Conceptual Priming for In-game BCI Training
summary
Claim: embedding BCI training inside a game — either as explicit in-game training or as implicit priming — raises immersion and flow without improving classifier accuracy. Method: 36 subjects play a modified Doom 3 level while EEG (g.tec, 14–16 electrodes) is recorded; ICA and a single-trial classifier with 200 ms overlap and priming windows (50–1000 ms) are used. Results: state-of-the-art 65–70% classification accuracy across conditions; GEQ flow/immersion rises from ~1.8/1.5 (baseline) to 2.78/2.67 (explicit) and 3.27/3.12 (implicit).
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chapters (10)
- 0:00Introduction and setup
- 1:50Brain-computer interface basics
- 3:33Synchronous vs asynchronous training
- 5:20Traditional training paradigms
- 6:44Conceptual priming explained
- 8:51Priming in BCI training
- 9:53Game-based training study
- 12:43Results and performance metrics
- 13:48User immersion and flow
- 15:31Future directions and Q&A
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