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Research Portfolio


Evaluation of a new clinical service to allow video-sharing and remote care for people with epilepsy



grant amount:

£49,726 over 12 months Awarded in 2020

lead investigator:

Professor Sameer Zuberi


- Dr Neil Patel (University of Glasgow)
- Prof Emanuele Trucco (University of Dundee)
- Mr Neil Anand (Healthcare Improvement Scotland)
- Prof Helen Cross
- Prof Finbar O’Callaghan (UCL GOS ICH)
- Dr Jay Shetty (Royal Hospital for Sick Children Edinburgh)
- Dr Ailsa McLellan (Edinburgh)
- Prof Sam Wiebe (Calgary, ILAE)
- Prof Jon Stone (University of Edinburgh)
- Dr Craig Heath (Glasgow)
- Dr Ian Morrison (Tayside)
- Prof Stephen McKenna (University of Dundee)
- Dr Philippus Brink (University of Dundee)
- Dr Stephen Elma (Royal Aberdeen Children’s Hospital)
- Dr Graham Mackay (University of Aberdeen)
- Dr Santosh Ravindra Mordekar (Sheffield Children’s Hospital NHS Foundation Trust)
- Dr Michael Absoud (Evelina Children’s Hospital)
- Dr Anita Devlin (Newcastle Upon Tyne Hospitals NHS Foundation Trust)
- Dr Ela Akay (Newcastle Upon Tyne Hospitals NHS Foundation Trust)
- Dr Rohini Rattihalli (Oxford University Hospitals NHS Foundation Trust)
- Prof Arjune Sen (University of Oxford)


University of Glasgow


Accurate correct diagnosis of epilepsy depends on expert history taking or witnessing an event. Access to both is limited resulting in high rates of misdiagnosis, inappropriate investigations and treatment. We want to know whether harnessing the universal availability and scale of smartphone video capability can improve epilepsy diagnosis and management.

"Finding ways to harness the everyday technologies of patients and their carers to improve epilepsy care will empower patients, make them feel more connected to their clinical teams and, in turn, allow those teams to be more responsive to their patients. Better, more accurate data will reduce harm from misdiagnosis, inappropriate tests and medication.

The Study

We have designed an NHS trusted platform, vCreateNeuro, which allows rapid, secure transfer of videos from patients and families to clinical teams. The system allows patients to input history and clinicians to classify events. One service alone has uploaded around 1000 videos for 500 patients in 6 months. With 15 services participating we can study data from thousands of people and through surveys and interviews understand whether our innovation can prevent misdiagnosis, unnecessary hospital visits & investigations and lead to faster diagnosis and treatment. We will test the feasibility of smartphone video to develop artificial intelligence programmes to diagnose epilepsy.


This innovation is impacting epilepsy care now. Bringing smartphone video early into the referral process speeds up diagnosis. The video database is a resource to study seizure types and events that mimic seizures. Machine learning programmes linked to smartphones could allow rapid diagnosis worldwide in resource-poor countries with limited access to neurologists.