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Biomedical Engineering and Bioengineering Commons™
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Full-Text Articles in Biomedical Engineering and Bioengineering
Computational Modeling Of Temporal Eeg Responses To Cyclic Binary Visual Stimulus Patterns, Connor M. Delaney
Computational Modeling Of Temporal Eeg Responses To Cyclic Binary Visual Stimulus Patterns, Connor M. Delaney
Theses and Dissertations
The human visual system serves as the basis for many modern computer vision and machine learning approaches. While detailed biophysical models of certain aspects of the visual system exist, little work has been done to develop an end-to-end model from the visual stimulus to the signals generated at the visual cortex measured via the scalp electroencephalogram (EEG). The creation of such a model would not only provide a better understanding of the visual processing pathways but would also facilitate the design and evaluation of more robust visual stimuli for brain-computer interfaces (BCIs). A novel experiment was designed and conducted where …
Estimating Affective States In Virtual Reality Environments Using The Electroencephalogram, Meghan R. Kumar
Estimating Affective States In Virtual Reality Environments Using The Electroencephalogram, Meghan R. Kumar
Theses and Dissertations
Recent interest in high-performance virtual reality (VR) headsets has motivated research efforts to increase the user's sense of immersion via feedback of physiological measures. This work presents the use of electroencephalographic (EEG) measurements during observation of immersive VR videos to estimate the user's affective state. The EEG of 30 participants were recorded as each passively viewed a series of one minute immersive VR video clips and subjectively rated their level of valence, arousal, dominance, and liking. Correlates between EEG spectral bands and the subjective ratings were analyzed to identify statistically significant frequencies and electrode locations across participants. Model feasibility and …
Brain Controlled Switch, Dimple Bhuta
Brain Controlled Switch, Dimple Bhuta
Theses and Dissertations
This study aims at designing and implementing a single channel stand-alone Brain-Controlled Switch (BCS) device, which records the electroencephalography (EEG) signals from the scalp using electrodes, amplifies it, eliminates interferences (associated with the EEG signals) and processes the EEG signals to extract and decode temporal signal features to determine user’s intention of regulating an external switch. The design of our “brain-controlled switch” device is implemented using a bio-potential amplifier and a microcontroller. The bio-potential amplifier amplifies the EEG signals to a level sufficient for processing, eliminates interferences and ensures patient safety. The microcontroller (dsPIC30F4013) digitizes the amplified and conditioned analog …
Development Of Electroencephalography Based Brain Controlled Switch And Nerve Conduction Study Simulator Software, Kai Qian
Theses and Dissertations
This thesis investigated the development of an EEG-based brain controlled switch and the design of a software for nerve conduction study. For EEG-based brain controlled switch, we proposed a novel paradigm for an online brain-controlled switch based on Event-Related Synchronizations (ERDs) following external sync signals. Furthermore, the ERD feature was enhanced by 3 event-related moving averages and the performance was tested online. Subjects were instructed to perform an intended motor task following an external sync signal in order to turn on a virtual switch. Meanwhile, the beta-band (16-20Hz) relative ERD power (ERD in reverse value order) of a single EEG …
Development Of An Electroencephalography-Based Brain-Computer Interface Supporting Two-Dimensional Cursor Control, Dandan Huang
Development Of An Electroencephalography-Based Brain-Computer Interface Supporting Two-Dimensional Cursor Control, Dandan Huang
Theses and Dissertations
This study aims to explore whether human intentions to move or cease to move right and left hands can be decoded from spatiotemporal features in non-invasive electroencephalography (EEG) in order to control a discrete two-dimensional cursor movement for a potential multi-dimensional Brain-Computer interface (BCI). Five naïve subjects performed either sustaining or stopping a motor task with time locking to a predefined time window by using motor execution with physical movement or motor imagery. Spatial filtering, temporal filtering, feature selection and classification methods were explored. The performance of the proposed BCI was evaluated by both offline classification and online two-dimensional cursor …