The aim of this course is to propose an introduction to the basics of Brain Computer Interfaces (BCI) principally based on oscillatory EEG activity from a signal processing point of view. The course will introduce the main data processing methods that allow to decode brain activity in real time and convert it into a control signal for a BCI. In the first part the students will learn the following topics: the BCI model, the main BCI types with relative basic signal processing techniques for feature extraction and classification, the performance of the systems, the limitations of the current paradigms and the broad range BCI applications. The second part will cover practical BCI design and use, with an introduction to real-time processing of EEG recordings. Collaboration among students with different backgrounds will be encouraged through research-oriented practical group projects.
- Introduction to the BCI model and its historical context
- Invasive and non-invasive BCIs
- Evoked vs. self-paced BCIs
- Signal processing and the data interpretation (filtering, feature extraction, classification)
- The BCI technology
- Example of applications and how to access performances
- Applications and case studies
Laboratory. Data analysis: preprocessing (epoching and noise reduction), frequency-domain processing, train a support vector machine classifier to decode imagined movement of single trials, test classifier with cross-validation.
Course Prerequisites: the recommended prerequisites of the course are basic familiarity with signal processing and programming in Matlab.
Educational material will be available to students enrolled in the course on the Moodle platform. This material includes lecture presentations in PDF format and material related to laboratory activities.
For further details and supplementary materials, please refer to the reference book.
Brain-Computer Interfaces 1: Foundations and Methods, Maureen Clerc, Laurent Bougrain, Fabien Lotte
Schedule: To be defined (September 2022 – Cà Vignal 2)
The students will be evaluated on practical group projects concerning a type of brain computer interface application.
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