David Steyrl

David’s research focus is on applying machine-learning techniques and statistical signal processing methods to psychological questions, modeling and formalizing exposure therapy, and applying rt-fMRI based neurofeedback to train brain-states with dynamic paradigms.

Past research focused on adaptive (bio-) signal processing and machine learning, with application to simultaneous EEG-fMRI and EEG based Brain-Computer Interfaces.

2016

Müller-Putz G, (ed.), Huggins J, (ed.), Steyrl D, (ed.). Proceedings of the 6th International Brain-Computer Interface Meeting: BCI Past, Present, and Future. Graz: Verlag der Technischen Universität Graz, 2016. 261 S. doi: 10.3217/978-3-85125-467-9

Steyrl D, Schwarz A, Müller-Putz GR. The MIRAGE91 Brain-Computer Interface. 2016. doi: 10.13140/RG.2.2.30530.61125

2015

Schwarz A, Scherer R, Steyrl D, Faller J, Muller-Putz GR. A co-adaptive sensory motor rhythms Brain-Computer Interface based on common spatial patterns and Random Forest. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 1049-1052 doi: 10.1109/embc.2015.7318545

Scherer R, Faller J, Opisso E, Costa U, Steyrl D, Muller-Putz GR. Bring mental activity into action! An enhanced online co-adaptive brain-computer interface training protocol. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 2323-2326 doi: 10.1109/embc.2015.7318858

Steyrl D, Patz F, Krausz G, Edlinger G, Muller-Putz GR. Reduction of EEG artifacts in simultaneous EEG-fMRI: Reference layer adaptive filtering (RLAF). in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 3803-3806 doi: 10.1109/embc.2015.7319222

Schwarz A, Scherer R, Steyrl D, Faller J, Müller-Putz GR. A Co-adaptive SMR-BCI Based on Common Spatial Patterns and Random Forest. 2015. doi: 10.13140/RG.2.2.27175.16809

2014

Muller-Putz GR, Steyrl D, Faller J. Adaptive hybrid brain-computer interaction: Ask a trainer for assistance! in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Chicago: IEEE. 2014. S. 1493-1496 doi: 10.1109/embc.2014.6943884

Bauernfeind G, Steyrl D, Brunner C, Muller-Putz GR. Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: A comparison between different classifiers. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Chicago: IEEE. 2014. S. 2004-2007 doi: 10.1109/embc.2014.6944008

Wriessnegger SC, Steyrl D, Koschutnig K, Müller-Putz GR. Short time sports exercise boosts motor imagery patterns: implications of mental practice in rehabilitation programs. Frontiers in Human Neuroscience. 2014 Jun 30;8:469. doi: 10.3389/fnhum.2014.00469

Bauernfeind G, Pokorny C, Steyrl D, Wriessnegger S, Pichler G, Schippinger W et al. Improved Classification of Auditory Evoked Event-Related Potentials. in Müller-Putz G, Hrsg., Proceedings of the 6th International Brain-Computer Interface Conference 2014: the future of brain-computer interaction: basics, shortcomings, users ; September 16 - 19, 2014, Graz University of Technology, Austria. Graz: Verlag der Technischen Universität Graz. 2014 doi: 10.3217/978-3-85125-378-8-62

Müller-Putz G, (ed.), Bauernfeind G, (ed.), Brunner C, (ed.), Steyrl D, (ed.), Wriessnegger S, (ed.), Scherer R, (ed.). Proceedings of the 6th International Brain-Computer Interface Conference 2014. Graz: Verlag der Technischen Universität Graz, 2014. 407 S. doi: 10.3217/978-3-85125-378-8

2013

Steyrl D, Wriessnegger SC, Müller-Putz GR. Single Trial Motor Imagery Classification in EEG Measured During FMRI Image Acquisition - A First Glance. Biomedical Engineering / Biomedizinische Technik. 2013 Sep;58(Suppl 1):000010151520134450. doi: 10.1515/bmt-2013-4450

Steyrl D, Scherer R, Müller-Putz GR. Random forests for feature selection in non-invasive brain-computer interfacing. in Holzinger A, Pasi G, Hrsg., Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data. Berlin: Springer-Verlag Berlin-Heidelberg. 2013. S. 207-216 doi: 10.1007/978-3-642-39146-0_19

Steyrl D. Single trial Motor Imagery classification in EEG measured during fMRI image acquisition – a first glance. 2013. doi: 10.13140/RG.2.2.20464.28163

Steyrl D, Scherer R, Förstner O, Müller-Putz G. Using random forests for classifying motor imagery EEG: Random Forests vs Regularized LDA - Non-linear Beats Linear. in Müller-Putz G, Hrsg., Proceedings of the 6th International Brain-Computer Interface Conference 2014: the future of brain-computer interaction: basics, shortcomings, users ; September 16 - 19, 2014, Graz University of Technology, Austria. Graz: Verlag der Technischen Universität Graz. 2013. S. 252-255 doi: 10.3217/978-3-85125-378-8-61

2012

Steyrl D. On the suitability of random forests for detecting mental imagery for non-invasive brain-computer interfacing. 2012.