Challenge

To gathered data within a paediatric population that can be used to provide evidence for clinical practice. Currently there is little scientific evidence on the benefits of assistive technologies, potentially due to the difficulty in measuring such benefits outside of the clinic.

Issues such as device abandonment and associated costs as well as overinflated perception of high-quality expert care by the patient and family can not be adequately addressed without this data.

It is essential to know if the interventions are working, to prevent device abandonment, false hopes, and unnecessary effort.

Challenge Image

Science

Rehabilitative and assistive devices, such as mobility and postural aids, can restore or replace the loss of mobility caused by a disability.  A high proportion (70%) of interventions for children with Cerebral Palsy have low or inconclusive evidence supporting their effectiveness.

This project applies state of the art sensor technology, integrated within mobility and postural assistive devices to understand how data gathered within a paediatric population can be used to provide evidence for clinical practice.

The system has been developed to collect movement and kinematic data longitudinally both at home and within clinical settings.  The use of sensors to measure motion, potential for feedback to the user, parent or the health professional.  The project explored the types of possible data and the potential impact of capturing quantifiable data on healthcare outcomes.

Impact

As assistive devices (such as wheelchairs, walking frames, and communication devices) form a large part of standard care for children with CP, a systematic, objective and disciplined approach to measuring clinical outcome is needed when prescribing them.

Opportunities exist to utilise longitudinal data to improve the intervention and to provide better engagement with the user through gamification.

In partnership with

Ulster University, Queen's University and Invest Northern Ireland