A wearable system for real-time detection of epileptic seizures

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Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

Low-power wearable technologies offer a promising solution to pervasive epilepsy monitoring by removing the constraints concerning time and location, on one hand, and fulfilling long-term tracking, on the other hand. In the case of epileptic seizures, as t ...

This study presents a new methodology for obtaining functional brain networks (FBNs) using multichannel scalp EEG recordings. The developed methodology extracts pair-wise phase synchrony between EEG electrodes to obtain FBNs at delta, theta, and alpha-band ...

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neur ...

A novel low-complexity method of detecting epileptic seizures from intracranial encephalography (iEEG) signals is presented. In the proposed algorithm, coastline, energy and nonlinear energy features of iEEG signals are extracted in a patient-specific two- ...

Objective: Markup of generalized interictal epileptiform discharges (IEDs) on EEG is an important step in the diagnosis and characterization of epilepsy. However, manual EEG markup is a time-consuming, subjective, and the specialized task where the human r ...

Attaching rigid wearables to ones skin may be socially challenging to be accustomed since their wearers may feel vulnerable with compromising their privacy, especially if the device is for tracking neurological or medical conditions. The development of fle ...

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

Reliably detecting focal seizures without secondary generalization during daily life activities, chronically, using convenient portable or wearable devices, would offer patients with active epilepsy a number of potential benefits, such as providing more re ...

A wearable system for real-time detection of epileptic seizures

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Personalized Real-Time Federated Learning for Epileptic Seizure Detection

Self-Aware Anomaly-Detection for Epilepsy Monitoring on Low-Power Wearable Electrocardiographic Devices

An EEG-based methodology for the estimation of functional brain connectivity networks: Application to the analysis of newborn EEG seizure

Interpreting deep learning models for epileptic seizure detection on EEG signals

Two-stage Hardware-Friendly Epileptic Seizure Detection Method with a Dynamic Feature Selection

Automatic detection of generalized paroxysmal fast activity in interictal EEG using time-frequency analysis

Gel-Free Wearable Electroencephalography (EEG) with Soft Graphene Textiles

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Noninvasive detection of focal seizures in ambulatory patients