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Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot study

arXiv 2211.10352 ↗First posted 4 Nov 2022eess.SP cs.LGcited by 0

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Abstract (arXiv)

Speeding up the spelling in event-related potentials (ERP) based Brain-Computer Interfaces (BCI) requires eliciting strong brain responses in a short span of time, as much as the accurate classification of such evoked potentials remains challenging and imposes hard constraints for signal processing and machine learning techniques. Recent advances in stimulus presentation and deep learning showcased a promising direction in significantly improving the efficacy of those systems, in this study we propose the combination of colored inverted face stimulation with classification using convolutional neural networks in the hard settings of dry electrodes and fast flashing single-trial ERP-based BCI. The high online accuracy achieved, with two subjects passing the 90 percent correct symbol detection bar and a transfer rate above 60 bits per minute, demonstrates the approach potential in improving the practicality of ERP based BCIs.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 74 references that are in the map. First posted on arXiv 4 Nov 2022.

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References · 14

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  3. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  4. 2014Going Deeper with Convolutionscited by 4,231
  5. 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,857
  6. 2017Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inferencecited by 1,548
  7. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,447
  8. 2017Mixed Precision Trainingcited by 1,135
  9. 2015Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)cited by 1,061
  10. 2016EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfacescited by 616
  11. 2017To prune, or not to prune: exploring the efficacy of pruning for model compressioncited by 596
  12. 2019Deep learning-based electroencephalography analysis: a systematic reviewcited by 155
2 more
  1. 2020EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfacescited by 62
  2. 2019A few filters are enough: Convolutional Neural Network for P300 Detectioncited by 1

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