Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by
infrequent seizures based on patient or caregiver reports and limited duration clinical …
infrequent seizures based on patient or caregiver reports and limited duration clinical …
Machine learning and wearable devices of the future
Abstract Machine learning (ML) is increasingly recognized as a useful tool in healthcare
applications, including epilepsy. One of the most important applications of ML in epilepsy is …
applications, including epilepsy. One of the most important applications of ML in epilepsy is …
Long-term brain network reorganization predicts responsive neurostimulation outcomes for focal epilepsy
AN Khambhati, A Shafi, VR Rao… - Science Translational …, 2021 - science.org
Responsive neurostimulation (RNS) devices, able to detect imminent seizures and to rapidly
deliver electrical stimulation to the brain, are effective in reducing seizures in some patients …
deliver electrical stimulation to the brain, are effective in reducing seizures in some patients …
A flexible, robust, and gel-free electroencephalogram electrode for noninvasive brain-computer interfaces
Brain–computer interfaces (BCIs) enable direct and near-instant communication between
the brain and electronic devices. One of the biggest remaining challenges is to develop an …
the brain and electronic devices. One of the biggest remaining challenges is to develop an …
Dogs as a natural animal model of epilepsy
W Löscher - Frontiers in veterinary science, 2022 - frontiersin.org
Epilepsy is a common neurological disease in both humans and domestic dogs, making
dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain …
dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain …
Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings
There exist significant clinical and basic research needs for accurate, automated seizure
detection algorithms. These algorithms have translational potential in responsive …
detection algorithms. These algorithms have translational potential in responsive …
Seizure prediction using undulated global and local features
In this study, a seizure prediction method is proposed based on a patient-specific approach
by extracting undulated global and local features of preictal/ictal and interictal periods of …
by extracting undulated global and local features of preictal/ictal and interictal periods of …
Consistency of long-term subdural electrocorticography in humans
Objective: Subdural electrocorticography (ECoG) can provide a robust control signal for a
brain-computer interface (BCI). However, the long-term recording properties of ECoG are …
brain-computer interface (BCI). However, the long-term recording properties of ECoG are …
Recurring functional interactions predict network architecture of interictal and ictal states in neocortical epilepsy
AN Khambhati, DS Bassett, BS Oommen, SH Chen… - eneuro, 2017 - eneuro.org
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions
that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is …
that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is …
Stochastic gradient MCMC for state space models
State space models (SSMs) are a flexible approach to modeling complex time series.
However, inference in SSMs is often computationally prohibitive for long time series …
However, inference in SSMs is often computationally prohibitive for long time series …