AI-based Clinical Decision Support System for Early Detection of iNPH
Overview
This project has been awarded by Fundación ASISA as part of their first call for research and social action support. The research focuses on developing an AI-powered clinical decision support tool that leverages video analytics and computer vision techniques to enable early detection of idiopathic normal pressure hydrocephalus (iNPH).
Research Objectives
- Develop computer vision algorithms for gait and mobility analysis in elderly patients
- Create machine learning models for early detection of iNPH biomarkers
- Build a clinical decision support system for neurology departments
- Validate the system in clinical settings with real patient data
Technical Approach
The project combines expertise in:
- Video-based human pose estimation
- Gait analysis and movement pattern recognition
- Deep learning for biomedical applications
- Clinical workflow integration
Funding Details
| Field | Value |
|---|---|
| Funding Agency | Fundación ASISA |
| Award Type | Research Grant |
| Amount | 6,000 EUR |
| Duration | 2026-2027 |
| Principal Investigator | Unai Elordi |
| Researchers | David Campo Caballero ( Facultad de Medicina y Enfermeria, Osakidetza), Elsa Fernandez Gómez, Ignacio Arganda-Carreras |
| Affiliation | CVPD Research Group |
Related Research Lines
This project aligns with the CVPD group’s research in:
- Computer vision and gait analysis
- Machine learning and deep learning for healthcare
- Video-based human pose estimation
- Clinical decision support systems
- Bioimage analysis and medical AI
Project Status
Status: Active (Awarded September 2026)
More Information
Part of the first edition of Fundación ASISA Research Awards, which granted 60,000 EUR across ten projects (five in health research and five in social initiatives).
Unai Elordi
Assistant Professor
My research interests include computer vision, pattern recognition, and artificial intelligence for intelligent video analytics.
Ignacio Arganda-Carreras
Ikerbasque Research Associate Professor
My research interests include image processing, computer vision, and deep learning for biomedical applications.