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Concept

Generalized epilepsy

Publications associées (22)

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

David Atienza Alonso, Giovanni Ansaloni, Flavio Ponzina, José Angel Miranda Calero, Jonathan Dan, Amirhossein Shahbazinia

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

IEEE2024

Ambulatory seizure detection

Jonathan Dan

Purpose of review: To review recent advances in the field of seizure detection in ambulatory patients with epilepsy. Recent findings: Recent studies have shown that wrist or arm wearable sensors, using 3D-accelerometry, electrodermal activity or photopleth ...

2024

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Keyvan Farhang Razi

Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...

EPFL2023

Disruption of layer-specific visual processing in a model of focal neocortical epilepsy

Silvestro Micera

The epileptic brain is the result of a sequence of events transforming normal neuronal populations into hyperexcitable networks supporting recurrent seizure generation. These modifications are known to induce fundamental alterations of circuit function and ...

OXFORD UNIV PRESS INC2022

Recent Developments on the Use of Nanomaterials for the Treatment of Epilepsy

Sandrine Gerber

Epilepsy affects more than 40 million people worldwide, constituting one of the most debilitating disorders of the Central Nervous System (CNS). It results from an imbalance in the electrical activity of neurons, which is primarily mediated by calcium ions ...

2022

Personalized seizure signature: An interpretable approach to false alarm reduction for long‐term epileptic seizure detection

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Dionisije Sopic

Objective Long-term automatic detection of focal seizures remains one of the major challenges in epilepsy due to the unacceptably high number of false alarms from state-of-the-art methods. Our aim was to investigate to what extent a new patient-specific ap ...

2022

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

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Farnaz Forooghifar

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 ...

2021

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Saleh Baghersalimi

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 ...

2021

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

Amir Hossein Omidvarnia

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 ...

2021

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Dionisije Sopic

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 ...

EPFL2020

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Damián Pascual Ortiz

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 ...

2021

Depersonalization- and derealization-like phenomena of epileptic origin

Olaf Blanke, Lukas Heydrich, Nathaniel Evans

Objective Depersonalization refers to the sensation of being detached from one's body, often associated with feelings of loss of control over one's own body, actions, or thoughts. Derealization refers to the altered perception of one's surroundings that is ...

2019

A Self-Learning Methodology for Epileptic Seizure Detection with Minimally Supervised Edge Labeling

David Atienza Alonso, Amir Aminifar, Damián Pascual Ortiz

Epilepsy is one of the most common neurological disorders and affects over 65 million people worldwide. Despite the continuing advances in anti-epileptic treatments, one third of the epilepsy patients live with drug resistant seizures. Besides, the mortali ...

2019

A Self-Aware Epilepsy Monitoring System for Real-Time Epileptic Seizure Detection

David Atienza Alonso, Leila Cammoun, Leila Faiza Ben Hamida Cammoun, Amir Aminifar, Farnaz Forooghifar

Epilepsy is one of the most prevalent paroxystic neurological disorders that can dramatically degrade the quality of life and may even lead to death. Therefore, real-time epilepsy monitoring and seizure detection has become important over the past decades. ...

2022

e-Glass: A Wearable System for Real-Time Detection of Epileptic Seizures

David Atienza Alonso, Amir Aminifar, Dionisije Sopic

Today, epilepsy is one of the most common chronic diseases affecting more than 65 million people worldwide and is ranked number four after migraine, Alzheimer’s disease, and stroke. Despite the recent advances in anti-epileptic drugs, one-third of the epil ...

2018

An Energy Efficient Power Converter for Zero Power Wearable Devices

Milad Ataei Ashtiani

Early diagnosis of Alzheimer's and epilepsy requires monitoring a subject's development of symptoms through electroencephalography (EEG) signals over long periods. Wearable devices enable convenient monitoring of biosignals, unlike complex and costly hospi ...

EPFL2018

Patient MoCap: Human Pose Estimation under Blanket Occlusion for Hospital Monitoring Applications

Alexandru Eugen Ichim

Motion analysis is typically used for a range of diagnostic procedures in the hospital. While automatic pose estimation from RGB-D input has entered the hospital in the domain of rehabilitation medicine and gait analysis, no such method is available for be ...

2016

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging

Jean-Philippe Thiran, Alessandro Daducci, François Lazeyras, Nicolas Kunz, Alia Lemkaddem

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation ...

2014

Capacitive Detuning Optimization for Wireless Uplink Communication in Neural Implants

Catherine Dehollain, Gürkan Yilmaz

This study presents a wireless energy and data transfer system for neural implants with an emphasis on epilepsy monitoring. A wireless uplink data transmission system is built upon a remote powering system based on magnetic coupling which has been implemen ...

Ieee2013

Partial and full own-body illusions of epileptic origin in a child with right temporoparietal epilepsy

Olaf Blanke, Lukas Heydrich

Partial and full own-body illusions of neurological origin have been claimed crucial to understand the contribution of bodily experience and perception to self-consciousness. Whereas partial body illusions are relatively common and well defined, much less ...

2011