The study PI and ZETO staff will train a nurse at the Charleston VA to acquire EEGs using the ZETO dry electrode EEG system at a Community Based Outpatient Clinic (CBOC) in South Carolina. The location of the CBOC will probably be in Beaufort, SC, where a previous similar study was performed. This ZETO device is easy to use and can be set up in 5-10 minutes because it is a headset which is placed on the head without skin or hair preparation. A total of 20 Veterans who are scheduled to be seen for primary care appointments at a VA CBOC will be recruited. Each EEG recording will take about 30 minutes to complete (including set-up time). EEG setup time and patient comfort measures will be acquired. EEG signal will be analyzed for signal quality with assistance from an investigator at the School of Computing at Clemson University. Three neurologist co-investigators will also assist in analysis of the EEG recordings.
This in an exploratory study and the information obtained may lead to new findings regarding the treatment of seizures in adults with drug-resistant focal epilepsy. This study will explore the effectiveness, safety, and of a medication called natalizumab.
This project proposes to develop a system to analyze electroencephalography (EEG) and magnetic resonance imaging (MRI) data from clinical studies of patients with epileptic seizures. This will be called the Next-Generative Neural Data Analysis (NGNDA) platform. This system will use new high-performance computing tools and algorithms to analyze high-dimensional brain data from EEG and MRI. The plan is to create tools for analyzing these big data clinical studies that clinicians can use to improve the care of patients with epilepsy.
The purpose of this project is to develop a highly accurate, reliable, and user-friendly electroencephalogram (EEG) recording and seizure monitoring and alert system (CereScope™) for use during times where patients require close EEG monitoring to detect seizures.
The goal of this study is to determine the effectiveness of the Companion™ device to detect GTC seizures and alert someone to the seizure.
EEG is the most common neurophysiology procedure. Unfortunately, EEG is plagued with the problem of artifacts. Artifacts are contaminant signals which come from other sources than the brain. These other sources are electrical potentials from eye movement, electromyogram (EMG) signals from muscles of the scalp, 60 Hz noise from the electrical power system, signals caused by patient movement, and noise from problems with individual EEG electrodes. The purpose of this study is to create EEG recordings from normal subjects that can be used to measure how well automatic EEG artifact removal software works. EEG recordings will be made from subjects during two states: (1) while subjects are at rest and (2) while subjects are being given somatosensory, visual, and auditory stimuli. The stimuli that will be used will be standard clinical somatosensory evoked potential stimuli using electrical shocks to the left wrist, flashing lights for a visual stimulus, and audio click sounds throughout headphones for the auditory stimuli. The averaged evoked potentials will be studied before and after automatic EEG artifact removal software is applied and comparied between the resting state and the stimulated state.