AI-based Clinical Decision Support System for Early Detection of iNPH

Wed, 23 Sep 2026 00:00:00 +0000

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

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).

David Campo Caballero | CVPD Research group