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Accelerating cognitive assessment for people with MND.

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CognoMND is an innovative digital tool designed to assess cognitive function and behaviour in individuals with Motor Neuron Disease (MND). By incorporating key questions from CognoMemory, alongside new questions inspired by widely-used clinical assessments, CognoMND offers a comprehensive approach to evaluating cognitive abilities. This tool also includes a care partner assessment, allowing caregivers to provide valuable insights and additional information to support a more complete evaluation of the individual's cognitive and behavioural health.

How it works?

CognoMND is a user-friendly digital tool designed to assess cognitive abilities and behavior in people with Motor Neuron Disease (MND). It consists of a series of questions and tasks that evaluate memory, attention, language, and behavior. These assessments can be completed by the individual with MND, while a care partner can also provide additional insights through a separate assessment. The results offer a comprehensive view of cognitive function, helping healthcare providers monitor changes over time and support personalized care.

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Patient or Caregiver conversation with CognoMND virtual agent is recorded

Speech is analysed for patterns

Clinicians receive a report

Current pathway

Patients + care not supported

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Hospital visit

Busy clinic + Multiple assessments

Less time for cognitive and behavioural testing, Specialist psychologist not always available

Future pathway

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Abnormal Result 

  • Referred to hospital services

  • Caregiver support offered

  • Reassured + repeat monitoring at home

  • Resources saved 

  • Hospital services directed to those who need it

Normal Result

Meet our team

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Prof Heidi Christensen

Co-PI and Technical lead. Professor in the Department of Computer Science in the Speech and Hearing Group at the University of Sheffield. Heidi has been working at the leading edge of speech technology research for 20 years and has made internationally recognised contributions in the field of speech technology for healthcare.

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Dr Dan Blackburn

Co-PI & Clinical lead. Senior Lecturer at the University of Sheffield and Honorary Consultant Neurologist. Dan’s research interests are into developing non-invasive scalable diagnostic tests for early dementia or cognitive impairment. Dan will oversee recruitment, diagnoses and overall project management including continued strong engagement with ethnic minority groups.

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Lise Sproson

She is an experienced Public Patient Involvement and Engagement (PPIE) researcher and will be coordinating all PPIE activity and links with ethnic minority groups and user evaluation stakeholders.

Dr Leslie Ing

Dr Leslie Ing

Neurologist and NIHR Clinical Research Fellow with expertise in dementia and MND. Leslie's research interests are in the early detection of cognitive impairment in people with MND.

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Chris McDermott

Professor Chris McDermott is a consultant neurologist and co-director of the Sheffield MND care and research centre. He leads a research group in the University of Sheffield whose main focus is to improve outcomes for people living with MND. He co-leads the development of CognoMND.

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Emily Mayberry

Clinical Psychologist and Research Psychologist

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Prof Sharon Abrahams

Professor Sharon Abrahams’ research focuses on the changes in thinking and behaviour, which can occur in some people with MND.

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Swapnil Gadgil

Co-founder of Therapy Box. Swapnil will lead the work on commercialisation and general software development including Memory Assessment Pathway integration infrastructure.

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Rebecca Bright

Co-founder of Therapy Box. Rebecca will lead the work on seeking regulatory approval and user experience for the software development team.

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Annie Galvin

Project Manager from Therapy Box. Works on digital project management and coordination.

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Clare Bartlett

Project Manager for the NIHR Devices for Dignity

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Fuxiang Tao

Research Associate

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Vijithan Jeyakody

Vijithan is a skilled software developer. They played a key role in coding and implementing crucial features for CognoMND

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