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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
 

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Article DOI: 10.3791/64959-v • 06:09 min • September 8th, 2023
September 8th, 2023 •
1, 1, 1, 2, 3,4, 1
1Brain and Body Sensing Lab, Mike Wiegers Department of Electrical & Computer Engineering, Kansas State University, 2Adaptive Cognitive Assessment Laboratory, Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, 3Direct Brain Interface Laboratory, Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, 4Direct Brain Interface Laboratory, Department of Biomedical Engineering, University of Michigan, Ann Arbor

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Resumo
Automatic Translation

This article presents a method for estimating same-day P300 speller Brain-Computer Interface (BCI) accuracy using a small testing dataset.

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Keywords: P300 Brain-computer Interface Speller Performance Estimation Classifier-based Latency Estimation CBLE Accuracy Prediction EEG Dataset Brain Invader Linear Regression RMSE VCBLE
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