Concept
Crise d'épilepsie
Publications associées (83)
Ambulatory seizure detection
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 ...
2024Resource-Efficient Continual Learning for Personalized Online Seizure Detection
David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Jonathan Dan, Amirhossein Shahbazinia, Flavio Ponzina
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 ...
2024Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants
Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...
EPFL2024Enhancing Epileptic Seizure Detection with EEG Feature Embeddings
Mahsa Shoaran, Bingzhao Zhu, Arman Zarei
Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering neurostimulation to r ...
ArXiv2023Controlling morpho-electrophysiological variability of neurons with detailed biophysical models
Henry Markram, Werner Alfons Hilda Van Geit, Lida Kanari, Alexis Arnaudon, Maria Reva, Mickael Maurice Zbili
Variability is a universal feature among biological units such as neuronal cells as they enable a robust encoding of a high volume of information in neuronal circuits and prevent hyper synchronizations such as epileptic seizures. While most computational s ...
2023EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems
David Atienza Alonso, Amir Aminifar, Renato Zanetti
Epilepsy is one of the most common neurological disorders that is characterized by recurrent and unpredictable seizures. Wearable systems can be used to detect the onset of a seizure and notify family members and emergency units for rescue. The majority of ...
2023Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection
Hyperdimensional (HD) computing is a novel approach to machine learning inspired by neuroscience, which uses vectors in a hyper-dimensional space to represent data and models. This approach has gained significant interest in recent years with applications ...
EPFL2023Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems
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 ...
EPFL2023Real-time Personalized Monitoring of Neurological Disorders on Wearable Systems
The terminology of neurological disorders encompasses a range of serious illnesses (e.g., epilepsy, Alzheimer's disease) leading to morbidity, disability, and stigma. Epilepsy alone affects over 50 million people worldwide, and these figures are rising as ...
EPFL2023How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?
Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinica ...
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