Precision Wound Care Collaborative: AI-Powered Multimodal Monitoring for Predictive, Preventive Healing
Build the future of wound care at UB: join an Engineering × Health Professions team creating AI-powered, multimodal monitoring to predict healing, prevent complications, and lower costs for diabetic foot, pressure, and surgical wounds.
Project description
We are building an AI-powered, multimodal wound monitoring platform to improve care quality while reducing medical costs through predictive, preventive, and continuous assessment. Focusing on diabetic foot ulcers, pressure injuries, and surgical wounds, our system fuses complementary sensing—RGB imaging, thermal, hyperspectral imaging, ultrasound, impedance, oxygenation, moisture, and photoacoustic signals—to generate objective wound metrics, detect early signs of deterioration, and forecast healing trajectories to support triage, treatment selection, and follow-up timing. This is a joint Engineering × Health Professions effort at UB, and we are actively seeking clinical collaborators and health-professional trainees to co-lead the translational pathway: defining real clinical decision points and success metrics, shaping workflow-ready product requirements, guiding study design and clinical validation, and identifying adoption/market needs so the technology is truly usable, trustworthy, and impactful at the bedside and beyond.
Project outcome
Clinical outcomes:
- Earlier detection of deterioration/complications (e.g., infection risk).
- More objective, consistent assessment and monitoring over time.
- Better triage and treatment decisions via healing-risk stratification.
Technical outcomes:
- Multimodal wound dataset (RGB, thermal, hyperspectral, ultrasound, impedance, oxygenation, moisture, photoacoustic).
- AI models for healing prediction + early-warning signals.
- Workflow-ready prototype for point-of-care/continuous monitoring.
Project details
| Length of commitment | Year-long |
| Start time | Anytime |
| In-person, remote, or hybrid? | In-person project |
| Level of collaboration | Individual student project |
| Benefits | Potential academic credit, work study and/or stipend |
| Who is eligible | All undergraduate students |
Core partners
- UB School of Engineering and Applied Science
- UB School of Medicine
Project mentor
Wenyao Xu
Professor
Computer Science and Engineering
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. After you’re approved to begin the project, your mentor will send the relevant materials. Please reference this when you get to Step 2 of the Preparation Phase.
- Attend weekly group meetings and discussion.
- Review this article: Gherardi et al., 2024
Keywords
computer engineering, health, wound care, AI, artificial intelligence