Simon Geirnaert
Simon Geirnaert
Home
Publications
Presentations
SciComm
Speech decoding resources
Music
CV
Contact
neuro-steered hearing device
Linear stimulus reconstruction works on the KU Leuven audiovisual, gaze-controlled auditory attention decoding dataset
In this report, we show that linear stimulus reconstruction (AAD) for EEG-based auditory attention decoding
works
on the KU Leuven audiovisual, gaze-controlled AAD dataset.
Simon Geirnaert
,
Iustina Rotaru
,
Tom Francart
,
Alexander Bertrand
December, 2024
report
PDF
Cite
Code
Dataset
DOI
Unsupervised Accuracy Estimation for Brain-Computer Interfaces based on Selective Auditory Attention Decoding
In this preprint, we present a new unsupervised method to estimate the performance of the stimulus reconstruction algorithm for EEG-based auditory attention decoding.
Miguel Ángel López-Gordo
,
Simon Geirnaert
,
Alexander Bertrand
November, 2024
preprint
PDF
Cite
Code
Dataset
DOI
Probabilistic Gain Control in a Multi-Speaker Setting using EEG-Based Auditory Attention Decoding
In this paper, presented at
EUSIPCO 2024
, we present a probabilistic gain control system steered by brain-decoded auditory attention decoding algorithms.
Nicolas Heintz
,
Simon Geirnaert
,
Iris Van de Ryck
,
Tom Francart
,
Alexander Bertrand
August, 2024
In Proceedings of
EUSIPCO 2024
, 2024
PDF
Cite
Dataset
What are we really decoding? Unveiling biases in EEG-based decoding of the spatial focus of auditory attention
In this article, we try to uncover potential biases of the CSP-based decoding of the spatial focus of auditory attention, using a multi-talker audiovisual EEG experiment.
Iustina Rotaru
,
Simon Geirnaert
,
Nicolas Heintz
,
Iris Van de Ryck
,
Alexander Bertrand
,
Tom Francart
February, 2024
Journal of Neural Engineering
, vol. 21, no. 1, 016017, 2024
PDF
Cite
Dataset
DOI
Fast, accurate, unsupervised, and time-adaptive EEG-based auditory attention decoding for neuro-steered hearing devices
This book chapter, published in
Brain-Computer Interface Research
, summarizes my PhD research and is written following my nomination for the BCI Award 2022.
Simon Geirnaert
,
Rob Zink
,
Tom Francart
,
Alexander Bertrand
January, 2024
in
Brain-Computer Interface Research
, 2024
PDF
Cite
Video
DOI
Unbiased Unsupervised Stimulus Reconstruction for EEG-Based Auditory Attention Decoding
In this article, presented at
ICASSP 2023
, we present an update of the unsupervised stimulus decoder that avoids its inherent bias to the initialization.
Nicolas Heintz
,
Simon Geirnaert
,
Tom Francart
,
Alexander Bertrand
June, 2023
In Proceedings of
ICASSP 2023
, 2023
PDF
Cite
Dataset
DOI
Signal Processing Algorithms for EEG-based Auditory Attention Decoding
In May 2022, I obtained my PhD degree in Electrical Engineering under the supervision of
Prof. Tom Francart
and
Prof. Alexander Bertrand
summa cum laude with congratulations from the board of examiners.
Simon Geirnaert
,
Tom Francart
,
Alexander Bertrand
May, 2022
PhD thesis
PDF
Cite
Video
Time-Adaptive Unsupervised Auditory Attention Decoding Using EEG-Based Stimulus Reconstruction
In this article, publlished in
IEEE Journal of Biomedical and Health Informatics
, we present a new time-adapative unsupervised stimulus decoder for AAD.
Simon Geirnaert
,
Tom Francart
,
Alexander Bertrand
March, 2022
IEEE Journal of Biomedical and Health Informatics
, vol. 26, no. 8, pp. 3767-3778, 2022
PDF
Cite
DOI
Dataset I
Dataset II
Demo
Electroencephalography-Based Auditory Attention Decoding: Toward Neurosteered Hearing Devices
In this article, published in
IEEE Signal Processing Magazine
, we provide a broad review and a statistically grounded comparative study of EEG-based AAD algorithms and address the main signal processing challenges in this field.
Simon Geirnaert
,
Servaas Vandecappelle
,
Emina Alickovic
,
Alain de Cheveigné
,
Edmund Lalor
,
Bernd T. Meyer
,
Sina Miran
,
Tom Francart
,
Alexander Bertrand
June, 2021
IEEE Signal Processing Magazine
, vol. 38, no. 4, pp. 89-102, 2021
PDF
Cite
Slides
DOI
Dataset I
Dataset II
Riemannian Geometry-Based Decoding of the Directional Focus of Auditory Attention Using EEG
In this article, presented at
ICASSP 2021
, we present a novel method to decode the spatial focus of auditory attention from EEG using Riemmanian geometry-based classifiers.
Simon Geirnaert
,
Tom Francart
,
Alexander Bertrand
June, 2021
In Proceedings of the
ICASSP 2021
, 2021
PDF
Cite
Code
Dataset
Poster
Slides
DOI
Video Presentation
»
Cite
×