&amp;sr=b&amp;sig=rdz1FrHIYkyjSswlwwyuurVsPio1xFA%2FeCnBiClZqd8%3D&amp;se=2017-08-30T04%3A00%3A14Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fnagi-08-00172.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0b/8c/0b8c1fce61ea47f83e79d50862a7288dbabdc2b8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnagi.2016.00172"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937019" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A review of classification algorithms for EEG-based brain-computer interfaces A review of classification algorithms for EEG-based brain A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces

Fabien Lotte, Marco Congedo, Anatole Lécuyer, Fabrice Lamarche, Bruno Arnaldi, Fabien Lotte, Marco Congedo, Anatole Lécuyer, Fabrice Lamarche, Bruno, F Lotte, M Congedo (+3 others)
<span title="">2007</span> <i title="IOP Publishing"> Journal of Neural Engineering </i> &nbsp; <span class="release-stage">unpublished</span>
In this paper we review classification algorithms used to design Brain-Computer Interface (BCI) systems based on ElectroEncephaloGraphy (EEG).  ...  Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.  ...  Brain-Computer Interfaces seen as a pattern recognition system The very aim of BCI is to translate brain activity into a command for a computer.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yudqhvkrvfbhlfy4xs2rtzbzze">fatcat:yudqhvkrvfbhlfy4xs2rtzbzze</a> </span>
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The Use of Fuzzy Inference Systems for Classification in EEG-based Brain-Computer Interfaces. 3rd International Brain-Computer Interfaces Workshop and Training Course

Fabien Lotte, Fabien, F Lotte
<span title="">2006</span> <span class="release-stage">unpublished</span>
This paper introduces the use of a Fuzzy Inference System (FIS) for classification in EEG-based Brain-Computer Interfaces (BCI) systems.  ...  Thus, FIS-based classification is suitable for BCI design. Furthermore, FIS algorithms have two additionnal advantages: they are readable and easily extensible.  ...  CONCLUSION In this paper we have described the use of a Fuzzy Inference System (FIS) for classification in Brain-Computer Interfaces.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mfce5pu775f4xnkdbvsfzgtnje">fatcat:mfce5pu775f4xnkdbvsfzgtnje</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180416224754/https://hal.inria.fr/file/index/docid/134951/filename/lotte06.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/88/02/8802ef65b98b9c2e3be55f4d58a47fad00b19394.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a>

Single Trial Classification of EEG in Predicting Intention and Direction of Wrist Movement: Translation Toward Development of Four-Class Brain Computer Interface System Based on a Single Limb

Syahrull Hi, Fi Syam, Heba Lakany, B Conway
<span class="release-stage">unpublished</span>
Keywords-Brain computer interface (BCI) ; wrist movement; motor imagery; Electroencephalography (EEG); intention of movement.  ...  Brain-computer interfaces (BCI) are paradigms that offer an alternative communication channel between neural activity generated in the brain and the users' external environment.  ...  INTRODUCTION A Brain Computer Interface (BCI) system applies and decodes the brain signature obtained from an electroencephalogram (EEG) signal and translates this information into a usable signal such  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tk2gznin2bcojn4yskv7nuldea">fatcat:tk2gznin2bcojn4yskv7nuldea</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180415231338/http://www.thinkmind.org/download.php?articleid=cognitive_2016_5_30_40085" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6b/27/6b2772f52da75f8431cf76a8e83275583a9c832b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a>

Technology Development for Unblessed People using BCI: A Survey

Mandeep Kaur, P. Ahmed, M. Qasim Rafiq
<span title="2012-02-29">2012</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
The Brain Computer Interface (BCI) systems enable unblessed people to operate devices and applications through their mental activities.  ...  Here, a general Electro-Encephalogram (EEG) based BCI system is discussed which can assist the paralyzed or physically or mentally challenged people in performing their various routine tasks or applications  ...  An EEG-based mouse designed for Brain-computer Interface (BCI) system to move a cursor on a computer display. [20] An EEG-based Brain-Computer Interface (BCI) system for on-line controlling the hand movement  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/4920-7142">doi:10.5120/4920-7142</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tp5ymaxvcjaubeg7cvuu2mmfmm">fatcat:tp5ymaxvcjaubeg7cvuu2mmfmm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809133655/http://research.ijcaonline.org/volume40/number1/pxc3877142.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/18/75/18751284d048bf2853fa7c13819c0468193abfc4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/4920-7142"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

EEG based brain-computer interface control applications: A comprehensive review

Abdullah Bilal Aygun, Ahmet Resit Kavsaoglu, Kemal Polat
<span title="2021-05-31">2021</span> <i title="Journal of Bionic Memory"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xlxgxhdnxja4zcpgo7jq64asu4" style="color: black;">Journal of Bionic Memory</a> </i> &nbsp;
The purpose of this study is to talk about both the type of brain signals used in the brain computer interface and the machine learning techniques used in the classification of these signals.  ...  Brain computer interfaces (BCI) is a tool that can make user requests to computerized systems by directly processing brain signals.  ...  The types of EEG signal classified used in BCI The purpose of this study is to investigate which classification method is widely preferred in EEG signal types used practically in brain computer interfaces  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.53545/jbm.2021175573">doi:10.53545/jbm.2021175573</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4kth7utxzrhzpjtw57u3pf4isy">fatcat:4kth7utxzrhzpjtw57u3pf4isy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220430064046/http://jbionicmemory.com/index.php/jbm/article/download/4/4/192" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c2/cf/c2cf416d5c9fc7dcd92420e1e0659e2cf3921399.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.53545/jbm.2021175573"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>
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