Publications associées à Post-traumatic seizure

Resource-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 ...

IEEE2024

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

Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Elvira Pirondini, Cyprien Alban Félicien Rivier

Rivier et al. report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients when added to focal and clinical ...

OXFORD UNIV PRESS2023

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Marcello Ienca

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 ...

ELSEVIER SCIENCE INC2023

Approximate Zero-Crossing: A new interpretable, highly discriminative and low-complexity feature for EEG and iEEG seizure detection

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale, Renato Zanetti

Objective: Long-term monitoring of people with epilepsy based on electroencephalography (EEG) and intracranial EEG (iEEG) has the potential to deliver key clinical information for personalised epilepsy treatment. More specifically, in outpatient settings, ...

2022

Cerebral Metabolic Dysfunction at the Acute Phase of Traumatic Brain Injury Correlates with Long-Term Tissue Loss

Adriano Bernini, Ricardo Alberto Corredor Jerez, Neil Graham

Following traumatic brain injury (TBI), cerebral metabolic dysfunction, characterized by an elevated cerebral microdialysis (CMD) lactate/pyruvate (LP) ratio, is associated with poor outcome. However, the exact pathophysiological mechanisms underlying this ...

MARY ANN LIEBERT, INC2022

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

Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Long-term monitoring of patients with epilepsy presents a challenging problem from the engineering perspective of real-time detection and wearable devices design. It requires new solutions that allow continuous unobstructed monitoring and reliable detectio ...

2022

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

Amir Hossein Omidvarnia

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 ...

ELSEVIER SCI LTD2021

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

Alexandre Schmid, Keyvan Farhang Razi

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- ...

IEEE2021