Wearable Technology and Machine Learning for Early Detection and Risk Assessment of Unacceptable Toxicities in a Paediatric Oncology Cohort
WEARABLES: Wearable Technology and Machine Learning for Early Detection and Risk Assessment of Unacceptable Toxicities in a Paediatric Oncology Cohort
Murdoch Childrens Research Institute
150 participants
Oct 15, 2025
OBSERVATIONAL
Conditions
Summary
Data collection study to establish a predictive model of infection observed during childhood cancer therapy using data captured by wearable technology.
Eligibility
Inclusion Criteria8
- Paediatric, adolescent or young adult diagnosis of cancer AND receiving therapy placing them at risk of infection
- Receiving cancer treatment at The Royal Children's Hospital
- Patients aged 5-18 years at time of the eligibility screening
- If aged < 16 years, parent or guardian able to provide consent
- iPhone 8 or later (iOS must be up to date/updated at time of enrolment)
- At least 10MB of iPhone storage for WEARABLES app and data collection.
- Willing and able to wear a wearable device for a period of 4 weeks (during waking hours).
- Consent to data being shared to the WEARABLES app (owned by the research team).
Exclusion Criteria4
- <5 years of age.
- <16 years of age without guardian or parent consent.
- Aged 16-18 and unable to provide consent.
- Participant did not consent to wearing Apple Watch for a period of 4 weeks.
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Interventions
Wearable device to collect the following health metrics directly from participants for the duration of the study (4 weeks). Health metrics are collected every 15 minutes, except for the ECG which will be collected once per week. Data points: * ECG data (Once per week) * Exercise time * Body Temperature * Heart Rate * Irregular Heart Rhythm * Blood Oxygen Saturation * Respiratory Rate
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07030998