Searched for: subject%3A%22EEG%22
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van Dijk, Mees (author)
Algorithms which can effectively detect epileptic seizures have the potential to improve current treatment methods for people who suffer from epilepsy. The current state-of-the-art methods use neural networks, which are able to learn directly from the electroencephalogram (EEG) data without feature extraction. However, neural networks have...
master thesis 2024
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Bras, Chris (author)
Brain-Computer Interfaces (BCIs) open avenues for communication among individuals unable to use voice or gestures. Silent speech interfaces are one such approach for BCIs that could offer a trans- formative means of connecting with the external world. Performance on imagined speech decoding however is rather low due to, amongst others, data...
master thesis 2024
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Oerlemans, Carlijn (author)
Study objectives: Conventional sleep scoring is based on the scoring criteria of the American Association of Sleep Medicine (AASM) but may not be suited to describe sleep in critically ill children admitted to the Pediatric Intensive Care Unit (PICU). In this study, an anomaly detection model using Gaussian Models trained on sleep stages in data...
master thesis 2024
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van den Hoek, Thomas C. (author), Perenboom, Matthijs J.L. (author), Terwindt, Gisela M. (author), Tolner, Else A. (author), van de Ruit, M.L. (author)
Introduction: Migraine is associated with enhanced visual sensitivity during and outside attacks. Processing of visual information is a highly non-linear process involving complex interactions across (sub)cortical networks. In this exploratory study, we combined electroencephalography with bi-sinusoidal light stimulation to assess non-linear...
journal article 2024
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Stölzle, Maximilian (author), Baberwal, S. (author), Rus, Daniela (author), Coyle, Shirley (author), Della Santina, C. (author)
Integrating Brain-Machine Interfaces into non-clinical applications like robot motion control remains difficult - despite remarkable advancements in clinical settings. Specifically, EEG-based motor imagery systems are still error-prone, posing safety risks when rigid robots operate near humans. This work presents an alternative pathway towards...
conference paper 2024
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Johri, Riddhi (author), Pandey, Pankaj (author), Miyapuram, Krishna Prasad (author), Lomas, J.D. (author)
The brain is an incredibly complex organ capable of perceiving and interpreting a wide range of stimuli. Depending on individual brain chemistry and wiring, different people decipher the same stimuli differently, conditioned by their life experiences and environment. This study’s objective is to decode how the CNN models capture and learn...
conference paper 2024
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van Rooijen, Thom (author)
Various source localization algorithms exist to perform localization with High Density (HD)-ElectroEncephaloGraphy (EEG). However, validation of these EEG source localization algorithms is lacking. The current gold standard for source localization in the brain is functional Magnetic Resonance Imaging (fMRI) by calculating the difference in...
master thesis 2023
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Plat, Benthe (author)
This report delves into the challenging process of translating complex tests from the Child Brain Lab into a design that is both accessible and engaging for children. The Child Brain Lab, part of the Erasmus MC Sophia Children’s Hospital, conducts research on brain development to gain a better understanding of the course of brain disorders and...
master thesis 2023
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Kyriazis, Ioannis (author)
Patients with neuromuscular diseases that are unable to speak, but whose cognitive ability has been maintained, can be benefited from Brain Computer Interfaces (BCIs). The decoding of inner (covert) speech from EEGs consists of one of the state of the art methods that aim to tackle this issue. High variability between subjects, as well as low...
master thesis 2023
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Verboom, Marit (author)
Critically ill patients in the Intensive Care Unit (ICU) are often comatose and thoroughly monitored. Neurological complications occur in up to 20% of these patients. Therefore, monitoring of the brain, which can be performed using electroencephalography (EEG), has the potential to significantly impact the outcomes of patients at the ICU....
master thesis 2023
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Lückerath, Femke (author)
During the initial phase of diagnosis, patients with anti-NDMA-receptor encephalitis (anti-NMDARE) often experience severe symptoms that significantly impact their quality of life. Anti-NDMARE is an autoimmune disorder affecting the brain, with electroencephalography (EEG) playing a vital role in diagnosis and treatment. Identifying EEG patterns...
master thesis 2023
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Dai, Anthony (author), van de Weg, Joris (author)
In the context of designing a real-time brain-computer interface for playing a game using the OpenBCI Ultracortex "Mark IV" headset, this paper focuses on the work of the decoding subgroup. The primary responsibility is to analyse EEG data retrieved from the OpenBCI headset and classify the intention of the user. Our objective is to achieve a...
bachelor thesis 2023
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Lee, Wesmond (author), Los, Thibault (author)
Purpose<br/>The main purpose of this report is to find out whether the OpenBCI "Ultracortex Mark IV" Electroencephalogram (EEG) headset is capable of differentiating EEG-signals of motor execution from neutral state with recorded data and to find out whether it can differ motor executions between left and right hand. Next to that, it is to be...
bachelor thesis 2023
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Apawti, Chelsea (author), van Zijl, Marlon (author)
This document presents the development of a user interface for an EEG motor imagery based Brain-Computer Interface (BCI) as the interface subgroup. The aim of this subgroup in the project was to design and implement a graphical user interface (GUI) incorporating visual neurofeedback to enhance the accuracy of the decode algorithm, developed by...
bachelor thesis 2023
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Scheffers, Marjolein (author)
master thesis 2023
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Lange, Sanne (author)
Epilepsy has been reported in 10-40% of children in the paediatric intensive care unit (PICU). Amplitude-integrated electroencephalography (aEEG), often used as neuromonitoring in the PICU, has some limitations and as a result, caretakers in the PICU may find it challenging to interpret aEEG. This may lead to uncertainty during diagnosis and...
master thesis 2023
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van Vliet, Sjoerd (author)
Different paradigms can be used to evoke brainwaves. These brainwaves can be interpreted as commands that can be used to control different applications. These frameworks that interpret the brainwaves are called brain-computer interfaces. Steady-state visually evoked potentials is one of these paradigms that uses external stimuli flickering at...
master thesis 2023
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Chaudhary, Shivam (author), Prasad Miyapuram, Krishna (author), Lomas, J.D. (author)
Entrainment is a phenomenon of phase or temporal matching of one system with that of another system. Human neural activity has been shown to resonate with external auditory stimuli. When we enjoy a piece of music, there is a resonance of brain responses with auditory signals. The crux of music cognition is based on this resonance of musical...
conference paper 2023
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Johri, Riddhi (author), Pandey, Pankaj (author), Miyapuram, Krishna Prasad (author), Lomas, J.D. (author)
Advances in neurotechnology have enhanced and simplified our ability to research brain activity with low-cost and effective equipment. One such scalable and noninvasive technique is Electroencephalography (EEG), which detects and records electrical brain activity. Brain activity recognition is one of the emerging problems as EEG wearables...
conference paper 2023
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Dekker, Bo (author), Schouten, A.C. (author), Scharenborg, O.E. (author)
Silent speech interfaces could enable people who lost the ability to use their voice or gestures to communicate with the external world, e.g., through decoding the person’s brain signals when imagining speech. Only a few and small databases exist that allow for the development and training of brain computer interfaces (BCIs) that can decode...
conference paper 2023
Searched for: subject%3A%22EEG%22
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