Search Results for author: Michael Tangermann

Found 12 papers, 5 papers with code

Synthesizing EEG Signals from Event-Related Potential Paradigms with Conditional Diffusion Models

no code implementations27 Mar 2024 Guido Klein, Pierre Guetschel, Gianluigi Silvestri, Michael Tangermann

Data scarcity in the brain-computer interface field can be alleviated through the use of generative models, specifically diffusion models.

S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention

no code implementations18 Mar 2024 Pierre Guetschel, Thomas Moreau, Michael Tangermann

Motivated by the challenge of seamless cross-dataset transfer in EEG signal processing, this article presents an exploratory study on the use of Joint Embedding Predictive Architectures (JEPAs).

Brain Decoding EEG +2

UMM: Unsupervised Mean-difference Maximization

no code implementations20 Jun 2023 Jan Sosulski, Michael Tangermann

In each trial, for every available letter our approach makes the hypothesis that it is in fact the attended letter, and calculates the ERPs based on each of these hypotheses.

Brain Computer Interface

An embedding for EEG signals learned using a triplet loss

no code implementations23 Mar 2023 Pierre Guetschel, Théodore Papadopoulo, Michael Tangermann

In offline analyses using EEG data of 14 subjects, we tested the embeddings' feasibility and compared their efficiency with state-of-the-art deep learning models and conventional machine learning pipelines.

Brain Computer Interface EEG +3

Embedding neurophysiological signals

1 code implementation IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence, and Neural Engineering (MetroXRAINE) 2022 Pierre Guetschel, Théodore Papadopoulo, Michael Tangermann

Neurophysiological time-series recordings of brain activity like the electroencephalogram (EEG) or local field potentials can be decoded by machine learning models in order to either control an application, e. g., for communication or rehabilitation after stroke, or to passively monitor the ongoing brain state of the subject, e. g., in a demanding work environment.

Brain Computer Interface Domain Adaptation +3

Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints

no code implementations26 Aug 2021 Jan Sosulski, David Hübner, Aaron Klein, Michael Tangermann

We could show that for 8 out of 13 subjects, the proposed approach using Bayesian optimization succeeded to select the individually optimal SOA out of multiple evaluated SOA values.

Bayesian Optimization Brain Computer Interface

Learning User Preferences for Trajectories from Brain Signals

no code implementations3 Sep 2019 Henrich Kolkhorst, Wolfram Burgard, Michael Tangermann

Robot motions in the presence of humans should not only be feasible and safe, but also conform to human preferences.

Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filters

1 code implementation27 Apr 2018 Andreas Meinel, Henrich Kolkhorst, Michael Tangermann

Based on electroencephalography data of 18 healthy subjects, we found that the components' distinct temporal envelope dynamics are highly subject-specific.

Brain Computer Interface

Post-hoc labeling of arbitrary EEG recordings for data-efficient evaluation of neural decoding methods

no code implementations22 Nov 2017 Sebastian Castaño-Candamil, Andreas Meinel, Michael Tangermann

In the present contribution, we thrive to remove many shortcomings of current simulation frameworks and propose a versatile alternative, that allows for objective evaluation and benchmarking of novel data-driven decoding methods for neural signals.

Benchmarking EEG +1

Deep learning with convolutional neural networks for EEG decoding and visualization

5 code implementations15 Mar 2017 Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball

PLEASE READ AND CITE THE REVISED VERSION at Human Brain Mapping: http://onlinelibrary. wiley. com/doi/10. 1002/hbm. 23730/full Code available here: https://github. com/robintibor/braindecode

EEG Eeg Decoding

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