Brain-Computer Interface (BCI) using OpenViBE, an open-source software platform

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💻 Hands-on tutorial organized during the 5th Symposium on cutting-edge methods for EEG research, October 4 – 7, 2021

🕣 Wednesday, October 6, 8:30am – 11:30am (CEST)

👥 Organizers:

• Arthur Desbois, Research Engineer, Aramis team-project, Inria Paris, Paris Brain Institute
• Marie-Constance Corsi, Postdoctoral Researcher, Aramis team-project, Inria Paris, Paris Brain Institute

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Audience/Prerequisites

• Windows/Linux users curious about BCI !
• Participants must install OpenViBE from this page before the workshop. Please install from the "stable version" links (v 3.1.0).
• Linux users need to follow the build instructions

Objectives

• Getting familiar with the main concepts of BCI
• Knowing the main features proposed by OpenViBE
• Being able to run a (virtual) BCI experiment with OpenViBE
• Manipulating the fundamental blocks of OpenViBE
• Getting a hint of the main challenges in BCI research

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Timetable

Introduction - 5'

Part 1, talks and Q&A - 25'

• What is BCI? Context, paradigms and applications
• What is OpenViBE?
• Concrete examples of use of OpenViBE
• How does OpenViBE work?
• Q&A-1

Part 2, BCI-CuttingEEG protocol and Q&A - 2h

We will perform a simulation of motor imagery-based BCI experiment with a virtual subject. To this end, we will use OpenViBE to extract, preprocess and classify the EEG data.

• Intro - Prerequisites before performing a MI-BCI experiment
  • Neurophysiological mechanisms
  • Motor imagery-based BCI in practice
• Workshop - BCI-CuttingEEG protocol set-up
  • Part 1 - Training data acquisition
  • Part 2 - Classifier training scenario
  • Part 3 - Online feedback
• Q&A-2

Concluding remarks & Perspectives - 30'

• BONUS - OpenViBE
  • Developing & prototyping OpenViBE boxes
  • Forum, scripts & community
  • Scenario tutorials
  • External scripting & interfacing using Python
• BONUS - BCI research
  • Current challenges
  • Machine & User-centered approaches

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Tools & resources

• OpenViBE - official website & citation

  • download
  • tutorials
  • technical documentation
  • forum

• Python toolboxes

  • Open datasets and pipelines to perform replicable BCI studies: Mother of All BCI Benchmarks (MOABB)
  • M/EEG data analysis: MNE-Python
  • Machine Learning tool: scikit-learn
  • LSL using Python - pyLsl

References

• Papers

  • [Wolpaw et al, Clin Neurophysiol, 2002] -> to start in the BCI domain
  • [Pfurtscheller et al, Clin Neurophysiol, 1999] -> to learn more about event-related EEG/MEG (de)synchronization
  • [Lotte et al, JNE, 2018] -> to learn more about classification algorithms used in EEG-based BCI

• Books

  • [Clerc et al, Wiley, 2016a] -> Methods and Perspectives
  • [Clerc et al, Wiley, 2016b] -> Technology and Applications

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To go further...

Previous OpenViBE workshops materials:

• 6th International Brain-Computer Interface Conference
• 2016 International BCI meeting
• IEEE International Conference on Systems, Man and Cybernetics (IEEE SMC 2018)

To learn more about BCI research & events:

• International BCI Society: Webpage
• French BCI Society: CORTICO
• Competitions to promote BCI with end users: Cybathlon