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In this paper, we present a new signal processing technique for the group analysis of stimulus-following neural responses, building upon our conference precursor. Again, all code is available!

In this article, we perform absolute attention decoding to speech based on EEG signals, to determine whether a subject is attending to the speech or not.

In this article, we demonstrate how a new object-based video feature leads to robust correlations with the decoded activity from EEG when subjects are watching natural videos.

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.

In this article, published in Signal Processing, we present a novel sparse variable selection method for generalized Rayleigh quotient optimization and generalized eigenvalue problems, which are ubiquitous in many signal processing fields.

In this article, publlished in IEEE Journal of Biomedical and Health Informatics, we present a new time-adapative unsupervised stimulus decoder for AAD.

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.

In this article, presented in IEEE Journal of Biomedical and Health Informatics, we present a novel unsupervised algorithm to train a stimulus decoder for AAD.

In this article, published in IEEE Transactions on Biomedical Engineering, we propose a new common spatial pattern-based algorithm to decode the spatial focus of auditory attention from EEG signals.

In this article, published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, we present a novel interpretable performance metric for AAD algorithms based on an adative gain control system.