Training and Research





Class attendance

Free Choice



Learning objectives

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.

Prerequisites and basic notions

The recommended prerequisites of the course are basic familiarity with signal processing and programming in Matlab.


- Introduction to the BCI model. Motivation for BCI. Its historical context and recent approaches. The BCI technology.
- Applications: in medicine, prevention of risk situations, smart environments, gaming etc.
- Invasive and non-invasive BCIs
- EEG-based control signals: evoked (e.g., SSVEP and P300 speller) vs. self-paced.
- Signal processing (filtering, feature extraction, classification) and the interpretation of the results.
- Kinesthetic motor imagery and introduction to a typical architecture of EEG-based MI-BCI (calibration and usage phases).
- The role of machine learning in BCIs.
- The classification problem and how to access performances.
- Case studies.

Laboratory. The lab involves implementing an MI-BCI interface in Matlab. Students will use EEGlab to create Matlab scripts and work on EEG-BCI data, filtering the data, extracting features like power spectral density, coherence, and correlation in the frequency bands of interest, implementing a classifier to distinguish different imagined movements. Finally, they will interpret the results obtained.


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When and where

Borgo Roma, Ca’ Vignal, Room to be defined.
Tentative Schedule
• Tuesday, March 11, 2025
• Tuesday, March 18, 2025
• Tuesday, March 25, 2025
• Tuesday, April 1, 2025
• Tuesday, April 8, 2025
• Tuesday, April 15, 2025

Learning assessment procedures

The exam consists in developing a short project in Matlab for analyzing EEG-BCI data. This task will require students to apply the knowledge gained during the course, facing challenges related to processing and interpreting brain signals.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE


To pass the exam, the students must show that: - they have understood the theoretical and practical concepts of the course; - they are able to use the knowledge acquired during the course to solve the assigned problems related to the processing of EEG-based BCI signals; - they are able to program in MATLAB environment in the context of signal processing.

Criteria for the composition of the final grade

Pass/no pass.

Sustainable Development Goals - SDGs

This initiative contributes to the achievement of the Sustainable Development Goals of the UN Agenda 2030. More information on sustainability
Salute e benessere (GOAL 3)

PhD school courses/classes - 2024/2025

PhD School training offer to be defined



Bombieri Nicola

symbol email symbol phone-number +39 045 802 7094

Bontempi Pietro

symbol email symbol phone-number +39 045 802 7614

Boschi Federico

symbol email symbol phone-number +39 045 802 7272

Boscolo Galazzo Ilaria

symbol email symbol phone-number +39 045 8127804

Calanca Andrea

symbol email symbol phone-number +39 045 802 7847

Cristani Marco

symbol email symbol phone-number +39 045 802 7841

Daldosso Nicola

symbol email symbol phone-number +39 045 8027076 - 7828 (laboratorio)

Di Marco Roberto

symbol email symbol phone-number +39 045 802 7847

Enrichi Francesco

symbol email symbol phone-number +390458027051

Fiorini Paolo

Fiorini Paolo

symbol email symbol phone-number 045 802 7963

Fummi Franco

symbol email symbol phone-number 045 802 7994

Giachetti Andrea

symbol email symbol phone-number +39 045 8027998

Lora Michele

symbol email symbol phone-number 0458027847

Marziliano Pina

Marzola Pasquina

symbol email symbol phone-number 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Menegaz Gloria

symbol email symbol phone-number +39 045 802 7024

Muradore Riccardo

symbol email symbol phone-number +39 045 802 7835

Pizzini Francesca Benedetta

symbol email symbol phone-number 00390458124301

Pravadelli Graziano

symbol email symbol phone-number +39 045 802 7081

Setti Francesco

symbol email symbol phone-number +39 045 802 7804

Storti Silvia Francesca

symbol email symbol phone-number +39 045 802 7850

Visentin Francesco

symbol email symbol phone-number +39 045 802 7964

PhD students

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Course lessons
PhD Schools lessons


Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2024/2025.