Developing a brain-computer interface to help paralyzed individuals control devices
An Intracortical Brain-Computer Interface Model for High Efficiency Development of Closed-Loop Neural Decoding Algorithms
['FUNDING_R01'] · EMORY UNIVERSITY · NIH-11076586
This study is working on a special brain-computer interface that helps people with severe paralysis control devices like prosthetic limbs or computers just by thinking, making it easier for them to interact with the world around them.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | EMORY UNIVERSITY (nih funded) |
| Locations | 1 site (ATLANTA, UNITED STATES) |
| Trial ID | NIH-11076586 on ClinicalTrials.gov |
What this research studies
This research focuses on creating an intracortical brain-computer interface (iBCI) that records brain signals to predict a person's intentions, enabling them to control assistive devices like prosthetic limbs or computer cursors. The approach involves training a modular recurrent neural network (RNN) using data from able-bodied individuals to simulate neural activity. This model aims to overcome challenges in decoding intentions from brain signals, which is crucial for helping severely paralyzed individuals interact with their environment. By generating real-time neural data, the project seeks to improve the effectiveness of assistive technologies.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals with severe paralysis who are seeking improved methods to interact with assistive technologies.
Not a fit: Patients with conditions that do not involve severe paralysis or those who do not require assistive devices may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly enhance the ability of paralyzed individuals to control devices and improve their quality of life.
How similar studies have performed: While the approach of using brain-computer interfaces is established, this specific model utilizing a modular RNN for real-time neural data generation is innovative and has not been extensively tested.
Where this research is happening
ATLANTA, UNITED STATES
- EMORY UNIVERSITY — ATLANTA, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: DANZIGER, ZACHARY C — EMORY UNIVERSITY
- Study coordinator: DANZIGER, ZACHARY C
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 below.