Self‑adjusting AI to personalize help from robotic prostheses and exoskeletons
Official title: A new framework for self-adaptive artificial intelligence to personalize assistance for patients using robotic exoskeletons and prostheses
Funded at Georgia Institute of Technology · NIH-11381552 · Data updated 2026-11-12
This project builds smart AI that helps robotic prostheses and exoskeletons give personalized walking support to people after lower‑limb amputation or stroke.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Georgia Institute of Technology NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project start | September 19, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $944,400 |
| NIH project number | 4DP2HD111709-02 |
| Project ID | NIH-11381552 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with lower‑limb amputation or stroke‑related walking impairment who can participate in device testing and community walking sessions.
✕Less likely to help
People with only upper‑limb problems, those who cannot walk or tolerate device testing, or those with unstable medical conditions are unlikely to receive direct benefit from this project.
What this research studies
If I join, the team will build AI that learns my walking patterns and changes how a robotic prosthesis or exoskeleton helps me in real time. They will use wearable sensors and predictive machine‑learning to infer my intent and adapt assistance without long, user‑specific training. The researchers plan to test the system outside the lab during community walking so it can work in everyday environments rather than only on treadmills. People with lower‑limb amputation and stroke will try prototype devices in real‑world settings to measure quicker and more accurate adaptation.
Why it matters
Potential benefit: If successful, this could make wearable robotic devices feel more natural, improve walking ability, reduce fall risk, and increase independence for users.
How similar studies have gone: Some lab‑based adaptive control studies have shown promise, but self‑adapting AI that works reliably in real‑world community walking is largely novel and less proven.
Where this research is happening
-
Georgia Institute of Technology
Atlanta, United States Active
Researchers
- Principal investigator: Young, Aaron John — Georgia Institute of Technology
- Study coordinator: Young, Aaron John
Related research
Other NIH-funded projects on the same topics.
-
Integrative AI tools to map protein sequences to structures and functions
A scientist team will develop advanced AI methods to better connect protein sequences, their 3D shapes, and how they work, using large biological data from sequencing and structures.
-
Robotic ultrasound-guided clot removal for stroke treatment
A new robot-assisted ultrasound system is being developed to help quickly reopen brain arteries during a stroke, with testing in patient-specific 3D-printed models and animal studies.
-
siRNA nanoparticle treatment to stop diabetic kidney damage
A new nanoparticle-delivered gene-silencing treatment aims to lower kidney inflammation in people with diabetes to help protect their kidneys.
-
Nanosensor blood test to spot early pancreatic cancer fingerprints
This project will use a nanosensor blood test to detect early-stage pancreatic cancer by reading a disease 'fingerprint' in patient serum.
-
Synergistic blood-brain barrier opening and targeted glioma treatment with pulsed electric fields
A new approach uses tiny, rapid electric pulses to safely disrupt the brain's protective barrier and enhance targeted treatment for malignant glioma.
-
Dexterous needle ablation for ventricular arrhythmia guided by MRI
A new MRI-guided, robot-assisted catheter delivers deeper heart tissue ablation to treat ventricular tachycardia.
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.