Search Results for author: Una Pale

Found 9 papers, 4 papers with code

SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms

3 code implementations20 Feb 2024 Jonathan Dan, Una Pale, Alireza Amirshahi, William Cappelletti, Thorir Mar Ingolfsson, Xiaying Wang, Andrea Cossettini, Adriano Bernini, Luca Benini, Sándor Beniczky, David Atienza, Philippe Ryvlin

Based on existing guidelines and recommendations, the framework introduces a set of recommendations and standards related to datasets, file formats, EEG data input content, seizure annotation input and output, cross-validation strategies, and performance metrics.

EEG Seizure Detection

Combining General and Personalized Models for Epilepsy Detection with Hyperdimensional Computing

no code implementations26 Mar 2023 Una Pale, Tomas Teijeiro, David Atienza

In this work, we demonstrate a few additional aspects in which HD computing, and the way its models are built and stored, can be used for further understanding, comparing, and creating more advanced machine learning models for epilepsy detection.

Transfer Learning

Importance of methodological choices in data manipulation for validating epileptic seizure detection models

no code implementations21 Feb 2023 Una Pale, Tomas Teijeiro, David Atienza

Epilepsy is a chronic neurological disorder that affects a significant portion of the human population and imposes serious risks in the daily life of patients.

Seizure Detection

Hyperdimensional computing encoding for feature selection on the use case of epileptic seizure detection

no code implementations16 May 2022 Una Pale, Tomas Teijeiro, David Atienza

As a result, we believe it can support the ML community to further foster the research in multiple directions related to feature and channel selection, as well as model interpretability.

EEG Electroencephalogram (EEG) +2

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

1 code implementation24 Jan 2022 Una Pale, Tomas Teijeiro, David Atienza

Yet, most of them have not been tested on the challenging task of epileptic seizure detection, and it stays unclear whether they can increase the HD computing performance to the level of the current state-of-the-art algorithms, such as random forests.

EEG Electroencephalogram (EEG) +1

Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

1 code implementation16 Nov 2021 Una Pale, Tomas Teijeiro, David Atienza

At the same time, the total number of sub-classes is not significantly increased compared to the balanced dataset.

EEG Electroencephalogram (EEG) +1

ReBeatICG: Real-time Low-Complexity Beat-to-beat Impedance Cardiogram Delineation Algorithm

no code implementations4 May 2021 Una Pale, Nathan Müller, Adriana Arza, David Atienza

It achieves a detection Gmean accuracy of 94. 9%, 98. 6%, 90. 3%, and 84. 3% for the B, C, X, and O points, respectively.

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

1 code implementation3 May 2021 Una Pale, Tomas Teijeiro, David Atienza

Furthermore, we evaluate a post-processing strategy to adjust the predictions to the dynamics of epileptic seizures, showing that performance is significantly improved in all the approaches and also that after post-processing, differences in performance are much smaller between approaches.

Seizure Detection

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