Publications related to Non-epileptic seizure

Controlling 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 ...

2023

Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure Detection

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Wearable and unobtrusive monitoring and prediction of epileptic seizures has the potential to significantly increase the life quality of patients, but is still an unreached goal due to challenges of real-time detection and wearable devices design. Hyperdim ...

2022

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Anthony Hitchcock Thomas

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...

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

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Alexandre Schmid, Keyvan Farhang Razi

Early and accurate detection of epileptic seizures is an extremely important therapeutic goal due to the severity of complications it can prevent. To this end, a low-power machine learning-based seizure detection implemented on an FPGA is proposed in this ...

IEEE2022

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

Silvestro Micera, Matteo Vissani

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

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences in data preparati ...

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

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

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Non-epileptic seizure

Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection

Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure Detection

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

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

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

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

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Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

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

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure Detection

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

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