1 citations · 3 across the 4 of their papers we have counts for
4 papers
Exploring new territory: Calibration-free decoding for c-VEP BCI
J. Thielen, J. Sosulski, M. Tangermann
This study explores two zero-training methods aimed at enhancing the usability of brain-computer interfaces (BCIs) by eliminating the need for a calibration session. We introduce a…
UMM: Unsupervised Mean-difference Maximization
Jan Sosulski, Michael Tangermann
Many brain-computer interfaces make use of brain signals that are elicited in response to a visual, auditory or tactile stimulus, so-called event-related potentials (ERPs). In visu…
Introducing Block-Toeplitz Covariance Matrices to Remaster Linear Discriminant Analysis for Event-related Potential Brain-computer Interfaces
Jan Sosulski, Michael Tangermann
Covariance matrices of noisy multichannel electroencephalogram time series data are hard to estimate due to high dimensionality. In brain-computer interfaces (BCI) based on event-r…
Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints
Jan Sosulski, David Hübner, Aaron Klein +1
The decoding of brain signals recorded via, e.g., an electroencephalogram, using machine learning is key to brain-computer interfaces (BCIs). Stimulation parameters or other experi…