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 …
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 …
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 …
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 …
Epileptic seizure prediction using big data and deep learning: toward a mobile system
Background Seizure prediction can increase independence and allow preventative
treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction …
treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction …
Non-invasive wearable seizure detection using long–short-term memory networks with transfer learning
Objective. The detection of seizures using wearable devices would improve epilepsy
management, but reliable detection of seizures in an ambulatory environment remains …
management, but reliable detection of seizures in an ambulatory environment remains …
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 detection using wearable sensors and machine learning: Setting a benchmark
Objective Tracking seizures is crucial for epilepsy monitoring and treatment evaluation.
Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may …
Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may …
Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous EEG: Generalizable cross‐patient models
This study describes a generalized cross‐patient seizure‐forecasting approach using
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …