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RehabAI: Towards Adaptive, Data-Driven Rehabilitation Planning

The Team

Dr Isibor Kennedy Ihianle, Nottingham Trent University 

Dr Pedro Machado, Nottingham Trent University 

Prof Ahmad Lofti, Nottingham Trent University 

Partners:

Dr Kerry Burvill, Nottingham University Hospitals NHS Trust 

Charlotte Leask, Headway Nottingham 

Mediprospects AI 

Project Summary

Rehabilitation planning for stroke, brain injury, and other neurological conditions is complex, resource-intensive, and often relies on generalised guidelines rather than personalised strategies. This creates an unmet need for intelligent tools that can account for the diverse clinical, psychological, and social factors that shape recovery. 

This project addresses that need by developing an advanced decision-support system that uses artificial intelligence to recommend tailored rehabilitation plans. Unlike existing tools, our approach goes beyond clinical data integrating data-driven modelling with behavioural economics to balance clinical outcomes, patient experience, and resource implications. 

We have already built a proof-of-concept prototype that demonstrates personalised recommendations using synthetic patient data. This project will extend the system’s capabilities, testing its feasibility as a strategic planning tool for both individual patient journeys and wider service level forecasting. 

The expected outcome is a robust prototype that demonstrates technical feasibility and translational potential, laying the foundation for clinical testing and eventual NHS integration. By enabling personalised care and more efficient resource planning, this Feasibility Impact Primer project aligns closely with EMERGE RehabTech’s vision of transforming rehabilitation through technology, driving improvements in patient outcomes and service efficiency across the UK. 

Contact: isibor.ihianle@ntu.ac.uk