BrainCap and BrainNet: An Affordable Integrated Solution for EEG Acquisition, Analysis, and BCI System Development

Description

The Research Project aims at developing:

  1. BrainCap: An EEG cap prototype balancing interoperability, cost, usability, form factor, and reliability.
  2. BrainNet: A neural network model providing EEG feature embeddings for two tasks: BrainNet-Monitoring and BrainNet-BCI, integrating neurophysiological signals for affective and cognitive evaluation.
  3. BrainTOP!: A cognitive rehabilitation video game for children with neurodegenerative conditions, using eye tracking and an EEG-based BCI for interaction.

References

[1] Burger J., Cuculo V., D'Amelio A., Grossi G., Lanzarotti R. (2025). "ECoGNet: An EEG-Based Effective Connectivity Graph Neural Network for Brain Disorder Detection", IJCNN 2025.
[2] Barbera, T., Burger, J., D’Amelio, A., Zini, S., Bianco, S., Lanzarotti, R., ... and Contreras-Vidal, J. L. (2025). "On using AI for EEG-based BCI applications: problems, current challenges and future trends". International Journal of Human–Computer Interaction, 1-20.
[3] Agnelli F., Ditroia M., Blandano G., D’Amelio A., Ghezzi O., DePaoli M., and Lanzarotti R. (2025). “A Study on Multimodal Foundation Models for Affective Video Prediction”, ICIAP 2025.
[4] Agnelli F., Blandano G., Burger J., D’Amelio A., Facchi G., Ghezzi O., Lanzarotti R., and Schmid L. (2025). "EEG-Based Mental Stress Detection: A Comparative and Explainable Study Across Tasks and Subjects", ICIAP 2025.