Electrical brain stimulation and continuous behavioral state tracking in ambulatory humans
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 …
with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy, and DBS …
Automated unsupervised behavioral state classification using intracranial electrophysiology
Objective. Automated behavioral state classification in intracranial EEG (iEEG) recordings
may be beneficial for iEEG interpretation and quantifying sleep patterns to enable …
may be beneficial for iEEG interpretation and quantifying sleep patterns to enable …
[HTML][HTML] Automatic sleep stage classification based on subcutaneous EEG in patients with epilepsy
Background The interplay between sleep structure and seizure probability has previously
been studied using electroencephalography (EEG). Combining sleep assessment and …
been studied using electroencephalography (EEG). Combining sleep assessment and …
Behavioral state classification in epileptic brain using intracranial electrophysiology
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 …
epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow …
Deep learning enables accurate automatic sleep staging based on ambulatory forehead EEG
We have previously developed an ambulatory electrode set (AES) for the measurement of
electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) …
electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) …
Expert-level automated sleep staging of long-term scalp electroencephalography recordings using deep learning
Abstract Study Objectives Develop a high-performing, automated sleep scoring algorithm
that can be applied to long-term scalp electroencephalography (EEG) recordings. Methods …
that can be applied to long-term scalp electroencephalography (EEG) recordings. Methods …
Validation of an EEG seizure detection paradigm optimized for clinical use in a chronically implanted subcutaneous device
D Bacher, A Amini, D Friedman, W Doyle… - Journal of Neuroscience …, 2021 - Elsevier
Background Many electroencephalography (EEG) based seizure detection paradigms have
been developed and validated over the last two decades. The majority of clinical …
been developed and validated over the last two decades. The majority of clinical …
A novel, fast and efficient single-sensor automatic sleep-stage classification based on complementary cross-frequency coupling estimates
Objective Limitations of the manual scoring of polysomnograms, which include data from
electroencephalogram (EEG), electro-oculogram (EOG), electrocardiogram (ECG) and …
electroencephalogram (EEG), electro-oculogram (EOG), electrocardiogram (ECG) and …
Noninvasive seizure prediction using autonomic measurements in patients with refractory epilepsy
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 …
generation. Advances in wearable sensors make it convenient to track many autonomic …
[HTML][HTML] Recurrent deep neural networks for real-time sleep stage classification from single channel EEG
E Bresch, U Großekathöfer… - Frontiers in computational …, 2018 - frontiersin.org
Objective: We investigate the design of deep recurrent neural networks for detecting sleep
stages from single channel EEG signals recorded at home by non-expert users. We report …
stages from single channel EEG signals recorded at home by non-expert users. We report …