Remote monitoring & gaming technology for children with CF

  • Research type

    Research Study

  • Full title

    Project Fizzyo: Remote monitoring and gaming technology for improving physiotherapy prescription, adherence and prediction of clinical outcomes in children with cystic fibrosis.

  • IRAS ID

    228625

  • Contact name

    Eleanor Main

  • Contact email

    e.main@ucl.ac.uk

  • Sponsor organisation

    UCL Great Ormond Street Institute of Child Health

  • Clinicaltrials.gov Identifier

    CEA010, Cystic Fibrosis Trust Clinical Excellence and Innovation Awards 2017; KEI2017-01-04, Higher Education Innovation Fund, Knowledge Exchange and Innovation Fund

  • Duration of Study in the UK

    3 years, 6 months, 13 days

  • Research summary

    Airway clearance treatments (ACTs) and physical activity can mitigate the progression of CF lung disease, but these routine physiotherapy treatments are burdensome and adherence is low. Traditional research methods have failed to produce credible evidence to guide practice, partly because ‘blinding’ isn’t possible and patient preference can confound results.

    We have worked with engineers and designers to develop an electronically chipped sensor (Fizzyo sensor) which mounts onto standard widely used airway clearance devices. This sensor monitors breathing during routine airway clearance. Additionally wearable activity trackers can monitor physical activity. We can now facilitate automatic transmission of ACT and physical activity data to clinicians and researchers caring for children with CF. Industry partners (Microsoft) and UCL computer science experts have helped us build an airway clearance and physical activity feedback dashboard app for patients and carers. This team has also developed computer games driven by breathing through an airway clearance device for this app (to enhance treatment enjoyment and adherence).

    The project will use this technology for passive remote capture and transmission of daily longitudinal data during airway clearance and physical activity to assess impact of different adherence levels on clinical outcomes. Innovative big data analysis methods will be used to find out whether:

    1) Children with CF should do regular ACTs or physical activity, and what the minimum effective dose is
    2) Physical activity levels have an impact on clinical outcomes
    3) Airway clearance or physical activity is more effective in different children (and how to choose)
    4) Some ACTs are better than others
    5) Airway clearance gaming helps children do treatments more regularly, and whether better adherence improves health
    6) Remote monitoring and big data analysis can provide a valuable alternative to traditional research methods and help identify sensitive composite outcome measures for children with mild signs and symptoms.

  • REC name

    London - Brighton & Sussex Research Ethics Committee

  • REC reference

    18/LO/1038

  • Date of REC Opinion

    16 Aug 2018

  • REC opinion

    Further Information Favourable Opinion