[HTML][HTML] Forecasting seizure likelihood with wearable technology
The unpredictability of epileptic seizures exposes people with epilepsy to potential physical
harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure …
harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure …
Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting
C Meisel, R El Atrache, M Jackson, S Schubach… - …, 2020 - Wiley Online Library
Objective Seizure forecasting may provide patients with timely warnings to adapt their daily
activities and help clinicians deliver more objective, personalized treatments. Although …
activities and help clinicians deliver more objective, personalized treatments. Although …
[HTML][HTML] Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning
The ability to forecast seizures minutes to hours in advance of an event has been verified
using invasive EEG devices, but has not been previously demonstrated using noninvasive …
using invasive EEG devices, but has not been previously demonstrated using noninvasive …
[HTML][HTML] Seizure forecasting: patient and caregiver perspectives
CL Grzeskowiak, SB Dumanis - Frontiers in neurology, 2021 - frontiersin.org
Accurate seizure forecasting is emerging as a near-term possibility due to recent
advancements in machine learning and EEG technology improvements. Large-scale data …
advancements in machine learning and EEG technology improvements. Large-scale data …
Forecasting cycles of seizure likelihood
Objective Seizure unpredictability is rated as one of the most challenging aspects of living
with epilepsy. Seizure likelihood can be influenced by a range of environmental and …
with epilepsy. Seizure likelihood can be influenced by a range of environmental and …
Development and validation of forecasting next reported seizure using e‐diaries
DM Goldenholz, SR Goldenholz, J Romero… - Annals of …, 2020 - Wiley Online Library
Objective There are no validated methods for predicting the timing of seizures. Using
machine learning, we sought to forecast 24‐hour risk of self‐reported seizure from e‐diaries …
machine learning, we sought to forecast 24‐hour risk of self‐reported seizure from e‐diaries …
The circadian profile of epilepsy improves seizure forecasting
It is now established that epilepsy is characterized by periodic dynamics that increase
seizure likelihood at certain times of day, and which are highly patient-specific. However …
seizure likelihood at certain times of day, and which are highly patient-specific. However …
Deep-learning for seizure forecasting in canines with epilepsy
Objective. This paper introduces a fully automated, subject-specific deep-learning
convolutional neural network (CNN) system for forecasting seizures using ambulatory …
convolutional neural network (CNN) system for forecasting seizures using ambulatory …
[HTML][HTML] 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 …
Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous electroencephalography: individualized intrapatient models
Objective One of the most disabling aspects of living with chronic epilepsy is the
unpredictability of seizures. Cumulative research in the past decades has advanced our …
unpredictability of seizures. Cumulative research in the past decades has advanced our …