ReviewSensors (Basel, Switzerland)2022
Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mapping autism's research landscape: trends in autism screening and its alignment with sustainable development goals.Frontiers in psychiatry · 2023Pooled it
- An Explorative Retrospective Video Analysis of Movement Quality in Infants Later Diagnosed with Developmental Coordination Disorder.Journal of autism and developmental disorders · 2026Article
- Infants' spontaneous movements explore arm dynamics.Communications biology · 2026Article
- Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026Review
- Automatic pose estimation in newborn infants: Lessons from the Baby Grow study.Behavior research methods · 2026Article
- Infant limb kinematics and muscle force variation during kicking is associated with clinical cerebral palsy risk measures.PloS one · 2026Article
- Movement smoothness at term-equivalent age is associated with motor developmental delay in preterm infants.Scientific reports · 2025Article
- The Development of a Wearable-Based System for Detecting Shaken Baby Syndrome Using Machine Learning Models.Sensors (Basel, Switzerland) · 2025Article
- Comparison of marker-less 2D image-based methods for infant pose estimation.Scientific reports · 2025Article
- Deep learning empowered sensor fusion boosts infant movement classification.Communications medicine · 2025Article
- NeoVault: empowering neonatal research through a neonate data hub.BMC pediatrics · 2024Article
- Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.Scientific reports · 2024Article
- Review
- Automating General Movements Assessment with quantitative deep learning to facilitate early screening of cerebral palsy.Nature communications · 2023Article
- Automated anomalous child repetitive head movement identification through transformer networks.Physical and engineering sciences in medicine · 2023Article
- Mobile Device-Based Video Screening for Infant Head Lag: An Exploratory Study.Children (Basel, Switzerland) · 2023Article
- Video-Based Behaviorally Coded Movement Assessment for Adolescents with Intellectual Disabilities: Application in Leg Dribbling Performance.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurodevelopmental disorders (NDD) are impairments of the growth and development of the brain and/or central nervous system. In the light of clinical findings on early diagnosis of NDD and prompted by recent advances in hardware and software technologies, several researchers tried to introduce automatic systems to analyse the baby's movement, even in cribs. Traditional technologies for automatic baby motion analysis leverage contact sensors. Alternatively, remotely acquired video data (e.g., RGB or depth) can be used, with or without active/passive markers positioned on the body. Markerless approaches are easier to set up and maintain (without any human intervention) and they work well on non-collaborative users, making them the most suitable technologies for clinical applications involving children. On the other hand, they require complex computational strategies for extracting knowledge from data, and then, they strongly depend on advances in computer vision and machine learning, which are among the most expanding areas of research. As a consequence, also markerless video-based analysis of movements in children for NDD has been rapidly expanding but, to the best of our knowledge, there is not yet a survey paper providing a broad overview of how recent scientific developments impacted it. This paper tries to fill this gap and it lists specifically designed data acquisition tools and publicly available datasets as well. Besides, it gives a glimpse of the most promising techniques in computer vision, machine learning and pattern recognition which could be profitably exploited for children motion analysis in videos.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.