Fernando Lopes da Silva

Research Topics

Research Topics 2022


Identification and classification of awake-sleep states in implanted Brain Computer Interfaces

Summary: A Brain-Computer Interface (BCI) allows its user to control a computer with brain activity. As part of the Utrecht NeuroProsthesis (UNP) study, people with locked-in syndrome have been implanted with an electrocorticography-based BCI that allows them to communicate at home. Our users should be able to use the system during the day and at night, but the latter has proven to be a challenge. The goal of the project is to improve classification of the BCI at night. Any insights from this project might be implemented in the home-system of our UNP participants for real-time testing.

Supervising team:

  • Mariska Vansteesel, Mariana Branco, Zachary Freudenburg (UMCU)
  • João Sanches and Agostinho Rosa (IST)


EEG-based motor Imagery-BCIs with EMBODIED feedback for stroke rehabilitation

Summary: EEG-based Motor Imagery Brain-Computer Interfaces (BCIs) have been shown to be effective in restoring motor function after stroke, by promoting neuroplasticity and improving neurorehabilitation results when compared with traditional approaches. In this line of research, neuroscientists, computer scientists, biomedical engineers and robotic engineers get together in a multi-disciplinary team to address this problem by developing an EEG-based Motor Imagery BCI for controlling embodied feedback (e.g., in virtual reality or robots), with the objective of further improving neuroplasticity.

Supervising team:

  • Athanasios Vourvopoulos, Patrícia Figueiredo, João Sanches and José Santos-Victor (IST)
  • Mariana Branco and Mathijs Raemaekers (UMCU).