Industrialisation of a transformative soft-stretchy sensor tool for family-led paediatric bimanual therapy

A handheld device using soft silicone sensors will track how well children with upper limb disabilities can move their hands, pinch, grip, and write in real time, then suggest personalised therapy exercises. The problem is that children with conditions such as cerebral palsy or brachial plexus injury often need intensive bimanual therapy—using both hands together—to improve coordination and strength. Current therapy relies on periodic clinical assessments that capture only snapshots of ability. Parents leading daily therapy at home have no way to measure progress objectively or adjust exercises between appointments. This project industrialises a soft, stretchy sensor technology that conforms to a child’s hand. The device gathers continuous data on mobility and dexterity, then feeds it into an algorithm that recommends specific exercises. If successful, it could shift paediatric upper limb therapy from clinic-based, episodic care to data-driven, family-led sessions at home. That would give clinicians richer information on real-world function, reduce the burden on specialist services, and help children improve more consistently between visits. The technology itself—a highly sensitive, comfortable sensor—could later be adapted for other rehabilitation contexts, such as adult stroke recovery or prosthetic control.