ZiF Research Group
Cognitive Behavior of Humans, Animals, and Machines:
Situation Model Perspectives
October 2019 – July 2020
Convenors: Werner Schneider (Bielefeld, GER), Helge Ritter (Bielefeld, GER)
Andrea Finke graduated in Computer Science for the Natural Sciences at Bielefeld University. Afterwards, she joined the CoR-Lab, where she worked on a joint project with the Honda Research Institute to develop a Brain-Robot Interface for the humanoid ASIMO robot. She is currently a researcher at CITEC and the Neuroinformatics Group at Bielefeld University, where she is responsible for the Brain-Computer Interface research.
Current Main Research Interests
Andrea's research is centered around novel EEG-based and multi-modal Brain-Computer Interface paradigms for different patient populations, such as those with Disorders of Consciousness, and also for healthy users. She focuses in particular on Machine Learning based methods and algorithms for modeling and classifying neural and other biophysiological data in real-time under real-world conditions.
Five selected publications with particular relevance to the Research Group
- Hachmeister, N., Finke, A., Ritter, H. (In Press). Does machine-mediated interaction induce inter-brain synchrony? — A hyperscanning study. Presented at the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14), IEEE EMBS:1-4.
- Finke, A., Steppacher, I., Kissler, J., & Ritter, H. (2018). Frequency band variations predict EEG single-trial classification performance in disorder of consciousness patients. International Engineering in Medicine and Biology Conference (EMBC'18), 1927-1930.
- Finke, A., Essig, K., Marchioro, G., & Ritter, H. (2016). Toward FRP-based brain-machine interfaces—single-trial classification of fixation-related potentials. PloS one, 11(1), e0146848.
- Finke, A., & Ritter, H. (2016). Discriminating object from non-object perception in a visual search task by joint analysis of neural and eyetracking data. International Conference on Neural Information Processing, 546-554. Springer, Cham.
- Riechmann, H., Finke, A., & Ritter, H. (2013). Hierarchical codebook visually evoked potentials for fast and flexible BCIs. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2776-2779.