Pseudo-online framework for BCI evaluation: a MOABB perspective using various MI and SSVEP datasets

• Published in: Journal of neural engineering Vol. 21; no. 1; pp. 16003 - 16023
• Main Authors: Carrara, Igor, Papadopoulo, Theodore
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 01.02.2024
• Subjects: Algorithms; BCI-EEG; Brain-Computer Interfaces; deep learning; Electroencephalography - methods; Evoked Potentials; Humans; Imagery, Psychotherapy; machine learning; MOABB; pseudo online BCI; Riemann geometry; BCI-EEG; deep learning; Riemann geometry; machine learning; MOABB; pseudo online BCI

Objective . BCI (Brain–Computer Interfaces) operate in three modes: online , offline , and pseudo-online . In online mode, real-time EEG data is constantly analyzed. In offline mode, the signal is acquired and processed afterwards. The pseudo-online mode processes collected data as if they were rece...