Early prediction of cerebral palsy in young children by the use of general movement assessment using a smart phone application in Denmark

Cerebral palsy (CP) is the most common physical disability in childhood. About 2-2.5/1000 children have CP with affected muscle tone, movement, and motor skills, often accompanied by pain, epilepsy, and intellectual, communication, and
behavioral disorder. Early detection of CP is difficult but important to minimize the consequences of neuro-developmental disorder by being able to introduce early and correct treatment. General Movement Assessment (GMA), an observational method for classifying spontaneous movements in infants, is currently the most accurate method for the early identification of CP.

The project examines how a mobile application can be used as an aid to identify or rule out cerebral palsy in children. Normally, children who have an increased risk of cerebral palsy are referred to a physiotherapist for assessment of their level of motor development and quality of movement. The project is testing letting the parents use a mobile application to be able to make video recordings at home at a time that suits the family and the child and with the push of a button the video is sent for assessment.

By observing the children's spontaneous behavior and motor skills, doctors and physiotherapists can then identify or rule out cerebral palsy in the children. The project is also testing letting AI participate in the analysis of the filmed material.

The study involves 130 parents at four neonatal clinics in Copenhagen and includes both the children's and the parent's perspectives.

The project is part of the FORTE-funded research program eChildhealth.