Epileptic seizure forecasting with wearable-based nocturnal sleep features.

Objective: Non-invasive biomarkers have recently shown promise for seizure forecasting in people with epilepsy. In this work, we developed a seizure-day forecasting algorithm based on nocturnal sleep features acquired using a smart shirt.

Methods: Seventy-eight individuals with epilepsy admitted to the Centre hospitalier de l'Université de Montréal epilepsy monitoring unit wore the Hexoskin biometric smart shirt during their stay.

Evaluation of Commercially Available Seizure Detection Wearables in Canada: Current Evidence.

Wearable-based seizure detection devices hold promise in reducing seizure-related adverse events and relieving the daily stress experienced by people with epilepsy. In this work, we present the latest evidence regarding the performance of three seizure detection wearables (eight studies) commercially available in Canada to provide guidance to clinicians. Overall, their ability to detect focal-to-bilateral and/or generalized tonic-clonic seizures ranges between 21.

Cross-bispectrum connectivity of intracranial EEG: A novel approach to seizure onset zone localization.

Connectivity analyses of intracranial electroencephalography (iEEG) could guide surgical planning for epilepsy surgery by improving the delineation of the seizure onset zone. Traditional approaches fail to quantify important interactions between frequency components. To assess if effective connectivity based on cross-bispectrum -a measure of nonlinear multivariate cross-frequency coupling- can quantitatively identify generators of seizure activity, cross-bispectrum connectivity between channels was computed from iEEG recordings of 5 patients (34 seizures) with good postsurgical outcome.

Decrease in wearable-based nocturnal sleep efficiency precedes epileptic seizures.

Introduction: While it is known that poor sleep is a seizure precipitant, this association remains poorly quantified. This study investigated whether seizures are preceded by significant changes in sleep efficiency as measured by a wearable equipped with an electrocardiogram, respiratory bands, and an accelerometer.

Methods: Nocturnal recordings from 47 people with epilepsy hospitalized at our epilepsy monitoring unit were analyzed (304 nights).

Epileptic Prodromes: Insights from Surveying 196 Patients and 150 Caregivers.

Objective: Uncontrolled epilepsy creates a constant source of worry for patients and puts them at a high risk of injury. Identifying recurrent "premonitory" symptoms of seizures and using them to recalibrate seizure prediction algorithms may improve prediction performances. This study aimed to investigate patients' ability to predict oncoming seizures based on preictal symptoms.

Bispectrum and Recurrent Neural Networks: Improved Classification of Interictal and Preictal States.

This work proposes a novel approach for the classification of interictal and preictal brain states based on bispectrum analysis and recurrent Long Short-Term Memory (LSTM) neural networks. Two features were first extracted from bilateral intracranial electroencephalography (iEEG) recordings of dogs with naturally occurring focal epilepsy. Single-layer LSTM networks were trained to classify 5-min long feature vectors as preictal or interictal.

Bispectrum Features and Multilayer Perceptron Classifier to Enhance Seizure Prediction.

The ability to accurately forecast seizures could significantly improve the quality of life of patients with drug-refractory epilepsy. Prediction capabilities rely on the adequate identification of seizure activity precursors from electroencephalography recordings. Although a long list of features has been proposed, none of these is able to independently characterize the brain states during transition to a seizure.

Bilateral preictal signature of phase-amplitude coupling in canine epilepsy.

Seizure forecasting would improve the quality of life of patients with refractory epilepsy. Although early findings were optimistic, no single feature has been found capable of individually characterizing brain dynamics during transition to seizure. Cross-frequency phase amplitude coupling has been recently proposed as a precursor of seizure activity.

Liquid chromatography coupled to different atmospheric pressure ionization sources-quadrupole-time-of-flight mass spectrometry and post-column addition of metal salt solutions as a powerful tool for the metabolic profiling of Fusarium oxysporum.

Fusarium oxysporum L11 is a non-pathogenic soil-borne fungal strain that yielded an extract that showed antifungal activity against phytopathogens. In this study, reversed-phase high-performance liquid chromatography (RP-HPLC) coupled to different atmospheric pressure ionization sources-quadrupole-time-of-flight mass spectrometry (API-QTOF-MS) was applied for the comprehensive profiling of the metabolites from the extract. The employed sources were electrospray (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI).