EEG processing and analysis for Neuroscience and Brain Computer Interface: tutorial & hands-on activities
EEG processing and analysis for Neuroscience and Brain Computer Interface: tutorial & hands-on activities
Embedded Files
4 Avril 2025
Abstract – This workshop offers a comprehensive introduction to the fundamentals of EEG signal processing, covering both theoretical and practical aspects. This workshop is designed for researchers, students, and professionals interested in understanding the principles behind EEG acquisition, processing techniques, and applications in neuroscience and brain-computer interfaces (BCIs).
The workshop will begin with an overview of the neurophysiological mechanisms underlying EEG signals, exploring the neural origins of brain rhythms and the principles governing their generation. Participants will then be introduced to the technology used for non-invasive EEG recording, including different electrode configurations, amplifier characteristics, and signal acquisition techniques. Following this theoretical foundation, the session will cover the state-of-the-art EEG processing methods, focusing on data preprocessing, artifact removal, spectral and time-frequency analysis, and visualization techniques. Special emphasis will be placed on the practical implementation of these methods to ensure participants gain a working knowledge of EEG data handling.
The second half of the workshop will feature guided hands-on activities using Python, where attendees will work with real EEG datasets to apply processing techniques. The practical session will focus on the analysis of evoked potentials and sensory-motor rhythms during motor imagery tasks—key components in both cognitive neuroscience and BCI applications. Participants will learn how to extract relevant features, interpret results, and implement standard pipelines using open-source Python libraries.
By the end of the workshop, attendees will have gained valuable insights into EEG signal processing and its applications, equipping them with the necessary skills to analyze EEG data effectively for both research and BCI development. No prior experience with EEG data analysis is required, although familiarity with basic signal processing concepts and Python programming is recommended.
Agenda de la journée
Agenda de la journée
Morning Session: Theoretical Foundations & EEG Processing Techniques
10:00 – Introduction to the LUTIN Laboratory Workshops
Overview of the workshop objectives
10:15 – Neurophysiological basis and EEG recording technology
Neural origins of EEG signals
Brain rhythms and their functional significance
Non-invasive EEG systems: electrodes, amplifiers, and acquisition setups
Common EEG recording paradigms in neuroscience and BCI
Signal quality and noise considerations
11:30 – Coffee Break
11:45 – EEG Data Processing: State-of-the-Art Techniques
Preprocessing steps: filtering, re-referencing, and segmentation
Artifacts removal techniques (ASR, ICA, etc.)
Time-frequency analysis and visualization methods
13:00 – Lunch Break
Afternoon Session: Hands-on EEG Data Analysis in Python
14:30 – Introduction to EEG Data Processing in Python
Overview of Python libraries for EEG analysis (e.g., MNE-Python)
Loading and visualizing EEG datasets
Preprocessing pipelines: filtering and artifact removal
15:15 – Evoked Potential Analysis
Detecting event-related potentials (ERPs)
Averaging and statistical considerations
Visualization of ERPs
16:00 – Coffee Break
16:15 – Sensory-Motor Rhythms & Motor Imagery Analysis
Extracting and analyzing sensory-motor rhythms (SMR)
Feature extraction for BCI applications
Practical example: classification of motor imagery tasks
17:15 – Discussion & Closing Remarks
L’atelier se tiendra en anglais le 4 avril 2025, de 10h à 17h30, au LUTIN, Cité des Sciences, Etage -2 : https://maps.app.goo.gl/X8nD6s9TJ3CBvDpF6
L’inscription à l’atelier est obligatoire : https://forms.gle/kGECQZGNLKqyNzH27
Plus d'informations, ici.
Téléchargez l’ensemble des ressources de l’atelier ici.
Biographies
Biographies
Stefano Tortora
Stefano Tortora
Stefano Tortora is Research Fellow at the Department of Information Engineering of the University of Padova. He obtained a M.Sc. in Biomedical Engineering from Politecnico di Milano, Italy, in 2017, and he received a PhD in Information Engineering from the University of Padova, Italy, in 2020. The research activity of Stefano Tortora is strongly characterized by a commitment to the emerging field of Neurorobotics. In particular, he has focused on its interdisciplinary engineering and neuroscientific aspects. His research has been passionately dedicated to improving the interaction between users and robotic devices by creating a new paradigm in human-machine interfacing (HMI) fusing multimodal information coming from wearable sensors and robot’s sensors. Stefano Tortora is Team Manager of the WHi Team and WHi Students Team (University of Padova) participating since 2019 at the Cybathlon BCI Race. With his teams, Stefano Tortora won 2 gold medals, 2 silver medals and 1 bronze medals in the various Cybathlon editions, and received the BCI Jury Award for the most promising technology at the last Cybathol 2024 in Zurich.
Page updated
Google Sites
Report abuse