Analysis of Biomedical Data

Electroencephalography is one of the most popular methods used for the acquisition of neural data in Brain-Computer Interfacing (BCI). Recently, BCI entered a broader scope of definition and monitoring and decoding the mental state of humans became an active research field. As mental states are reflectances of sensation, perception and decision making, this makes BCI a perfect candidate to provide insights into the neural processing of quality experience.

One part of our research is concerned with the development of robust techniques for the analysis of these high-dimensional, noisy and non-stationary signals. We investigated robust divergences-based approaches for parameter estimation and optimization in the context of Brain-Computer Interfacing and developed novel EEG-based technoloqy for extracting brain correlations for user’s perceived quality.


  1. F. Shahbazi Avarvand, S. Bosse, K.-R. Müller, G. Nolte, T. Wiegand, R. Schäfer, G. Curio, and W. Samek, "Objective Quality Assessment of Stereoscopic Images with Vertical Disparity using EEG", Journal of Neural Engineering, IOP Publishing, vol. 14, no. 4, May 2017.
  2. S. Bosse, L. Acqualagna, W. Samek, A. K. Porbadnigk, G. Curio, B. Blankertz, K.-R. Müller, and T. Wiegand, "Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition", IEEE Transactions on Circuits and Systems for Video Technology, April 2017.
  3. W. Samek, D. Blythe, G. Curio, K.-R. Müller, B. Blankertz, and V. V. Nikulin, "Multiscale temporal neural dynamics predict performance in a complex sensorimotor task", NeuroImage, Elsevier Inc., vol. 141, pp. 291–303, November 2016.
  4. S. Brandl, L. Frølich, J. Höhne, K.-R. Müller, and W. Samek, "Brain-Computer Interfacing under Distraction: An Evaluation Study", Journal of Neural Engineering, vol. 13, no. 5, pp. 056012, October 2016.
  5. W. Samek, "On robust spatial filtering of EEG in nonstationary environments", it-Information Technology, Distinguished Dissertations, vol. 58, no. 3, pp. 150–154, June 2016.
  6. S. Dähne, F. Bießmann, W. Samek, S. Haufe, D. Goltz, C. Gundlach, A. Villringer, S. Fazli, and K.-R. Müller, "Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data", Proceedings of the IEEE, vol. 103, no. 9, pp. 1507-1530, September 2015.
  7. S. Fazli, S. Dähne, W. Samek, F. Bießmann, and K.-R. Müller, "Learning from more than one Data Source: Data Fusion Techniques for Sensorimotor Rhythm-based Brain-Computer Interfaces", Proceedings of the IEEE, vol. 103, no. 6, pp. 891-906, June 2015.
  8. S. Bosse, K.-R. Müller, T. Wiegand, and W. Samek, "Brain-Computer Interfacing for Multimedia Quality Assessment", Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, pp. 002834-002839, October 2016.