ArticleChildren (Basel, Switzerland)2022
Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study.
Article in Children (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Early cerebral palsy risk screening through wearable accelerometry in infants under nine weeks.Scientific reports · 2026Article
- Video and Wearable Sensor Technologies for Early Detection of Cerebral Palsy in Infants: A Scoping Review.Journal of clinical medicine · 2026Review
- Applying artificial intelligence in neurodevelopmental disorders management and research.European journal of medical research · 2026Review
- Evaluating Non-Invasive Computer Vision-Based Quantification of Neonatal Movement as a Marker of Development in Preterm Infants: A Pilot Study.Healthcare (Basel, Switzerland) · 2025Article
- A systematic review of portable technologies for the early assessment of motor development in infants.NPJ digital medicine · 2025Article
- Deep-learning-based markerless tracking of distal anatomical landmarks in clinically recorded videos for assessing infant movement patterns associated with neurodevelopmental status.Journal of the Royal Society of New Zealand · 2025Article
- Systematic Review and Meta-Analysis of Intervention Techniques in Occupational Therapy for Babies and Children with Obstetric Brachial Plexus Palsy.Journal of clinical medicine · 2024Review
- Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review.PeerJ. Computer science · 2024Review
- Spontaneous movements as prognostic tool of neurodevelopmental outcomes in preterm infants: a narrative review.Clinical and experimental pediatrics · 2023Article
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
Abstract
The General Movements Assessment requires extensive training. As an alternative, a novel automated movement analysis was developed and validated in preterm infants. Infants < 31 weeks’ gestational age or birthweight ≤ 1500 g evaluated at 3−5 months using the general movements assessment were included in this ambispective cohort study. The C-statistic, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for a predictive model. A total of 252 participants were included. The median gestational age and birthweight were 274/7 weeks (range 256/7−292/7 weeks) and 960 g (range 769−1215 g), respectively. There were 29 cases of cerebral palsy (11.5%) at 18−24 months, the majority of which (n = 22) were from the retrospective cohort. Mean velocity in the vertical direction, median, standard deviation, and minimum quantity of motion constituted the multivariable model used to predict cerebral palsy. Sensitivity, specificity, positive, and negative predictive values were 55%, 80%, 26%, and 93%, respectively. C-statistic indicated good fit (C = 0.74). A cluster of four variables describing quantity of motion and variability of motion was able to predict cerebral palsy with high specificity and negative predictive value. This technology may be useful for screening purposes in very preterm infants; although, the technology likely requires further validation in preterm and high-risk term populations.
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Registered trials
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