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Andreas Meinel

andreas-meinel.jpg Brain State Decoding Lab 
Albertstr. 23
D-79104 Freiburg im Breisgau 
Office: 00.009 (ground floor)
Phone:   +49 761 203 5330


Research Interests

My research focuses on two main areas:

1) Robust brain state decoding methods: I work on novel machine learning methods for robust single-trial brain state decoding in the field of brain-computer interface research. Specifically, my work focuses on approaches to capture and monitor the functional role of oscillatory brain states.

2) Clinical BCI application in post-stroke motor rehabilitation: The above described methods are utilized for a brain-state dependent hand motor training for stroke rehabilitation.

About me

since 03/2014: PhD student in the BSD Lab.

04/2011 - 05/2013: Master of Science in Physics at the Ludwig-Maximilians-University, Munich, Germany. Master thesis at the chair for Bio- und Nanophotonics at the Albert-Ludwig-University Freiburg.

10/2007 - 09/2010: Bachelor of Science in Physics at the University of Konstanz, Germany. Bachelor thesis at the Center for the Study of Emotion and Attention at the University of Florida, Gainesville, USA.


Journal papers

A. Meinel, S. Castaño-Candamil, B. Blankertz, F. Lotte, M. Tangermann, "Characterizing Regularization Techniques for Spatial Filter Optimization in Oscillatory EEG Regression Problems", Springer Neuroinformatics (2018) [link]

A. Meinel, S. Castaño-Candamil, J. Reis, M. Tangermann, "Pre-Trial EEG-based Single-Trial Motor Performance Prediction to Enhance Neuroergonomics for a Hand Force Task", Frontiers in Human Neuroscience 10 (2016) [link]

Selected conference papers

A. Meinel, F. Lotte, M. Tangermann, "Tikhonov Regularization Enhances EEG-Based Spatial Filtering For Single-Trial Regression", Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 308-313 (2017) [link]

A. Meinel, T. Koller, M. Tangermann,"Time-Frequency Sensitivity Characterization of Single-Trial Oscillatory EEG Components", The First Biannual Neuroadaptive Technology Conference 36-37 (2017) [link]

M. Tangermann, A. Meinel, "Informative Oscillatory EEG Components and their Persistence in Time and Frequency", NEUROTECHNIX 2017 - Extended Abstracts Volume 1: CogNeuroEng 17-21 (2017)

A. Meinel, K. Eggensperger, M. Tangermann, F. Hutter, "Hyperparameter Optimization for Machine Learning Problems in BCI", Proceedings of the 6th International Brain-Computer Interface Meeting: BCI Past, Present, and Future 184 (2016) [link]

A. Meinel, E. M. Schlichtmann, T. Koller, J. Reis, M. Tangermann, "Predicting Single-Trial Motor Performance from Oscillatory EEG in Chronic Stroke Patients", Proceedings of the 6th International Brain-Computer Interface Meeting: BCI Past, Present, and Future 140 (2016) [link]

A. Meinel, J. S. Castaño-Candamil, S. Dähne, J. Reis, M. Tangermann, "EEG Band Power Predicts Single-Trial Reaction Time in a Hand Motor Task", Proc. Int. IEEE Conf. on Neural Eng. (NER) 182–185 (2015) [link]