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Fabien Lotte

Researcher at L'Abri

Publications -  189
Citations -  11832

Fabien Lotte is an academic researcher from L'Abri. The author has contributed to research in topics: Brain–computer interface & Electroencephalography. The author has an hindex of 42, co-authored 179 publications receiving 9441 citations. Previous affiliations of Fabien Lotte include University of Bordeaux & French Institute for Research in Computer Science and Automation.

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A review of classification algorithms for EEG-based brain–computer interfaces

TL;DR: This paper compares classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG) in terms of performance and provides guidelines to choose the suitable classification algorithm(s) for a specific BCI.
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A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update

TL;DR: A comprehensive overview of the modern classification algorithms used in EEG-based BCIs is provided, the principles of these methods and guidelines on when and how to use them are presented, and a number of challenges to further advance EEG classification in BCI are identified.
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Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms

TL;DR: Results showed that the best RCSP methods can outperform CSP by nearly 10% in median classification accuracy and lead to more neurophysiologically relevant spatial filters and enable us to perform efficient subject-to-subject transfer.
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Openvibe: An open-source software platform to design, test, and use brain--computer interfaces in real and virtual environments

TL;DR: The OpenViBE software platform is described which enables researchers to design, test, and use braincomputer interfaces (BCIs) and its suitability for the design of VR applications controlled with a BCI is shown.
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Brain-Computer Interfaces, Virtual Reality, and Videogames

TL;DR: Major challenges must be tackled for brain-computer interfaces to mature into an established communications medium for VR applications, which will range from basic neuroscience studies to developing optimal peripherals and mental gamepads and more efficient brain-signal processing techniques.