Relevant bibliographies by topics / Brain-Computer Interfaces (BCIs) / Dissertations / Theses
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Dissertations / Theses on the topic 'Brain-Computer Interfaces (BCIs)'

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Published: 1 March 2025
Last updated: 25 July 2025

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1

Botrel, Loic [Verfasser], Andrea [Gutachter] Kübler, and Johannes [Gutachter] Hewig. "Brain-computer interfaces (BCIs) based on sensorimotor rhythms - Evaluating practical interventions to improve their performance and reduce BCI inefficiency / Loic Botrel ; Gutachter: Andrea Kübler, Johannes Hewig." Würzburg : Universität Würzburg, 2018. http://d-nb.info/1168146445/34.

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Yamamoto, Maria Sayu. "Addressing the Large Variability of EEG Data with Riemannian Geometry : Toward Designing Reliable Brain-Computer Interfaces." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG098.

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Les interfaces cerveau-ordinateur (BCI) basées sur la géométrie riemannienne ont gagné en popularité au cours de la dernière décennie, démontrant des améliorations significatives dans divers contextes de classification des BCI. Malgré ces avancées, les systèmes BCI restent insuffisamment fiables pour des applications pratiques. L'une des principales difficultés auxquelles les BCI sont confrontées est la variabilité considérable de l'électroencéphalogramme (EEG). Cette variabilité est censée être encore plus prononcée lorsque les systèmes BCI sont utilisés sur plusieurs jours ou en dehors des e
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Mindermann, Björn [Verfasser], Axel [Akademischer Betreuer] Gräser, Axel [Gutachter] Gräser, and Canan [Gutachter] Basar-Eroglu. "Untersuchung eines hybriden Brain-Computer Interfaces (BCIs) zur optimalen Auslegung als Mensch-Maschine-Schnittstelle / Björn Mindermann ; Gutachter: Axel Gräser, Canan Basar-Eroglu ; Betreuer: Axel Gräser." Bremen : Staats- und Universitätsbibliothek Bremen, 2018. http://d-nb.info/1159699917/34.

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Bhalotiya, Anuj Arun. "Brain Computer Interface (BCI) Applications: Privacy Threats and Countermeasures." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984122/.

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In recent years, brain computer interfaces (BCIs) have gained popularity in non-medical domains such as the gaming, entertainment, personal health, and marketing industries. A growing number of companies offer various inexpensive consumer grade BCIs and some of these companies have recently introduced the concept of BCI "App stores" in order to facilitate the expansion of BCI applications and provide software development kits (SDKs) for other developers to create new applications for their devices. The BCI applications access to users' unique brainwave signals, which consequently allows them t
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Petrucci, Maila. "Sistemi Brain Computer Interface: dalla macchina al paziente." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10137/.

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C’è un crescente interesse nella comunità scientifica per l’applicazione delle tecniche della bioingegneria nel campo delle interfacce fra cervello e computer. Questo interesse nasce dal fatto che in Europa ci sono almeno 300.000 persone con paralisi agli arti inferiori, con una età media piuttosto bassa (31 anni), registrandosi circa 5.000 nuovi casi ogni anno, in maggioranza dovuti ad incidenti automobilistici. Tali lesioni traumatiche spinali inducono delle disfunzioni sensoriali a causa dell’interruzione tra gli arti e i centri sopraspinali. Per far fronte a questi problemi gli scienziati
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Del, Monte Tamara. "Utilizzo dell'elettroencefalografia per la brain-computer interface." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9220/.

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Con Brain-Computer Interface si intende un collegamento diretto tra cervello e macchina, che essa sia un computer o un qualsiasi dispositivo esterno, senza l’utilizzo di muscoli. Grazie a sensori applicati alla cute del cranio i segnali cerebrali del paziente vengono rilevati, elaborati, classificati (per mezzo di un calcolatore) e infine inviati come output a un device esterno. Grazie all'utilizzo delle BCI, persone con gravi disabilità motorie o comunicative (per esempio malati di SLA o persone colpite dalla sindrome del chiavistello) hanno la possibilità di migliorare la propria qualità di
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Jeunet, Camille. "Understanding & Improving Mental-Imagery Based Brain-Computer Interface (Mi-Bci) User-Training : towards A New Generation Of Reliable, Efficient & Accessible Brain- Computer Interfaces." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0221/document.

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Les Interfaces Cerveau-Ordinateur basées sur l’Imagerie Mentale (IM-ICO) permettent auxutilisateurs d’interagir uniquement via leur activité cérébrale, grâce à la réalisation de tâchesd’imagerie mentale. Cette thèse se veut contribuer à l’amélioration des IM-ICO dans le but deles rendre plus utilisables. Les IM-ICO sont extrêmement prometteuses dans de nombreuxdomaines allant de la rééducation post-AVC aux jeux-vidéo. Malheureusement, leurdéveloppement est freiné par le fait que 15 à 30% des utilisateurs seraient incapables de lescontrôler. Nombre de travaux se sont focalisés sur l’amélioratio
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Sicbaldi, Marcello. "Brain-Computer Interface per riabilitazione motoria e cognitiva." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18556/.

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Pazienti con lesioni cerebrali o spinali possono essere affetti da gravi deficit nelle funzioni sensoriali, motorie e comunicative; sono perciò sempre più necessarie tecniche di riabilitazione avanzate, personalizzate e adattative, per limitare i deficit insorti e restituire al paziente una vita il più normale possibile. Negli ultimi decenni, numerosi gruppi di ricerca hanno sviluppato Brain-Computer Interface (BCI) basate sul segnale elettroencefalografico (EEG) con l’obbiettivo di fornire mezzi di comunicazione o riabilitazione motoria funzionale. Tuttavia, le tecnologie BCI hanno un ampio p
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JUBIEN, Guillaume. "Decoding Electrocorticography Signals by Deep Learning for Brain-Computer Interface." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-243903.

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Brain-Computer Interface (BCI) offers the opportunity to paralyzed patients to control their movements without any neuromuscular activity. Signal processing of neuronal activity enables to decode movement intentions. Ability for patient to control an effector is closely linked to this decoding performance. In this study, I tackle a recent way to decode neuronal activity: Deep learning. The study is based on public data extracted by Schalk et al. for BCI Competition IV. Electrocorticogram (ECoG) data from three epileptic patients were recorded. During the experiment setup, the team asked subjec
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Bodranghien, Florian. "A novel brain-computer interface (BCI) to assist upper limb pointing movements." Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261534.

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Human to computer interaction only using thoughts is no longer a science fiction topic and recent progress made in this field are astounding. This work shows the creation of a novel upper limb pointing movement performance quantification platform (eCAM test) and its validation on a group of healthy subjects. After that, it shows that functional electrical stimulation (FES) enhances these upper limbs movements performance. Furthermore, this work shows that anodal transcranial direct current stimulation (atDCS) of the cerebellum impacts brain rhythms as well as postural tremor on a patient. Also
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11

Szafir, Daniel J. "Non-Invasive BCI through EEG." Thesis, Boston College, 2010. http://hdl.handle.net/2345/1208.

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Thesis advisor: Robert Signorile<br>It has long been known that as neurons fire within the brain they produce measurable electrical activity. Electroencephalography (EEG) is the measurement and recording of these electrical signals using sensors arrayed across the scalp. Though there is copious research in using EEG technology in the fields of neuroscience and cognitive psychology, it is only recently that the possibility of utilizing EEG measurements as inputs in the control of computers has emerged. The idea of Brain-Computer Interfaces (BCIs) which allow the control of devices using brain s
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Allison, Brendan. "P3 or not P3 : toward a better P300 BCI /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2003. http://wwwlib.umi.com/cr/ucsd/fullcit?p3090451.

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13

Clanton, Samuel T. "Brain-Computer Interface Control of an Anthropomorphic Robotic Arm." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/170.

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This thesis describes a brain-computer interface (BCI) system that was developed to allow direct cortical control of 7 active degrees of freedom in a robotic arm. Two monkeys with chronic microelectrode implants in their motor cortices were able to use the arm to complete an oriented grasping task under brain control. This BCI system was created as a clinical prototype to exhibit (1) simultaneous decoding of cortical signals for control of the 3-D translation, 3-D rotation, and 1-D finger aperture of a robotic arm and hand, (2) methods for constructing cortical signal decoding models based on
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14

Lind, Carl Jonas. "Brain Computer Interface (BCI) : - Översiktsartikel utifrån ett neuropsykologiskt perspektiv med tillämpningar och enkätundersökning." Thesis, Stockholms universitet, Psykologiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-186099.

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Syftet med uppsatsen är att ge en uppdaterad översikt av området BCI (Brain Computer Interface) och undersöka vad som hänt sedan begreppet introducerades i forskningssammanhang; vilka praktiska resultat forskningen lett till och vilka tillämpningar som tillkommit. Metoden som företrädesvis används är litteraturstudie som tecknar bakgrund och enkät. Därefter följer en diskussion där utmaningar för framtiden, potential och tillämpningar i BCI-tekniken behandlas utifrån ett neuropsykologiskt perspektiv. Kommer BCI-tekniken att implementeras på samma sätt som radio, TV och telekommunikationer i sa
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Belluomo, Paola. "New proposals for EEG and fMRI based Brain Computer Interface technology." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1305.

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In this manuscript three related aspects of research on BCI systems were discussed. These aspects were the evaluation of a nonlinear feature extraction algorithm for BCI, the analysis of the functional connectivity between the signals acquired in different brain regions when a user performs an operant conditioning paradigm with fMRI based BCI technology, and the development of BCIs applications for disabled subjects. We have introduced a new EEG signals features extraction techniques based on nonlinear time series analysis. This signal processing approach was tested offline considering three s
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Schwartz, Nicholas Edward. "P300-Based BCI Performance Prediction through Examination of Paradigm Manipulations and Principal Components Analysis." Digital Commons @ East Tennessee State University, 2010. https://dc.etsu.edu/etd/1775.

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Severe neuromuscular disorders can produce locked-in syndrome (LIS), a loss of nearly all voluntary muscle control. A brain-computer interface (BCI) using the P300 event-related potential provides communication that does not depend on neuromuscular activity and can be useful for those with LIS. Currently, there is no way of determining the effectiveness of P300-based BCIs without testing a person's performance multiple times. Additionally, P300 responses in BCI tasks may not resemble the typical P300 response. I sought to clarify the relationship between the P300 response and BCI task paramete
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Boldeanu, Silvia. "Merging brain-computer interfaces and virtual reality : A neuroscientific exploration." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15774.

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Brain-computer interfaces (BCIs) blend methods and concepts researched by cognitive neuroscience, electrophysiology, computer science and engineering, resulting in systems of bi-directional information exchange directly between brain and computer. BCIs contribute to medical applications that restore communication and mobility for disabled patients and provide new forms of sending information to devices for enhancement and entertainment. Virtual reality (VR) introduces humans into a computer-generated world, tackling immersion and involvement. VR technology extends the classical multimedia expe
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Mattiaccia, Francesca. "Brain Computer Interface: una nuova tecnologia per la medicina riabilitativa." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19014/.

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La Brain Computer Interface (BCI) è una delle nuove tecnologie che si sta diffondendo negli ultimi anni con nuove ricerche e nuove applicazioni. La ricerca è continua e sempre con l'obiettivo di rendere la BCI uno strumento a disposizione di tutti e applicabile in molti contesti sfruttando la capacità di adattamento del dispositivo. In questo lavoro è stata fatta una prima introduzione alla struttura, alle caratteristiche di acquisizione e gestione del segnale e alle diverse tipologie di BCI oggi a disposizione; successivamente si è focalizzata l'attenzione sulle più recenti applicazioni e in
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Jarmolowska, Joanna. "Nuovi sistemi per la comunicazione alternativa basati su Brain Computer Interface." Doctoral thesis, Università degli studi di Trieste, 2014. http://hdl.handle.net/10077/10149.

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2011/2012<br>La comunicazione alternativa attraverso le BCIs può risultare uno strumento per agevolare le condizioni di vita di pazienti affetti dai disturbi neurologici. La comunicazione via BCI è ancora molto più lenta rispetto alla comunicazione con il linguaggio naturale. L’obiettivo di questo lavoro di tesi si inserisce in tale ambito, consistendo nello sviluppo di nuove applicazioni in grado di migliorare la velocità di comunicazione con utilizzo delle BCIs. Sono stati sviluppati due sistemi di comunicazione alternativa basati sulla componente P300. Il primo sistema chiamato ‘Multimenu
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Hagerty-Hoff, Christopher V. "MODIFICATION AND EVALUATION OF A BRAIN COMPUTER INTERFACE SYSTEM TO DETECT MOTOR INTENTION." VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/3746.

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It is widely understood that neurons within the brain produce electrical activity, and electroencephalography—a technique used to measure biopotentials with electrodes placed upon the scalp—has been used to observe it. Today, scientists and engineers work to interface these electrical neural signals with computers and machines through the field of Brain-Computer Interfacing (BCI). BCI systems have the potential to greatly improve the quality of life of physically handicapped individuals by replacing or assisting missing or debilitated motor functions. This research thus aims to further improve
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CISOTTO, GIULIA. "Movement-related desynchronization detection in Brain-Computer Interface applications for post-stroke motor rehabilitation." Doctoral thesis, Università di Padova, 2014. http://hdl.handle.net/10281/367531.

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Neurological degenerative diseases like stroke, Alzheimer, Amyothrophic Lateral Sclerosis (ALS), Parkinson and many others are constantly increasing their incidence in the world health statistics as far as the mean age of the global population is getting higher and higher. This leads to a general need for effective, at-home and low-cost rehabilitative and health-daily-care tools. The latter should consist either of technological devices implemented for operating in a remote way, i.e. tele-medicine is quickly spreading around the world, or very-advanced computer-based and robotic systems to re
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Erdogan, Hasan Balkar. "A Design And Implementation Of P300 Based Brain-computer Interface." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611141/index.pdf.

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In this study, a P300 based Brain-Computer Interface (BCI) system design is realized by the implementation of the Spelling Paradigm. The main challenge in these systems is to improve the speed of the prediction mechanisms by the application of different signal processing and pattern classification techniques in BCI problems. The thesis study includes the design and implementation of a 10 channel Electroencephalographic (EEG) data acquisition system to be practically used in BCI applications. The electrical measurements are realized with active electrodes for continuous EEG recording. The data
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Mondelli, Giuseppina Ester. "Brain Computer Interface: una nuova frontiera per la riabilitazione del paziente." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Le interfacce cervello-computer o brain-computer interface sono dei sistemi che attraverso la misurazione e l'analisi di segnali provenienti dall'attività cerebrale traducono in azione il segnale registrato, realizzando un canale di comunicazione alternativo alle normali vie neurali. L'obbiettivo di questa tesi è quello di analizzare e differenziare le varie tipologie di BCI dal punto di vista della struttura e dei metodi di acquisizione del segnale e infine classificarle a seconda della funzione che andranno a ricoprire: motoria o cognitiva. Le Interfacce cervello-computer nascono come una te
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Renfrew, Mark E. "A Comparison of Signal Processing and Classification Methods for Brain-Computer Interface." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1246474708.

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George, Laurent. "Contribution to the study of active and passive brain-computer interfaces for interacting with virtual environments based on EEG and mental workkload." Rennes, INSA, 2012. http://www.theses.fr/2012ISAR0035.

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Une Interface Cerveau-Ordinateur (ICO) est un système de communication direct entre le cerveau humain et un ordinateur. Les ICOs offrent un nouveau type d'interaction basée sur "la pensée" pour différent contexte d'utilisation comme la robotique, la domotique, le multimédia, la réalité virtuelle et les jeux vidéo. Dans ce travail, nous nous concentrons sur l'utilisation des ICOs pour interagir avec des environnements virtuels. Nous nous intéressons plus particulièrement à l'utilisation des signaux cérébraux en lien avec la charge mentale. Dans un premier temps, nous avons étudié les signaux él
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Gregori, Federica. "Sistemi di comunicazione alternativa basati su Brain Computer Interface: stato dell’arte e prospettive future." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/19912/.

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Con il termine Brain-Computer Interface (BCI) si indica un sistema hardware e software che permette, a partire da segnali di origine cerebrale, di tradurre le intenzioni dell’utente in comandi per il controllo di un dispositivo di output, come computer, sintetizzatori vocali, apparecchi di assistenza e neuroprotesi. Questa tipologia di applicazioni non richiede l’impiego di muscoli periferici, poiché sfrutta solamente specifici segnali generati dall’attività cerebrale. In particolare, il presente elaborato tratta le BCI-speller, ovvero sistemi che permettono la scrittura di un testo sfruttando
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Cisotto, Giulia. "Movement-Related Desynchronization in EEG-based Brain-Computer Interface applications for stroke motor rehabilitation." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423860.

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Neurological degenerative diseases like stroke, Alzheimer, Amyothrophic Lateral Sclerosis (ALS), Parkinson and many others are constantly increasing their incidence in the world health statistics as far as the mean age of the global population is getting higher and higher. This leads to a general need for effective, at-home and low-cost rehabilitative and health-daily-care tools. The latter should consist either of technological devices implemented for operating in a remote way, i.e. tele-medicine is quickly spreading around the world, or very-advanced computer-based and robotic systems to r
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28

Mendes, Gabriel Alves Vasiljevic. "Brain-computer interface games based on consumer-grade electroencephalography devices: systematic review and controlled experiments." PROGRAMA DE P?S-GRADUA??O EM SISTEMAS E COMPUTA??O, 2017. https://repositorio.ufrn.br/jspui/handle/123456789/24003.

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Calore, E. "TOWARDS STEADY-STATE VISUALLY EVOKED POTENTIALS BRAIN-COMPUTER INTERFACES FOR VIRTUAL REALITY ENVIRONMENTS EXPLICIT AND IMPLICIT INTERACTION." Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233319.

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In the last two decades, Brain-Computer Interfaces (BCIs) have been investigated mainly for the purpose of implementing assistive technologies able to provide new channels for communication and control for people with severe disabilities. Nevertheless, more recently, thanks to technical and scientific advances in the different research fields involved, BCIs are gaining greater attention also for their adoption by healthy users, as new interaction devices. This thesis is dedicated to to the latter goal and in particular will deal with BCIs based on the Steady State Visual Evoked Potential
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Barachant, Alexandre. "Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENT112/document.

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Cette thèse a pour but le développement d’une Interface cerveau-machine (ICM) à partir de la mesure EEG,permettant à l’utilisateur de communiquer avec un dispositif externe directement par l’intermédiaire de son activité cérébrale. Ces travaux ont été menés avec comme ligne directrice le développement d'un système d'ICM utilisable dans un contexte de vie courante, le but étant de réaliser une ICM simple d'utilisation, robuste et ergonomique, permettant le contrôle d'un effecteur avec un temps de calibration minimal.Un brain-switch ou interrupteur cérébral a été réalisé et permet à l'utilisateu
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Venot, Tristan. "Design and evaluation of a multimodal control of a robotic arm with a Brain Computer Interface." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS418.

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Les interfaces cerveau machines ont quitté le domaine de la science-fiction dans les années 70 avec la réflexion portée par Jacques Vidal sur la faisabilité d’utiliser des signaux électro-encéphalogrammes comme moyen de communication entre le cerveau et des dispositifs extérieurs. Pendant le développement de ce domaine de recherche, différentes pistes ont été explorées afin de créer une véritable interface entre le cerveau et une machine. Les méthodes d’acquisition ont pris différentes formes et avec l'amélioration des capacités informatiques et l'avènement de l'apprentissage automatique, les
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32

Petrini, Alexander, and Henrik Forslin. "Evaluation of Player Performance with a Brain Computer Interface and Eye TrackingControl in an Entertainment Game Application." Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-12928.

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Gergondet, Pierre. "Commande d’humanoïdes robotiques ou avatars à partir d’interface cerveau-ordinateur." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20134/document.

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Cette thèse s'inscrit dans le cadre du projet Européen intégré VERE (Virtual Embodiement and Robotics re-Embodiement). Il s'agit de proposer une architecture logicielle intégrant un ensemble de stratégies de contrôle et de retours informationnels basés sur la "fonction tâche" pour incorporer (embodiment) un opérateur humain dans un humanoïde robotique ou un avatar notamment par la pensée. Les problèmes sous-jacents peuvent se révéler par le démonstrateur suivant (auquel on souhaite aboutir à l'issue de cette thèse). Imaginons un opérateur doté d'une interface cerveau-ordinateur ; le but est d'
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Montgomery, Mason. "OPTIMIZATION OF FEATURE SELECTION IN A BRAIN-COMPUTER INTERFACE SWITCH BASED ON EVENT-RELATED DESYNCHRONIZATION AND SYNCHRONIZATION DETECTED BY EEG." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2786.

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There are hundreds of thousands of people who could benefit from a Brain-Computer Interface. However, not all are willing to undergo surgery, so an EEG is the prime candidate for use as a BCI. The features of Event-Related Desynchronization and Synchronization could be used for a switch and have been in the past. A new method of feature selection was proposed to optimize classification of active motor movement vs a non-active idle state. The previous method had pre-selected which frequency and electrode to use as electrode C3 at the 20Hz bin. The new method used SPSS statistical software
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Liao, James Yu-Chang. "Evaluating Multi-Modal Brain-Computer Interfaces for Controlling Arm Movements Using a Simulator of Human Reaching." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1404138858.

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Si, Mohammed Hakim. "Design and Study of Interactive Systems based on Brain- Computer Interfaces and Augmented Reality." Thesis, Rennes, INSA, 2019. http://www.theses.fr/2019ISAR0024.

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Les Interfaces Cerveau Ordinateur (ICO) permettent l’interaction à partir de l’activité cérébrale. La Réalité Augmentée (RA) elle, permet d’intégrer des éléments virtuels dans un environnement réel. Dans cette thèse, nous avons cherché à concevoir des systèmes interactifs exploitant des ICO dans des environnements RA, afin de proposer de nouveaux moyens d’interagir avec des éléments réels et virtuels. Dans la première partie de cette thèse, nous avons étudié la possibilité d’extraire différents signaux cérébraux dans un contexte de RA. Nous avons ainsi montré qu’il était possible d’exploiter l
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Avilov, Oleksii. "Deep learning methods for motor imagery detection from raw EEG : applications to brain-computer interfaces." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0032.

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Cette thèse présente trois contributions pour améliorer la reconnaissance d’imaginations motrices utilisées par de nombreuses interfaces cerveau-ordinateur (BCI) comme moyen d'interaction. Tout d'abord, nous proposons d'estimer la qualité des images motrices en détectant des valeurs aberrantes et de les supprimer avant apprentissage. Ensuite, nous étudions la sélection des caractéristiques pour sept imaginations de mouvements. Enfin, nous présentons une architecture d'apprentissage profond reprenant les principes du réseaux EEGnet applicable directement sur des signaux électro-encéphalographiq
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Dornhege, Guido. "Increasing information transfer rates for brain-computer interfacing." Phd thesis, [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98051276X.

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Young, Daniel R. "Restoring Thought-Controlled Movements After Paralysis: Developing Brain Computer Interfaces For Control Of Reaching Using Functional Electrical Stimulation." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1530808401714587.

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Bocquelet, Florent. "Vers une interface cerveau-machine pour la restauration de la parole." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAS008/document.

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Restorer la faculté de parler chez des personnes paralysées et aphasiques pourrait être envisagée via l’utilisation d’une interface cerveau-machine permettant de contrôler un synthétiseur de parole en temps réel. L’objectif de cette thèse était de développer trois aspects nécessaires à la mise au point d’une telle preuve de concept.Premièrement, un synthétiseur permettant de produire en temps-réel de la parole intelligible et controlé par un nombre raisonable de paramètres est nécessaire. Nous avons choisi de synthétiser de la parole à partir des mouvements des articulateurs du conduit vocal.
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Burger, Christiaan. "A novel method of improving EEG signals for BCI classification." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95984.

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Thesis (MEng)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Muscular dystrophy, spinal cord injury, or amyotrophic lateral sclerosis (ALS) are injuries and disorders that disrupts the neuromuscular channels of the human body thus prohibiting the brain from controlling the body. Brain computer interface (BCI) allows individuals to bypass the neuromuscular channels and interact with the environment using the brain. The system relies on the user manipulating his neural activity in order to control an external device. Electroencephalography (EEG) is a cheap, non-invasive, real time ac
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Mladenovic, Jelena. "Computational Modeling of User States and Skills for Optimizing BCI Training Tasks." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0131.

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Les Interfaces Cerveaux-Ordinateur (ICO) sont des systèmes qui permettent de manipuler une machine avec sa seule activité cérébrale. Elles sont utilisées pour accomplir des objectifs variés, par exemple afin qu’un amputé puisse manipuler un bras robotique, pour une réhabilitation neuronale en cas d’accident vasculaire cérébral, dans un cadre ludique pour jouer à des jeux vidéo, etc. Une ICO comprend l’acquisition du signal cérébral (le plus souvent par électroencéphalographie, EEG), le décodage et l’interprétation de ce signal, et enfin la production d’un retour sensoriel à l’utilisateur. Ce r
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Akinci, Berna. "Realization Of A Cue Based Motor Imagery Brain Computer Interface With Its Potential Application To A Wheelchair." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612607/index.pdf.

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This thesis study focuses on the realization of an online cue based Motor Imagery (MI) Brain Computer Interface (BCI). For this purpose, some signal processing and classification methods are investigated. Specifically, several time-spatial-frequency methods, namely the Short Time Fourier Transform (STFT), Common Spatial Frequency Patterns (CSFP) and the Morlet Transform (MT) are implemented on a 2-class MI BCI system. Distinction Sensitive Learning Vector Quantization (DSLVQ) method is used as a feature selection method. The performance of these methodologies is evaluated with the linear and n
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Mileros, Martin D. "A Real-Time Classification approach of a Human Brain-Computer Interface based on Movement Related Electroencephalogram." Thesis, Linköping University, Department of Mechanical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2824.

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<p>A Real-Time Brain-Computer Interface is a technical system classifying increased or decreased brain activity in Real-Time between different body movements, actions performed by a person. Focus in this thesis will be on testing algorithms and settings, finding the initial time interval and how increased activity in the brain can be distinguished and satisfyingly classified. The objective is letting the system give an output somewhere within 250ms of a thought of an action, which will be faster than a persons reaction time. </p><p>Algorithms in the preprocessing were Blind Signal Separation a
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Lotte, Fabien. "Study of Electroencephalographic Signal Processing and Classification Techniques towards the use of Brain-Computer Interfaces in Virtual Reality Applications." Phd thesis, INSA de Rennes, 2008. http://tel.archives-ouvertes.fr/tel-00356346.

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Une Interface Cerveau-Ordinateur (ICO) est un système de communication qui permet à ses utilisateurs d'envoyer des commandes à un ordinateur via leur activité cérébrale, cette activité étant mesurée, généralement par ÉlectroEncéphaloGraphie (EEG), et traitée par le système. Dans la première partie de cette thèse, dédiée au traitement et à la classification des signaux EEG, nous avons cherché à concevoir des ICOs interprétables et plus efficaces. Pour ce faire, nous avons tout d'abord proposé FuRIA, un algorithme d'extraction de caractéris- tiques utilisant les solutions inverses. Nous avons ég
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Carrara, Igor. "Méthodes avancées de traitement des BCI-EEG pour améliorer la performance et la reproductibilité de la classification." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4033.

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L'électroencéphalographie (EEG) mesure de manière non invasive l'activité électrique du cerveau par le biais de champs électromagnétiques générés par l'activité synchronisée de millions de neurones. Cela permet de collecter des données temporelles multivariées qui constituent une trace de l'activité électrique du cerveau mesurée au niveau du cuir chevelu. À tout instant, les mesures enregistrées par ces capteurs sont des combinaisons linéaires des activités électriques provenant d'un ensemble de sources sous-jacentes situées dans le cortex cérébral. Ces sources interagissent entre elles selon
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Hellrung, Lydia. "Softwareframework zur universellen Methodenentwicklung für ein fMRT- BCI: Adaptive Paradigmen und Echtzeitdatenanalyse." Doctoral thesis, Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-165443.

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Die funktionelle Magnetresonanztomographie (fMRT) ist ein nicht-invasives Bildgebungsverfahren, mit dem Veränderungen der neuronalen Aktivität im Gehirn mit hoher räumlicher Auflösung erfasst werden können. Mit der fMRT-Bildgebung bei neurowissenschaftlichen Experimenten wurden in den letzten beiden Jahrzehnten bedeutende Erkenntnisse für die Hirnforschung und Medizin gewonnen. Mit Hilfe dieser Methode werden neuronale Aktivitätsunterschiede bei der Durchführung einer bestimmten Aufgabe, z. B. dem Betrachten von Bildern mit emotionalen Inhalten, erfasst und die Daten unabhängig von der Messu
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Berry, Daniel Ryan. "Manipulating Paradigm and Attention via a Mindfulness Meditation Training Program Improves P300-Based BCI." Digital Commons @ East Tennessee State University, 2011. https://dc.etsu.edu/etd/1329.

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To date, only one study has situationally bolstered attentional resources in an effort to improve P300-BCI performance. The current study implements a 4-week Mindfulness Meditation Training Program (MMTP) as a nonmedicinal means to increase concentrative attention and to reduce lapses of attention; MMTP is expected to improve P300-BCI performance by enhancing attentional resources and reducing distractibility. A second aim is to test the efficacy of the checkerboard paradigm (CBP) against the standard row-column paradigm (RCP). Online results show that MMTP had greater accuracies than CTRL and
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Silva, Junior José Inácio da. "Comparativo de desempenho de sistemas BCI-SSVEP off-line e em tempo de execução utilizando técnicas de estimação de espectro e análise de correlação canônica." reponame:Repositório Institucional da UFABC, 2017.

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Orientador: Prof. Dr. Diogo Coutinho Soriano<br>Dissertação (mestrado) - Universidade Federal do ABC. Programa de Pós-Graduação em Engenharia Biomédica, 2017.<br>Interfaces cérebro-computador (BCIs) definem canais de comunicação capazes de mapear sinais cerebrais em sinais de controle para dispositivos externos, sem utilização dos eferentes biológicos, utilizando comumente estratégias não invasivas para tanto, tal como obtido pela eletroencefalografia de superfície. Dentre os principais paradigmas BCI têm-se os potenciais visualmente evocados em regime estacionário (SSVEP - steady state visual
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McCooey, Conor Gerard, and cmccooey@ieee org. "Characterising Evoked Potential Signals using Wavelet Transform Singularity Detection." RMIT University. Electrical and Computer Engineering, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080829.101311.

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This research set out to develop a novel technique to decompose Electroencephalograph (EEG) signal into sets of constituent peaks in order to better describe the underlying nature of these signals. It began with the question; can a localised, single stimulation of sensory nervous tissue in the body be detected in the brain? Flash Visual Evoked Potential (VEP) tests were carried out on 3 participants by presenting a flash and recording the response in the occipital region of the cortex. By focussing on analysis techniques that retain a perspective across different domains � temporal (time)
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