Imagine a smart system that can tell when a person with dementia is in pain or anxious, even if they can't speak. It uses wearable gadgets and virtual reality to soothe patients and help them feel better. It's like giving doctors and families a translator for a patient's hidden distress.
Care for dementia patients is currently reactive and often fails to detect pain and distress in non-verbal patients. This leads to avoidable healthcare use and high caregiver stress.
Explainable AI (XAI) models for pain and anxiety detection and a multilingual medical concept extraction service for unstructured text.
If you are a wearable device manufacturer dealing with low clinical adoption in elderly care — this project developed AI models for the Polar 360 wearable that detect pain and anxiety. This allows your hardware to provide actual medical insights rather than just fitness tracking.
If you are an EHR provider dealing with messy, unstructured medical notes — this project developed a multilingual service to extract medical concepts like problems and treatments from text. This automates data entry and improves clinical workflow efficiency.
If you are a nursing home operator dealing with high caregiver burnout and reactive symptom control — this project developed VR-supported pain management and early care planning tools. This shifts care to a preventive model, reducing avoidable healthcare costs.
Based on available project data, specific pricing or cost structures for the developed tools are not provided.
The project uses a consortium of 16 partners across 13 countries, suggesting a design intended for wide European adoption. It specifically targets a global health concern affecting over 55 million people.
Based on available project data, there is no specific mention of patents or licensing terms, though it is a Horizon-RIA funded project.
The system is designed to work with the Polar 360 wearable and integrates a multilingual service into a Patient Sensing Network.
The project period runs from 2024-01-01 to 2027-12-31, indicating that final results will be available by the end of 2027.
The consortium is well-balanced for commercialization, featuring 16 partners with a 25% industry ratio (4 companies). The presence of 6 SMEs indicates a strong capacity for agile development and potential spin-offs, while 6 universities and 4 research centers provide the necessary scientific validation across 13 different countries.
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