ArticleResearch in developmental disabilities2021
The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review.
Article in Research in developmental disabilities, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.
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Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence support for diagnosis of neurodevelopmental disorders during childhood: an umbrella review.Frontiers in psychiatry · 2026Pooled it
- Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk.JAMA network open · 2022Trial
- Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants.Scientific reports · 2022Trial
- Movement-Related Differences Between Infants with High and Low Likelihood of Autism: A Longitudinal Study Using Markerless Motion Tracking.Sensors (Basel, Switzerland) · 2026Article
- Nonlinear Measures Applied to Spontaneous Infant Movement Analysis: A Scoping Review.Sensors (Basel, Switzerland) · 2026Article
- Automated contactless radar-derived movement index for outpatient motor surveillance.Pediatric research · 2026Article
- Early cerebral palsy risk screening through wearable accelerometry in infants under nine weeks.Scientific reports · 2026Article
- A preregistered, open pipeline for early cerebral palsy risk assessment from infant videos.GigaScience · 2026Article
- Infant limb kinematics and muscle force variation during kicking is associated with clinical cerebral palsy risk measures.PloS one · 2026Article
- Implementation of an innovative virtual selective screening program for early detection of cerebral palsy in British Columbia.Frontiers in public health · 2026Article
- An Automated Framework for Pose-Sequence Analysis of Spontaneous Movements in Preterm Infants.IEEE open journal of engineering in medicine and biology · 2026Article
- Movement smoothness at term-equivalent age is associated with motor developmental delay in preterm infants.Scientific reports · 2025Article
- Towards universal early screening for cerebral palsy: a roadmap for automated General Movements Assessment.EClinicalMedicine · 2025Review
- Autonomous screening of infants at high risk for neurodevelopmental impairments using a radar sensor and machine learning.Scientific reports · 2025Article
- 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
- Validity of tremor analysis using smartphone compatible computer vision frameworks.Scientific reports · 2025Article
- Doing Everything We Can to Help Our High-Risk Newborns: A Qualitative, Lifeworld-Led Study of What Early Risk Assessment for Cerebral Palsy Means to Parents.Journal of clinical medicine · 2025Article
- Comparison of marker-less 2D image-based methods for infant pose estimation.Scientific reports · 2025Article
- Deep learning-based classification of hemiplegia and diplegia in cerebral palsy using postural control analysis.Scientific reports · 2025Article
- Data-Driven Early Prediction of Cerebral Palsy Using AutoML and interpretable kinematic features.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundThe clinical and scientific value of Prechtl general movement assessment (GMA) has been increasingly recognised, which has extended beyond the detection of cerebral palsy throughout the years. With advancing computer science, a surging interest in developing automated GMA emerges.
aimsIn this scoping review, we focused on video-based approaches, since it remains authentic to the non-intrusive principle of the classic GMA. Specifically, we aimed to provide an overview of recent video-based approaches targeting GMs; identify their techniques for movement detection and classification; examine if the technological solutions conform to the fundamental concepts of GMA; and discuss the challenges of developing automated GMA. METHODS AND PROCEDURES: We performed a systematic search for computer vision-based studies on GMs. OUTCOMES AND
resultsWe identified 40 peer-reviewed articles, most (n = 30) were published between 2017 and 2020. A wide variety of sensing, tracking, detection, and classification tools for computer vision-based GMA were found. Only a small portion of these studies applied deep learning approaches. A comprehensive comparison between data acquisition and sensing setups across the reviewed studies, highlighting limitations and advantages of each modality in performing automated GMA is provided. CONCLUSIONS AND IMPLICATIONS: A "method-of-choice" for automated GMA does not exist. Besides creating large datasets, understanding the fundamental concepts and prerequisites of GMA is necessary for developing automated solutions. Future research shall look beyond the narrow field of detecting cerebral palsy and open up to the full potential of applying GMA to enable an even broader application.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.