Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-Based Brain-Computer Interfaces (Student Abstract)

Rally Lin, Christina Mo, Reyan Shariff, Darrick Zhang, Abdullah Alumar, Kaleb Kassaw, Leslie M. Collins, Boyla O. Mainsah

AAAI 2025 pp. 29415-29417

doi:10.1609/AAAI.V39I28.35271 /aaai/2025/lin2025aaai-assessing/

Abstract

Brain-computer interfaces (BCIs) can provide a means of communication for individuals with severe neuromuscular diseases, the target end-users. While personalized BCI machine learning models are the current standard, models trained on data from other users could reduce BCI calibration time. We use a novel dataset with BCI users with and without amyotrophic lateral sclerosis (ALS) and a popular BCI deep learning model, EEGNet, to assess the impact of population domain data on transfer learning of a P300 speller task in the ALS cohort. Results show that training on source data from the non-ALS cohort was detrimental to transfer learning. In contrast, generic EEGNet models trained on source data from the ALS cohort performed comparably as user-specific models. Our findings highlight the need for more data from target end-users populations in publicly available BCI datasets.

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Cite

Text

Lin et al. "Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-Based Brain-Computer Interfaces (Student Abstract)." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35271

Markdown

[Lin et al. "Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-Based Brain-Computer Interfaces (Student Abstract)." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/lin2025aaai-assessing/) doi:10.1609/AAAI.V39I28.35271

BibTeX

@inproceedings{lin2025aaai-assessing,
  title     = {{Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-Based Brain-Computer Interfaces (Student Abstract)}},
  author    = {Lin, Rally and Mo, Christina and Shariff, Reyan and Zhang, Darrick and Alumar, Abdullah and Kassaw, Kaleb and Collins, Leslie M. and Mainsah, Boyla O.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {29415-29417},
  doi       = {10.1609/AAAI.V39I28.35271},
  url       = {https://mlanthology.org/aaai/2025/lin2025aaai-assessing/}
}