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Дисертації з теми "Brain interfacing"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Kaper, Matthias. "P300 based brain computer interfacing." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=979538203.

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2

Daly, Ian. "Phase synchronisation in brain computer interfacing." Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553633.

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Анотація:

Brain Computer Interfaces (BCls) are an emerging area of research combining the Neuroscience, Computer Science, Engineering, Mathematics, Human Computer Interaction and Psychology research fields. A BCI enables an individual to exert control of a computer without activation of the efferent nervous system or the muscles. This allows individuals suffering with partial or complete paralysis and associated conditions which prevent muscle movement to control a computer and hence communicate and exert control over their environment. This thesis first investigates tools for automatically removing art

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3

Shoker, Leor. "Signal processing algorithms for brain computer interfacing." Thesis, Cardiff University, 2006. http://orca.cf.ac.uk/56097/.

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A brain computer interface (BCI) allows the user to communicate with a computer using only brain signals. In this way, the conventional neural pathways of peripheral nerves and muscles are bypassed, thereby enabling control of a computer by a person with no motor control. The brain signals, known as electroencephalographs (EEGs), are recorded by electrodes placed on the surface of the scalp. A requirement for a successful BCI is that interfering artifacts are removed from the EEGs, so that thereby the important cognitive information is revealed. Two systems based on second order blind source s

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4

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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5

Valbuena, Varon Diana Alexandra [Verfasser]. "Practical Brain Computer Interfacing / Diana Alexandra Valbuena Varon." München : Verlag Dr. Hut, 2012. http://d-nb.info/1029399751/34.

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6

Melano, Timothy. "Insect-Machine Interfacing." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145388.

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Анотація:

A terrestrial robotic electrophysiology platform has been developed that can hold a moth (<italic>Manduca sexta</italic>), record signals from its brain or muscles, and use these signals to control the rotation of the robot. All signal processing (electrophysiology, spike detection, and robotic control) was performed onboard the robot with custom designed electronic circuits. Wireless telemetry allowed remote communication with the robot. In this study, we interfaced directionally-sensitive visual neurons and pleurodorsal steering muscles of the mesothorax with the robot and used the spike rat

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7

Nazarpour, Kianoush. "Brain signal analysis in space-time-frequency domain : an application to brain computer interfacing." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54718/.

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In this dissertation, advanced methods for electroencephalogram (EEG) signal analysis in the space-time-frequency (STF) domain with applications to eye-blink (EB) artifact removal and brain computer interfacing (BCI) are developed. The two methods for EB artifact removal from EEGs are presented which respectively include the estimated spatial signatures of the EB artifacts into the signal extraction and the robust beamforming frameworks. In the developed signal extraction algorithm, the EB artifacts are extracted as uncorrelated signals from EEGs. The algorithm utilizes the spatial signatures

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8

Eaton, Joel. "Brain-computer music interfacing : designing practical systems for creative applications." Thesis, University of Plymouth, 2016. http://hdl.handle.net/10026.1/5221.

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Brain-computer music interfacing (BCMI) presents a novel approach to music making, as it requires only the brainwaves of a user to control musical parameters. This presents immediate benefits for users with motor disabilities that may otherwise prevent them from engaging in traditional musical activities such as composition, performance or collaboration with other musicians. BCMI systems with active control, where a user can make cognitive choices that are detected within brain signals, provide a platform for developing new approaches towards accomplishing these activities. BCMI systems that u

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9

Spüler, Martin [Verfasser]. "Assessing the Benefit of Adaptive Brain-Computer Interfacing / Martin Spüler." München : Verlag Dr. Hut, 2013. http://d-nb.info/1037287002/34.

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10

Wang, Suogang. "Enhancing brain-computer interfacing through advanced independent component analysis techniques." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/65897/.

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Анотація:

A brain-computer interface (BCI) is a direct communication system between a brain and an external device in which messages or commands sent by an individual do not pass through the brain’s normal output pathways but is detected through brain signals. Some severe motor impairments, such as Amyothrophic Lateral Sclerosis, head trauma, spinal injuries and other diseases may cause the patients to lose their muscle control and become unable to communicate with the outside environment. Currently no effective cure or treatment has yet been found for these diseases. Therefore using a BCI system to reb

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11

Marshall, David. "Brain-computer games interfacing with motion-onset visual evoked potentials." Thesis, Ulster University, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.685554.

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Анотація:

A brain-computer interface (BCI) measures brain activity and translates this activity into commands for a program to execute. BCls enable movement-free communication and interaction with technologies. This thesis evaluates the effectiveness and limitations of motion-onset visual evoked potentials (mVEP) based BCI as a control method for brain-computer games interaction. MVEP incorporates neural activity from the dorsal pathway of the visual system which allows more elegant visual stimuli than other types ofVEP and has yet to be used in computer games. This thesis investigates ifmVEP can be use

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12

Reezek, Iead Arend. "Information dynamics in physiological control systems." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266591.

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13

Raza, Haider. "Adaptive learning for modelling non-stationarity in EEG-based brain-computer interfacing." Thesis, Ulster University, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.695308.

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Non-stationary learning (NSL) refers to the process that can learn rules from data, adapt to shifts, and improve the performance of the system with its experience while operating in the non-stationary environments (NSE). While data processing in NSE, a covariate shift is a major challenge wherein the input data distribution may shift during transitioning from training to testing phase. Covariate shift is one of the fundamental challenges in electroencephalogram (EEG) based brain-computer interface (BCI) systems and these can be often found during multiple trials over different sessions of EEG

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14

Dharwarkar, Gireesh. "Using Temporal Evidence and Fusion of Time-Frequency Features for Brain-Computer Interfacing." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/830.

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Анотація:

Brain-computer interfacing (BCI) is a new method of human-machine interaction. It involves the extraction of information from the electroencephalogram (EEG) through signal processing and pattern recognition. The technology has far reaching implications for those with severe physical disabilities and has the potential to enhance machine interaction for the rest of the population. In this work we investigate time-frequency analysis in motor-imagery BCI. We consider two methods for signal analysis: adaptive autoregressive models (AAR) and wavelet transform (WAV). There are three ma

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15

Talbot, Brian Mark. "Characterization of phase estimation techniques to guide phasic stimulation for brain machine interfacing." Thesis, Boston University, 2012. https://hdl.handle.net/2144/31616.

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Thesis (M.S.)--Boston University<br>PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.<br>While much work on brain-machine interfaces (BMI) focuses on decoding neural signals to drive external plants (e.g. a robotic arm), there is increasing interest in the delivery of central neural stimulation, f

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16

Choi, Yoonsu. "A Three-Dimensional Coupled Microelectrode and Microfluidic Array for Neuronal Interfacing." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/11638.

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The objective of this research is to develop a three-dimensional (3-D) microfluidic/ electronic interface system for sustaining and monitoring 3-D neuronal networks. This research work is divided into two parts. One is the development of a 3-D multi-electrode array (MEA) with integrated microfluidic channels. The other is a microneedle array with embedded microelectrodes and microfluidic channels. The 3-D MEA is composed of three elements that are essential for the development and monitoring of 3-D cultures of neurons. These components consist of scaffolds for cellular growth and structural

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17

Wu, Shuai. "Mot robust cross-subject klassificering av electroencephalogram (EEG) baserad brain-computer interfacing (BCI):En genomförbarhetsstudie." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254765.

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Анотація:

Brain-computer interface(BCI) är ett system där man kan skicka kommandon till dator med bara hjärnaktivitet. En sådan system är viktigt för människor lider av flera motorisk funktionshinder, då maskinen skulle kunna förbättra patienters liv genom att uppfylla deras behov. Denna rapport fokusera på en variant av BCI, kallas motor imagery based BCI, vilken basera på att klassificera försökspersons hjärnaktivitet då han/hon tänka sig att röra sin kroppsdelar. Det finns flera svårighet för att bygga en fungerande system, en av de är generalisering av tränad model. En tränad model garanti inte exak

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18

Valbuena, Varon Diana Alexandra [Verfasser], Axel [Akademischer Betreuer] Gräser, and Jan [Akademischer Betreuer] Peleska. "Practical Brain Computer Interfacing / Diana Alexandra Valbuena Varon. Gutachter: Axel Gräser ; Jan Peleska. Betreuer: Axel Gräser." Bremen : Staats- und Universitätsbibliothek Bremen, 2011. http://d-nb.info/1071842099/34.

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19

Clements, Isaac Perry. "Topographic guidance scaffolds for peripheral nerve interfacing." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/42938.

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Анотація:

In response to high and rising amputation rates, significant advances have been made in the field of prosthetic limb design. Unfortunately, there exists a lag in the neural interfacing technology required to provide an adequate link between the nervous system and this emerging generation of advanced prosthetic devices. Novel approaches to peripheral nerve interfacing are required to establish the stable, high channel count connections necessary to provide natural, thought driven control of an external prosthesis. Here, a tissue engineering-based approach has been used to create a device capabl

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20

Ta, Christopher Ian. "Interfacing a Brain Control Interface towards the Development of a Retrofitted, Low-Cost, Open Sourced, Electric Wheelchair." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1707240/.

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The Emotiv Insight is a commercially available, low-cost, mobile EEG device that is commonly overshadowed by its costlier counterpart, the Emotiv EPOC. The purpose of this report is to investigate if the Emotiv Insight is a suitable headset to be used as a controlling factor in conjunction with an Arduino microcontroller and various electrical components that are used towards the development of an open-sourced, affordable electric wheelchair with the primary goal of providing those who either do not have the financial resources or the physical capability to operate a traditional wheelchair due

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21

Foldes, Stephen Thomas. "Command of a Virtual Neuroprosthesis-Arm with Noninvasive Field Potentials." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1290109568.

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22

Herweg, Andreas [Verfasser], and Andrea [Gutachter] Kübler. "Beyond the state of the art, towards intuitive and reliable non-visual Brain-Computer-Interfacing / Andreas Herweg ; Gutachter: Andrea Kübler." Würzburg : Universität Würzburg, 2016. http://d-nb.info/1132063485/34.

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23

Hohlefeld, Friederike U. [Verfasser]. "Neural correlates of covert and overt movements investigated by EEG/EMG with implications for brain-computer interfacing / Friederike U. Hohlefeld." Berlin : Freie Universität Berlin, 2011. http://d-nb.info/1025355628/34.

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24

Heffernan, Brian. "Characterization and Classification of the Frequency Following Response to Vowels at Different Sound Levels in Normal Hearing Adults." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38816.

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This work seeks to more fully characterize how the representation of English vowels changes with increasing sound level in the frequency following response (FFR) of normal-hearing adult subjects. It further seeks to help inform the design of brain-computer interfaces (BCI) that exploit the FFR for hearing aid (HA) applications. The results of three studies are presented, followed by a theoretical examination of the potential BCI space as it relates to HA design. The first study examines how the representation of a long vowel changes with level in normal hearing subjects. The second study exa

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25

Mahmud, Mufti. "SigMate: A Comprehensive Automated Tool for Processing and Analysis of Extracellular Brain Signals Recorded by Neuronal Probes." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3421567.

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Анотація:

The ionic gating across the neuron membrane generates neuronal activity in the brain. During the last two decades rapid advances in microelectronics and microelectrode technology have provided scientists with many devices enabling them to record extracellularly the transmembrane potentials near the electrode in the brain. These devices that are implanted invasively without causing too much tissue damage, can record from hundreds of neurons, and also simultaneously from a number of channels generating a huge amount of data. Inferring meaningful conclusions by analyzing this massive amount of da

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26

Cecchetto, Claudia. "Neuronal Population Encoding of Sensory Information in the Rat Barrel Cortex: Local Field Potential Recording and Characterization by an Innovative High-Resolution Brain-Chip Interface." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3424482.

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Neuronal networks are at the base of information processing in the brain. They are series of interconnected neurons whose activation defines a recognizable linear pathway. The main goal of studying neural ensembles is to characterize the relationship between the stimulus and the individual or general neuronal responses and the relation amongst the electrical activities of neurons within the network, also understanding how topology and connectivity relates to their function. Many techniques have been developed to study these complex systems: single-cell approaches aim to investigate single neur

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27

Wenzel, Markus Verfasser], Benjamin [Akademischer Betreuer] Blankertz, Benjamin [Gutachter] Blankertz, Klaus-Robert [Gutachter] [Müller, and Peter [Gutachter] Desain. "Decoding implicit information from the electroencephalogram with methods from brain-computer interfacing / Markus Wenzel ; Gutachter: Benjamin Blankertz, Klaus-Robert Müller, Peter Desain ; Betreuer: Benjamin Blankertz." Berlin : Technische Universität Berlin, 2017. http://d-nb.info/1156179823/34.

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28

Wenzel, Markus [Verfasser], Benjamin Akademischer Betreuer] Blankertz, Benjamin [Gutachter] Blankertz, Klaus-Robert [Gutachter] [Müller, and Peter [Gutachter] Desain. "Decoding implicit information from the electroencephalogram with methods from brain-computer interfacing / Markus Wenzel ; Gutachter: Benjamin Blankertz, Klaus-Robert Müller, Peter Desain ; Betreuer: Benjamin Blankertz." Berlin : Technische Universität Berlin, 2017. http://d-nb.info/1156179823/34.

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29

Kaper, Matthias [Verfasser]. "P300 based brain computer interfacing / Matthias Kaper." 2006. http://d-nb.info/979538203/34.

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30

Dornhege, Guido [Verfasser]. "Increasing information transfer rates for brain-computer interfacing / von Guido Dornhege." 2006. http://d-nb.info/98051276X/34.

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31

Herweg, Andreas. "Beyond the state of the art, towards intuitive and reliable non-visual Brain-Computer-Interfacing." Doctoral thesis, 2016. https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-133447.

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For the present work three main goals were formulated: goal 1 To design a tactile BCI used for mobility which is intuitive (G1.1), reliable and fast while being usable by participants aged 50 years and above. goal 2 To design an auditory BCI used for communication which is intuitive and reliable. goal 3 To examine the effects of training on tactile and auditory BCI performance. Three studies were performed to achieve these goals. In the first study nine participants aged above 50 years performed a five-session training after which eight participants were able to navigate a virtual wheelchair w

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32

RATH, SATYASAMBIT, and 薩特亞. "Application of a Brain Computer Interfacing System in Comparing Visual verses Haptic Induction of Motor Imaginary Task." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/46r7fx.

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碩士<br>國立中央大學<br>認知與神經科學研究所<br>105<br>Haptic-based Brain Computer Interface (BCI) has great values in real-world applications as it is less intrusive than visual or auditory based BCI. It is not clear from previous literature whether haptic-based BCI can achieve equivalent or even better accuracies when applied to the classification of motor imagery. In addition, it was also not clear whether high classification accuracy can be achieved in haptic cue based motor imagery BCI with few channels. The current study sets out to establish a BCI framework using only four channels for motor imagery clas

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33

"Novel Organic Light Emitting Diodes for Optogenetic Experiments." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.34848.

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abstract: Optical Fibers coupled to laser light sources, and Light Emitting Diodes are the two classes of technologies used for optogenetic experiments. Arizona State University's Flexible Display Center fabricates novel flexible Organic Light Emitting Diodes(OLEDs). These OLEDs have the capability of being monolithically fabricated over flexible, transparent plastic substrates and having power efficient ways of addressing high density arrays of LEDs. This thesis critically evaluates the technology by identifying the key advantages, current limitations and experimentally assessing the technolo

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34

Che, Ruslan Mohd Fuad Anwari. "Modelling CO2-Brine Interfacial Tension using Density Gradient Theory." Diss., 2018. http://hdl.handle.net/10754/627680.

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Knowledge regarding carbon dioxide (CO2)-brine interfacial tension (IFT) is important for petroleum industry and Carbon Capture and Storage (CCS) strategies. In petroleum industry, CO2-brine IFT is especially importance for CO2 – based enhanced oil recovery strategy as it affects phase behavior and fluid transport in porous media. CCS which involves storing CO2 in geological storage sites also requires understanding regarding CO2-brine IFT as this parameter affects CO2 quantity that could be securely stored in the storage site. Several methods have been used to compute CO2-brine interfacial

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