In this live demonstration the RIDDANCE (distuRb-resIstant Dry electroDe-based brAiN Computer intErface) framework is presented. It is a Brain-Computer Interface (BCI) framework that characterizes and counteracts several factors that make difficult applying BCIs to real life contexts. RIDDANCE exploits data from an 8-channel dry EEG headset by g. Tec, Data collection for training/testing is typically carried out in not controlled environment (often disturbed) to improve the training and the classification robustness. For the purpose RIDDANCE embeds a user-tailored neural network (NN) topology selector that find the most robust model in terms of average validation loss. RIDDANCE is optimized for P300-based tasks and tested in a prototype car driving application.

Live Demonstration: A Dry electrode-based Brain Computer Interface for P300-based Car Driving / Mezzina, Giovanni; Brunetti, Alberto Fakhri; Ciccarese, Dionisio; Mascellaro, Grazia; Saragaglia, Cataldo Luciano; De Venuto, Daniela. - ELETTRONICO. - (2023), pp. 1-1. (Intervento presentato al convegno 2023 IEEE International Symposium on Circuits and Systems (ISCAS) tenutosi a Monterey, CA USA nel 21-25 May 2023) [10.1109/ISCAS46773.2023.10181355].

Live Demonstration: A Dry electrode-based Brain Computer Interface for P300-based Car Driving

Mezzina, Giovanni;Brunetti, Alberto Fakhri;Ciccarese, Dionisio;Mascellaro, Grazia;Saragaglia, Cataldo Luciano;De Venuto, Daniela
2023-01-01

Abstract

In this live demonstration the RIDDANCE (distuRb-resIstant Dry electroDe-based brAiN Computer intErface) framework is presented. It is a Brain-Computer Interface (BCI) framework that characterizes and counteracts several factors that make difficult applying BCIs to real life contexts. RIDDANCE exploits data from an 8-channel dry EEG headset by g. Tec, Data collection for training/testing is typically carried out in not controlled environment (often disturbed) to improve the training and the classification robustness. For the purpose RIDDANCE embeds a user-tailored neural network (NN) topology selector that find the most robust model in terms of average validation loss. RIDDANCE is optimized for P300-based tasks and tested in a prototype car driving application.
2023
2023 IEEE International Symposium on Circuits and Systems (ISCAS)
978-1-6654-5109-3
Live Demonstration: A Dry electrode-based Brain Computer Interface for P300-based Car Driving / Mezzina, Giovanni; Brunetti, Alberto Fakhri; Ciccarese, Dionisio; Mascellaro, Grazia; Saragaglia, Cataldo Luciano; De Venuto, Daniela. - ELETTRONICO. - (2023), pp. 1-1. (Intervento presentato al convegno 2023 IEEE International Symposium on Circuits and Systems (ISCAS) tenutosi a Monterey, CA USA nel 21-25 May 2023) [10.1109/ISCAS46773.2023.10181355].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/255960
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact