234 citations · 628 across the 22 of their papers we have counts for
6 papers · 1 filter
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding
Kay Gregor Hartmann, Robin Tibor Schirrmeister, Tonio Ball
Recently, there is increasing interest and research on the interpretability of machine learning models, for example how they transform and internally represent EEG signals in Brain…
The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks
Joos Behncke, Robin Tibor Schirrmeister, Wolfram Burgard +1
The importance of robotic assistive devices grows in our work and everyday life. Cooperative scenarios involving both robots and humans require safe human-robot interaction. One im…
Deep Transfer Learning for Error Decoding from Non-Invasive EEG
Martin Völker, Robin T. Schirrmeister, Lukas D. J. Fiederer +2
We recorded high-density EEG in a flanker task experiment (31 subjects) and an online BCI control paradigm (4 subjects). On these datasets, we evaluated the use of transfer learnin…
Brain Responses During Robot-Error Observation
Dominik Welke, Joos Behncke, Marina Hader +6
Brain-controlled robots are a promising new type of assistive device for severely impaired persons. Little is however known about how to optimize the interaction of humans and brai…
Deep learning with convolutional neural networks for decoding and visualization of EEG pathology
Robin Tibor Schirrmeister, Lukas Gemein, Katharina Eggensperger +2
We apply convolutional neural networks (ConvNets) to the task of distinguishing pathological from normal EEG recordings in the Temple University Hospital EEG Abnormal Corpus. We us…
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills
Felix Burget, Lukas Dominique Josef Fiederer, Daniel Kuhner +8
As autonomous service robots become more affordable and thus available also for the general public, there is a growing need for user friendly interfaces to control the robotic syst…