Cerebral Palsy (CP) is the most common motor dysfunction in childhood. Traditionally, diagnosis is set between 12 and 24 months of age. This study will evaluate feasibility of a new screening procedure for early detection of CP in high-risk infants and investigate how such a procedure can be implemented in the Central Norwegian Regional Health Authority (CNRHA).

The most accurate method to detect and predict CP at an early age is the General Movement Assessment (GMA). GMA is based upon expert observations of infant spontaneous movements in a video. In Central-Norway such expertise is today only present at St. Olavs Hospital, Trondheim University Hospital. Video recordings by health personnel and parents will be used in follow-up programs within CNRHA for remote expert based GMA. In addition, machine learning models will be applied for automatic detection of CP.

Early identification of CP will lead to improved function and increased possibility to direct health care resources to the patients who need it most, independent of geographical and expert based constraints.

Inclusion Criteria:

• hospitalized at a Neonatal Intensive Care Unit (NICU) within the Central Norway Regional Health Authority that is referred to follow-up in the Specialist Health Services containing a team of minimum a pediatrician and a physiotherapist.
• at high-risk for adverse neurological outcomes as considered by the pediatrician on the basis of clinical judgement (example: serious asphyxia, prematurity, stroke, brain hemorrhage)

Exclusion Criteria:

• Peripheral neuromotor disease e.g. brachial plexus injury
• iatrogenic restricted movements (e.g. cast for clubfoot)

High-risk infants referred to high-risk follow-up at discharge from one of the participating Neonatal Intensive Care Units, are candidates for enrollment. Following review of the inclusion and exclusion criteria, eligible subjects will be invited to participate. All subjects (parents) must give written informed consent prior to any study procedures being carried out.