A practical hybrid BCI speller for Chinese Character Input: Integrating an Eye Tracker into a P300-Based Spelling approach
Author:
Affiliation:
1. College of Intelligence Science and Technology, National University of Defense Technology, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3569966.3570046
Reference24 articles.
1. Predictive Spelling With a P300-Based Brain–Computer Interface: Increasing the Rate of Communication
2. Improving P300 spelling rate using language models and predictive spelling
3. Utilizing a Language Model to Improve Online Dynamic Data Collection in P300 Spellers
4. G. Kshirsagar , N. Londhe: Weighted Ensemble of Deep Convolution Neural Networks for Single-Trial Character Detection in Devanagari-Script-Based P300 Speller . IEEE T. Cogn. Dev. Syst . 12(3) ( 2020 ). G. Kshirsagar, N. Londhe: Weighted Ensemble of Deep Convolution Neural Networks for Single-Trial Character Detection in Devanagari-Script-Based P300 Speller. IEEE T. Cogn. Dev. Syst. 12(3) (2020).
5. Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces
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