EEG-based real-time BCI system using drones for attention visualization
Attention management is crucial for cognitive development, especially in children. This study presents a novel brain-computer interface (BCI) system that uses EEG signals to classify attention states. It analyzes these signals using a waveform ratio feature extraction method and visualizes attention levels through a drone's altitude. The system provides real-time feedback via a GUI and incorporates gamified elements like drone control to enhance engagement and training efficacy. Experimental results show that positive response mechanisms significantly improve focus and motivation, demonstrating the system's potential to transform traditional attention training methods.
Authors
- Chengyuan Shen (ORCID: https://orcid.org/0009-0002-2130-5295)
- Linfeng Sui (ORCID: https://orcid.org/0000-0003-3969-0670)
- Ran Zhang (ORCID: https://orcid.org/0000-0002-9514-7253)
- Lan Xu (ORCID: https://orcid.org/0000-0002-8807-7787)
- Jianting Cao (ORCID: https://orcid.org/0009-0000-3413-9789)
Institutions
- Saitama Institute of Technology (JP)
- RIKEN Center for Advanced Intelligence Project (JP)
- Shandong University of Science and Technology (CN)
Publication Details
- Journal
- Computer Methods in Biomechanics & Biomedical Engineering
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1080/10255842.2025.2459272
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 4.29