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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
Manoj Thulasidas1, Cuntai Guan
1Neural Signal Processing Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. manoj@i2.a-star.edu.sg.
This study optimized Brain Computer Interface (BCI) spellers for performance and usability. High accuracy (99%) was achieved with minimal training and channels, making BCI a viable communication tool for disabled individuals.
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