During my work, I was involved in the development of softwares and/or librairies dedicated to Brain-Computer Interface research and applications.
So far, our objective was to make these developments available to the community, by distributing these softwares under free and open-source licences.
T. de Surrel, S. Chevallier, F. Lotte, F. Yger, "Geometry-Aware visualization of high dimensional Symmetric Positive Definite matrices", Transactions on Machine Learning Research, 2025 - pdf
M.S. Yamamoto, F. Lotte, F. Yger, S. Chevallier, "Class-distinctiveness-based frequency band selection on the Riemannian manifold for oscillatory activity-based BCIs: preliminary results", IEEE EMBS Engineering in Medecine and Biology Conference (EMBC'22), 2022 - pdf
M.S. Yamamoto, K. Sadatnejad, T. Tanaka, M.R. Islam, F. Dehais, Y. Tanaka, F. Lotte, "Modeling complex EEG data distribution on the Riemannian manifold toward outlier detection and multimodal classification", IEEE Transactions on Biomedical Engineering, 2023 - pdf
S. Kumar, F. Yger, F. Lotte, "Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces", IEEE International Winter Conference on Brain-Computer Interfaces, 2019 - pdf
LR Krol, J Pawlitzki, F Lotte, K Gramann, TO Zander, "SEREEGA: Simulating Event-Related EEG Activity", Journal of Neuroscience Methods, vol. 309, pp. 13-24, 2018 - preprint pdf (not final) - final pdf
A. Meinel, S. Castaño-Candamil, B. Blankertz, F. Lotte, M. Tangermann, "Characterizing Regularization Techniques for Spatial Filter Optimization in Oscillatory EEG Regression Problems", Neuroinformatics, 2018 - draft pdf - final version
F. Lotte, C. Jeunet, "Towards Defining and Quantifying Mental Imagery-based BCI Users' skills", Journal of Neural Engineering, 2018 - pdf
F. Lotte, "Signal processing approaches to minimize or suppress calibration time in oscillatory activity-based Brain-Computer Interfaces", Proceedings of the IEEE, vol. 103, no. 6, pp. 871-890, 2015 - pdf
F. Lotte, C.T. Guan, "Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms", IEEE Transactions on Biomedical Engineering, vol. 58, no. 2, pp. 355-362, 2011 - pdf
OpenViBE is a free and open-source software platform for the acquisition, processing, classification and display of brain signals (e.g., EEG, MEG, ECoG, ...). The platform consist in a set of software modules that can be integrated easily and efficiently, in order to design real-time applications for neuroscience including Brain-Computer Interfaces (BCI) and neurofeedback.
It is made to be easy, in the sense that by using OpenViBE, it becomes possible to rapidly create a BCI without writing a single line of code.
Indeed, OpenViBE enables users to design a BCI by using only graphical programming, simply by adding and assembling together boxes, each box corresponding to a given processing module (see pictures below)
Fig. 1: Graphical design of a BCI or neurofeedback system using OpenViBE
OpenViBE already proposes various features and processing modules in order to design a BCI, such as:
Processing modules: temporal filters, spatials filters, ICA, windowing, FFT, time-frequency analysis, inverse solutions, etc.
Classification modules: linear discriminant analysis, classifier combination, fuzzy inference systems, etc.
Visualization modules: raw signal, 2D topography, 3D topography, spectrums, etc.
Easy interaction with virtual reality applications
Acquisition from various EEG devices
Ready-to-use BCI: motor imagery based BCI (binary of multiclass, synchronous or self-paced), P300-based BCI, neurofeedback, ...
Fig. 2: Some modules for real-time visualization of brain activity in OpenViBE
For more details and to download (for free) the OpenViBE platform, you may go there: http://openvibe.inria.fr/
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