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- W2991297747 abstract "Making training more seamless is one of the main challenges for BCIs in order to become a modality for common interaction. We explore the integration of BCI training for tasks in a real environment. We propose two implicit training protocols. Firstly, the Fully Implicit Synchronous Training (FIST) protocol involves a passive observation of the control actions. Secondly, the gamified Wizard-of-Oz (WOzGT) protocol simulates executing commands in such a way as to make users believe they are at the origin of the execution. We describe and present an experiment in a smart home as a proof of concept. We compare the implicit protocols to the standard BCI training baseline (EST): FIST vs. WOzGT vs. EST in experiment controlling a smart home with Conceptual Imagery. FIST and EST have similar performance ($sim 70$% accuracy, $sim 1230$ms time to correct classification) and usability ($sim 70$% percentile SUS). WOzGT leads to improved performance (+5.23%, -40ms) and usability (+5) compared to EST/FIST." @default.
- W2991297747 created "2019-12-05" @default.
- W2991297747 creator A5068310449 @default.
- W2991297747 date "2019-10-01" @default.
- W2991297747 modified "2023-09-25" @default.
- W2991297747 title "Towards An Implicit, In-Situ Training Protocol for EEG-based Brain-Computer Interfaces: a Feasibility Study" @default.
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- W2991297747 doi "https://doi.org/10.1109/smc.2019.8914214" @default.
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