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AI-Assisted Rehabilitation Interface for Wheelchair Users

AI-Assisted Rehabilitation Interface for Wheelchair Users

he solution is an innovative, offline AI-assisted rehabilitation platform mounted directly onto wheelchairs, designed to support users with severe mobility and speech disabilities. Developed through clinical co-validation with the Bristol Centre for Enablement (BCE), this system addresses the critical challenge of configuring complex assistive technologies.

The platform integrates an offline, privacy-preserving generative AI module with multimodal sensing including cameras, microphones and environmental sensors. It provides wheelchair users with safe, real-time voice control over their devices without relying on cloud connectivity. Simultaneously, it supports clinical engineers by offering guided setup routines, real-time multimodal feedback and automated drafting of session notes.

By automating repetitive calibration and administrative tasks, the system significantly reduces clinician workload while keeping the human-in-the-loop for security oversight. This enables clinicians to focus on direct patient care and drastically improves patient independence and engagement. Our open-source, edge-AI architecture ensures affordability, scalability and strict adherence to NHS data security standards, presenting a replicable framework for the future of inclusive, AI-driven rehabilitation technology.

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  • Organization
    University of the West of England (UWE Bristol), Integrated Care Academy (ICA) and Bristol Centre for Enablement (BCE NHS Trust)
  • Profession
    AI offline voice control and multimodal wheelchair integration

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