ArticleFrontiers in psychology2021
A Contactless Method for Measuring Full-Day, Naturalistic Motor Behavior Using Wearable Inertial Sensors.
Article in Frontiers in psychology, 2021. 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.
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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.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Quantifying infants' everyday restrained experiences in the home using wearable inertial sensors.Behavior research methods · 2026Article
- Body position classification using wearable sensors in infants with cerebral palsy.Infant behavior & development · 2026Article
- Thinking Critically About Algorithms for Automated Detection of Behavior: 11 Guidelines for Social and Behavioral Scientists.Developmental science · 2026Article
- Machine Learning Methods in Posture-Related Applications in Children up to 12 Years Old: A Systematic Review.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
- 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
- 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
- Identifying Infant Body Position from Inertial Sensors with Machine Learning: Which Parameters Matter?Sensors (Basel, Switzerland) · 2024Article
- Automatic assessment of infant carrying and holding using at-home wearable recordings.Scientific reports · 2024Article
- Preliminary Technical Validation of LittleBeats™: A Multimodal Sensing Platform to Capture Cardiac Physiology, Motion, and Vocalizations.Sensors (Basel, Switzerland) · 2024Article
- Sitting Capacity and Performance in Infants with Typical Development and Infants with Motor Delay.Physical & occupational therapy in pediatrics · 2024Article
- Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors.Sensors (Basel, Switzerland) · 2023Article
- Quantifying States and Transitions of Emerging Postural Control for Children Not Yet Able to Sit Independently.Sensors (Basel, Switzerland) · 2023Article
- Motor Overflow during Reaching in Infancy: Quantification of Limb Movement Using Inertial Motion Units.Sensors (Basel, Switzerland) · 2023Article
- Changes in the Complexity of Limb Movements during the First Year of Life across Different Tasks.Entropy (Basel, Switzerland) · 2022Article
- Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants.Communications medicine · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
How can researchers best measure infants' motor experiences in the home? Body position-whether infants are held, supine, prone, sitting, or upright-is an important developmental experience. However, the standard way of measuring infant body position, video recording by an experimenter in the home, can only capture short instances, may bias measurements, and conflicts with physical distancing guidelines resulting from the COVID-19 pandemic. Here, we introduce and validate an alternative method that uses machine learning algorithms to classify infants' body position from a set of wearable inertial sensors. A laboratory study of 15 infants demonstrated that the method was sufficiently accurate to measure individual differences in the time that infants spent in each body position. Two case studies showed the feasibility of applying this method to testing infants in the home using a contactless equipment drop-off procedure.
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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.