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Objective
Epilepsy management employs self‐reported seizure diaries, despite evidence of seizure underreporting. Wearable and implantable seizure detection devices are now becoming more widely available. There are no clear guidelines about what levels of accuracy are sufficient. This study aimed to simulate clinical use cases and identify the necessary level of accuracy for each.
Methods
Using...
Objective
Previous studies suggested that patients with epilepsy might be able to forecast their own seizures. This study aimed to assess the relationships between premonitory symptoms, perceived seizure risk, and future and recent self‐reported and electroencephalographically (EEG)‐confirmed seizures in ambulatory patients with epilepsy in their natural home environments.
Methods
Long‐term e‐surveys...
Objectives
Despite the prevalence of cognitive symptoms in the idiopathic generalized epilepsies (IGEs), cognitive dysfunction in juvenile absence epilepsy (JAE), a common yet understudied IGE subtype, remains poorly understood. This descriptive study provides a novel, comprehensive characterization of cognitive functioning in a JAE sample and examines the relationship between cognition and 24‐h...
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 seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy,...
Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor‐quality or corrupt data segments. In this study,...
Objective
We report on patient‐specific durations of postictal periods in long‐term intracranial electroencephalography (iEEG) recordings. The objective was to investigate the relationship between seizure duration and postictal suppression duration.
Methods
Long‐term recording iEEG from 9 patients (>50 seizures recorded) were analyzed. In total, 2310 seizures were recorded during a total of...
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