Improving communication for disabled individuals using brain-computer interfaces
Official title: Brain-Computer Interface in dynamic tasks with deep learning and functional connectivity analysis
Funded at California State University Fresno · NIH-10292336 · Data updated 2026-11-12
This study is working on new technology to help people with severe disabilities use their thoughts to control devices like computers or robots, by better understanding their brain signals during different activities.
Quick facts
| Grant type | R15 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | California State University Fresno NIH-funded |
| Lab location | 1 site (Fresno, United States) |
| Project start | September 1, 2021 |
| Project end | August 31, 2025 |
| Funding year | 2021 |
| Award (this year) | $396,731 |
| NIH project number | 1R15NS118581-01A1 |
| Project ID | NIH-10292336 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with severe disabilities who have limited communication abilities and could benefit from brain-computer interface technology.
✕Less likely to help
Patients without severe disabilities or those who do not have conditions affecting their communication abilities may not benefit from this research.
What this research studies
This research focuses on developing advanced machine learning algorithms to enhance the reliability of brain-computer interfaces (BCIs) for individuals with severe disabilities. By analyzing electroencephalogram (EEG) signals, the project aims to decode brain responses and translate them into commands for devices like virtual keyboards or robotic systems. The study will investigate how different types of data shifts affect brain decoding performance, particularly during dynamic tasks. This approach seeks to improve the effectiveness of BCIs in real-world clinical settings.
Why it matters
Potential benefit: If successful, this research could significantly improve communication and control for individuals with severe disabilities, enhancing their quality of life.
How similar studies have gone: Previous research has shown promise in using machine learning for brain-computer interfaces, indicating potential for success in this innovative approach.
Where this research is happening
-
California State University Fresno
Fresno, United States Active
Researchers
- Principal investigator: Cecotti, Hubert Charles — California State University Fresno
- Study coordinator: Cecotti, Hubert Charles
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.