no code implementations • 4 Apr 2023 • Tomas Teijeiro, Jamie M. Taylor, Ali Hashemian, David Pardo
The quadrature rule search is posed as an optimization problem and solved by a machine learning strategy based on gradient-descent.
no code implementations • 26 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.
no code implementations • 21 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.
no code implementations • 9 Sep 2022 • Lara Orlandic, Tomas Teijeiro, David Atienza
In this work, we use a semi-supervised learning (SSL) approach to improve the labeling consistency of the COUGHVID dataset and the robustness of COVID-19 versus healthy cough sound classification.
no code implementations • 20 Jul 2022 • Saleh Baghersalimi. Alireza Amirshahi, Farnaz Forooghifar, Tomas Teijeiro, Amir Aminifar, David Atienza
Integrating low-power wearable Internet of Things (IoT) systems into routine health monitoring is an ongoing challenge.
no code implementations • 5 Jul 2022 • Silvio Zanoli, Tomas Teijeiro, Giovanni Ansaloni, David Atienza
In this work, we leverage the self-similarity of the electrocardiogram (ECG) signal to recover missing features in event-based sampled ECG signals, dynamically selecting patient-representative templates together with a novel dynamic time warping algorithm to infer the morphology of event-based sampled heartbeats.
no code implementations • 9 Jun 2022 • William Andrew Simon, Una Pale, Tomas Teijeiro, David Atienza
However, its accuracy is not yet on par with other Machine Learning (ML) approaches.
no code implementations • 16 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.
1 code implementation • 24 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.
1 code implementation • 8 Dec 2021 • Elisabetta De Giovanni, Tomas Teijeiro, Grégoire P. Millet, David Atienza
Additionally, the online adaptive process achieves an F1 score of 99% across five different exercise intensities, with a total energy consumption of 1. 55+-0. 54~mJ.
1 code implementation • 16 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.
1 code implementation • 3 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.
no code implementations • 22 Dec 2020 • Valentin Gabeff, Tomas Teijeiro, Marina Zapater, Leila Cammoun, Sylvain Rheims, Philippe Ryvlin, David Atienza
Specifically, we focused the discussion on three main aspects: 1) how to aggregate the classification results on signal segments provided by the DL model into a larger time scale, at the seizure-level; 2) what are the relevant frequency patterns learned in the first convolutional layer of different models, and their relation with the delta, theta, alpha, beta and gamma frequency bands on which the visual interpretation of EEG is based; and 3) the identification of the signal waveforms with larger contribution towards the ictal class, according to the activation differences highlighted using the DeepLIFT method.
1 code implementation • 17 Mar 2020 • Tomas Teijeiro, Paulo Felix
This paper presents a software implementation of a general framework for time series interpretation based on abductive reasoning.