Privacy-aware radar-centric British Sign Language recognition and translation for healthcare communication

About the project

About the Project Supervisory Team: Dr Shelly Vishwakarma This project explores how British Sign Language users could interact with healthcare and smart devices with greater privacy, choice and independence. Using radar-centric multimodal AI, the project will study how signing movements can be recognised and translated without relying on cameras, speech or wearable sensors. It aims to complement, not replace, qualified interpreters. Sign language users are often excluded from technologies designed for spoken communication, including smart devices, digital health systems and automated patient services. In sensitive settings such as healthcare, some British Sign Language (BSL) users may value greater privacy, autonomy and choice in selected interactions, alongside support from qualified interpreters. This project will address the research challenge of developing privacy-aware BSL recognition and translation using radar-centric multimodal sensing. Radar can capture body, arm and hand movements without recording identifiable camera images, making it a promising technology for non-intrusive sign language recognition. You'll develop AI methods that combine radar signals with privacy-aware information such as skeletal keypoints, contextual prompts and language models to support expressive BSL recognition and translation. The work will focus on carefully bounded healthcare and smart-device use cases, such as appointment check-in, requesting communication support, symptom-category reporting and medication reminders. The aim is not to replace qualified BSL interpreters, but to complement existing accessibility support and give signers greater choice, privacy and control. You'll join the EPSRC-funded RADAR-SIGN-BRIDGE project and work within the Digital Health and Biomedical Engineering group at the University of Southampton. You'll access radar sensing facilities, computing resources, interdisciplinary supervision, and training in radar signal processing, machine learning, multimodal AI, responsible innovation and assistive technology. The project will also involve collaboration with experts in language technology and engagement with Deaf community stakeholders. Entry requirements You must have a UK 2:1 honours degree or its international equivalent . Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages. How to apply Apply now You need to: choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences select Full time or Part time search for programme PhD Computer Science (7089) add name of the supervisor in section 2 of the application Applications should include: research proposal your CV (resumé) 2 academic references degree transcripts and certificates to date English language qualification (if applicable) Contact us Faculty of Engineering and Physical Sciences If you have a general question, feps-pgr-apply@soton.ac.uk . Project leader For an initial conversation, S.Vishwakarma@soton.ac.uk .

Research areas