ArticleScientific reports2020
Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 56 papers, 3 of them syntheses that pooled it.
What it found
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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.
Development of Motility and Cognition in Infants
Assessment of Motor Development With a Wearable in Rural and Low-income Settings: Feasibility and Validity of MAIJU Jumpsuit in Malawi
Who cites it
56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 8 citations in OpenAlex.
- Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.Annals of medicine · 2026Pooled it
- Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old).The international journal of behavioral nutrition and physical activity · 2022Pooled it
- Quantifying infants' everyday restrained experiences in the home using wearable inertial sensors.Behavior research methods · 2026Article
- Infants' Sleep Supports the Emergence and Mastery of Locomotor and Linguistic Skills.Developmental psychobiology · 2026Article
- Body position classification using wearable sensors in infants with cerebral palsy.Infant behavior & development · 2026Article
- Characterizing infant leg movements using 72-h wearable sensor data: Descriptive analysis from a large, heterogenous sample of infants 0-2 months of age from the HEALthy Brain and Child Development Study.Infant behavior & development · 2026Article
- A Novel Workflow to Estimate Limb Orientation from Wearable Sensors to Monitor Infant Motor Development.Sensors (Basel, Switzerland) · 2026Article
- Video and Wearable Sensor Technologies for Early Detection of Cerebral Palsy in Infants: A Scoping Review.Journal of clinical medicine · 2026Review
- Infant limb kinematics and muscle force variation during kicking is associated with clinical cerebral palsy risk measures.PloS one · 2026Article
- Machine Learning Methods in Posture-Related Applications in Children up to 12 Years Old: A Systematic Review.Bioengineering (Basel, Switzerland) · 2025Review
- Advancing Wrist-Worn Accelerometry for Measurement of Infant Motor Behavior.Developmental psychobiology · 2025Article
- A Scoping Review of AI-Based Approaches for Detecting Autism Traits Using Voice and Behavioral Data.Bioengineering (Basel, Switzerland) · 2025Review
- Tummy Time Tracking: Concurrent-Validity of Wearable Sensors in Home Settings for Term and Preterm Infants.Pediatric physical therapy : the official publication of the Section on Pediatrics of the American Physical Therapy Association · 2025Article
- Automatic infant 2D pose estimation from videos: Comparing seven deep neural network methods.Behavior research methods · 2025Article
- Early gross motor performance is associated with concurrent prelinguistic and social development.Pediatric research · 2025Article
- A Two-Dimensional Position and Motion Monitoring System for Preterm Infants Using a Fiber-Optic Pressure-Sensitive Mattress.Sensors (Basel, Switzerland) · 2025Article
- Trade-Offs Between Simplifying Inertial Measurement Unit-Based Movement Recordings and the Attainability of Different Levels of Analyses: Systematic Assessment of Method Variations.JMIR mHealth and uHealth · 2025Article
- Can AI-Based Video Analysis Help Evaluate the Performance of the Items in the Bayley Scales of Infant Development?Children (Basel, Switzerland) · 2025Article
- Physical Activity in Pre-Ambulatory Children with Cerebral Palsy: An Exploratory Validation Study to Distinguish Active vs. Sedentary Time Using Wearable Sensors.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.
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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.