Objective. Automated behavioral state classification in intracranial EEG (iEEG) recordings
may be beneficial for iEEG interpretation and quantifying sleep patterns to enable …

Objective. Automated behavioral state classification can benefit next generation implantable
epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow …

Objective. Electrical deep brain stimulation (DBS) is an established treatment for patients
with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy, and DBS …

Background The interplay between sleep structure and seizure probability has previously
been studied using electroencephalography (EEG). Combining sleep assessment and …

There is resurgent interest in the role played by autonomic dysfunction in seizure
generation. Advances in wearable sensors make it convenient to track many autonomic …

Differentiating epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES) is
commonly based on electroencephalogram and concurrent video recordings (vEEG). Here …

Objective. To perform automatic sleep scoring based only on intracranial
electroencephalography (iEEG), without the need for scalp EEG), electrooculography (EOG) …

State of vigilance is determined by behavioral observations and electrophysiological activity.
Here, we improve automatic state of vigilance discrimination by combining head …

Electroencephalography is a widely used clinical and research method to record and
monitor the brain's electrical activity–the electroencephalogram (EEG). Machine learning …

We have previously developed an ambulatory electrode set (AES) for the measurement of
electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) …