Chronic wounds affect up to 1.8 million people in Germany, significantly impacting patient quality of life and placing a massive financial burden on the healthcare system. Because wound care is often managed by non-specialized nursing staff, there is a high risk of documentation errors and delayed treatments.

The IKIAWu project aims to bridge this gap by developing an advanced, interactive support system. By integrating data-driven technologies that have previously been considered too high-risk for commercial development, IKIAWu is setting a new standard for digital health.

The project is built upon three central pillars designed to support healthcare professionals at the Point of Care (PoC):

• Advanced Image Recognition: While current AI tools focus on standard wound types, IKIAWu extends these capabilities to “underrepresented” cases. This includes the detection of rare wound entities, malignant changes, and accurate assessment across diverse skin tones (e.g., dark skin), which are often overlooked in existing databases.

• The Digital Nose (eNose): One of the most innovative aspects of the project is the integration of olfactory parameters. By using gas sensors to detect Volatile Organic Compounds (VOCs), the system can “smell” bacteria. This is intended to enable faster and more cost-effective detection of microbiological colonization of wounds, as well as correlation with image recognition.

• AI-Based Chatbot: To combat the shortage of specialized experts, an interactive chatbot provides evidence-based, guideline-compliant knowledge. This acts as a real-time digital consultant, assisting nursing staff in making informed decisions for individualized patient care.

Project volume:
1,51 million € (75% of which is funded by the BMFTR)

Funding institution:
Federal Ministry of Research, Technology and Space (BMFTR)

Funding period:
01.09.2025 to 31.08.2028

Project Coordination:

• sciendis GmbH, (WUNDERA®) Leipzig

Project partners: University Hospital of Essen

• Nursing Directorate, Department of Nursing Development and Nursing Research
• Department of Dermatology, Venerology and Allergology
• Institute for Artificial Intelligence