Development of a Smart Glove for Remote Monitoring of Paediatric Limb Deformities

Every year approximately 200,000 children are born worldwide with hand and upper limb deformities. These are caused by a wide range of medical conditions (e.g. cerebral palsy) and require medical and surgical interventions. A reliable assessment of fine motor skills is crucial for evaluating these interventions and monitoring the symptoms over time.
Objectively assessing hand and upper limb function in children is a challenge. Communication difficulties mean standard methods cannot be used. Recording accurate joint positions from the patient in a way that requires no training, can surface information accurately and will not interfere with results will provide an invaluable tool to diagnose and evaluate patients, especially in situations where face to face interactions may not be possible; as with the 2020 COVID-19 pandemic.

This project aims to develop a smart glove, to read and record hand motion and grip characteristics as the patient completes tasks over teleconference with a clinician. Software will be developed to help clinicians interpret the data. The software will be designed to map measurements to clinically relevant parameters and provide more detailed insight into patient's hand movements. Using the software clinicians will be able to remotely perform diagnosis and assess the success of treatments objectively.

The glove will be designed as not to interfere with the patient while data is being collected and be simple enough to be used in a natural home environment. The final design will then be assessed on children with upper limb and hand deformities at Birmingham Children's Hospital. Opportunities for commercialisation of the device will also be explored.

Recognising patterns quickly gives machine learning a key role in streamlining the diagnosis process by detecting key features automatically and highlighting those areas ready for the clinician to review. It will also facilitate faster and more confident diagnosis and classification of a patient's state.

Children with hand and upper limb deformities are generally unable to adequately communicate making diagnosis difficult. Incorrect diagnosis and poor-quality assessments can result in ineffective surgery, leading to further corrective procedures. The benefits of our glove will include significant improvement in information on patient's functioning; savings in clinic and clinician's time; number of visits to specialists' units; limiting distress to patients; and ultimately improved quality of life and functioning.