One of the most accurate ways to spot cerebral palsy early is simply to watch how a baby moves. The General Movements Assessment (GMA), a short observation of an infant’s spontaneous wriggling at around three to four months, can flag a high probability of cerebral palsy with remarkable accuracy. Its catch: it requires a specially trained, certified expert, and there aren’t enough of them.
Researchers think artificial intelligence could change that, by reading a baby’s movements from an ordinary smartphone video.
“AI has the potential to increase accessibility to early screening; health professionals will always need to be involved in the pathway to diagnosis.”
— Roadmap for automated GMA, eClinicalMedicine, 2025
Why automate the movement test
The absence of normal “fidgety” movements at three to four months has a sensitivity of about 95–98% for predicting cerebral palsy, making the GMA the most accurate early prediction tool available. But, as a 2025 roadmap in eClinicalMedicine notes, its use is “limited by the need for training and certification of assessors.” That bottleneck means many infants (especially in under-resourced areas) are never screened.
How AI could help
The approach is straightforward: a parent records a short video on a phone or tablet; software estimates the baby’s body movements (a step called “pose estimation”); and a machine-learning model flags movement patterns linked to cerebral palsy. An international consortium has published a roadmap to standardize the data, validate the models, and bring this to families worldwide, including in low- and middle-income countries. The authors are clear that AI is meant to widen access to screening, not replace clinicians: a concerning result still leads to a full assessment by a health professional. This pairs naturally with starting support early; see our guide to cerebral palsy diagnosis.
This article is for general education and is not medical advice. AI-based screening tools are still being developed and validated; talk with your child’s doctor about any concerns regarding development.
Sources
“Towards universal early screening for cerebral palsy: a roadmap for automated General Movements Assessment.” eClinicalMedicine, 2025. ncbi.nlm.nih.gov
“Automating General Movements Assessment with quantitative deep learning to facilitate early screening of cerebral palsy.” Nature Communications, 2023. nature.com
Kelsey is an experienced surgical nurse with more than 10 years in hospital-based care, including leadership within the operating room. She has worked extensively with pediatric patients, refining her ability to support children and families during critical moments.
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Cerebral Palsy Center
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