Abstract Machine learning leverages statistical and computer science principles to develop
algorithms capable of improving performance through interpretation of data rather than …

Epileptic seizures vary greatly in clinical phenomenology and can markedly affect the
patient's quality of life. As therapeutic interventions focus on reduction or elimination of …

We conclude the review with an exercise in wishful thinking, which asks what the ideal
seizure prediction dataset would look like and how these data should be manipulated to …

Objective To develop and prospectively evaluate a method of epileptic seizure detection
combining heart rate and movement. Methods In this multicenter, in-home, prospective …

We propose Laelaps, an energy-efficient and fast learning algorithm with no false alarms for
epileptic seizure detection from long-term intracranial electroencephalography (iEEG) …

A review is given on the combined use of multiple modalities in non electroencephalography
(EEG)‐based detection of motor seizures in children and adults. A literature search of …

Objective To analyze the factors that determine the occurrence or severity of postictal
hypoxemia in the immediate aftermath of a generalized convulsive seizure (GCS). Methods …

A better understanding of the early detection of seizures is highly desirable as identification
of an impending seizure may afford improved treatments, such as antiepileptic drug …

Purpose Adequate epileptic seizure detection may have the potential to minimize seizure-
related complications and improve treatment evaluation. Autonomic changes often precede …

Reliably detecting focal seizures without secondary generalization during daily life activities,
chronically, using convenient portable or wearable devices, would offer patients with active …