Wearable Technologies for Children with Chronic Illnesses: An Exploratory Approach.

Abstract

To determine the utility of wearable technologies in physical activity assessment in three paediatric diseases, namely, Niemann-Pick C (NP-C), Juvenile Idiopathic Arthritis (JIA) and Duchenne Muscular Dystrophy (DMD). Exploratory study SETTING AND PATIENTS: Thirty children were recruited across three UK hospitals (Royal Manchester's Children Hospital, Great Ormond Street Children's Hospital, and the Great North Children's Hospital). Ten were diagnosed with NP-C, eight with DMD and twelve with JIA. All participants completed the 6-min walk test (6MWT) at enrolment. Patients were provided with disease-specific smartphone apps paired with a wearable device via Bluetooth. Ambulation was recorded in 30-min epochs measuring average daily maximum (ADM), average daily steps (ADS) and average daily steps per 30-min epoch (ASE). Median 6MWT results were 450m, 325m and 434.5m for the NP-C, DMD and JIA cohorts, respectively. Wearable data capture was feasible in all three disease cohorts, although complete data capture was not sustained. A statistically significant between-cohort difference was identified for ADM, ADS and ASE. Statistically significant differences were found between DMD/JIA for ADM; NP-C/DMD for ADS and DMD/JIA for ASE. Wearable sensor technologies have the potential to provide additional information for our understanding of ambulation in chronic paediatric disease. The wearable devices were easy to use and popular with patients although key features need to be addressed to appropriately meet study objectives. As the technology continues to evolve at a rapid pace, opportunities to implement child friendly solutions are already available.