ArticleTechnologies2017
Sample Entropy Identifies Differences in Spontaneous Leg Movement Behavior between Infants with Typical Development and Infants at Risk of Developmental Delay.
Article in Technologies, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants.Scientific reports · 2022Trial
- 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
- Nonlinear Measures Applied to Spontaneous Infant Movement Analysis: A Scoping Review.Sensors (Basel, Switzerland) · 2026Article
- Spontaneous Leg Movements Measured by Wearable Sensors in Infancy Differentiate Later Risk for Cerebral Palsy.Pediatric neurology · 2026Article
- A Novel Workflow to Estimate Limb Orientation from Wearable Sensors to Monitor Infant Motor Development.Sensors (Basel, Switzerland) · 2026Article
- Movement smoothness at term-equivalent age is associated with motor developmental delay in preterm infants.Scientific reports · 2025Article
- Marker-Less Video Analysis of Infant Movements for Early Identification of Neurodevelopmental Disorders.Diagnostics (Basel, Switzerland) · 2025Article
- A multi-level analysis of motor and behavioural dynamics in 9-month-old preterm and term-born infants during changing emotional and interactive contexts.Scientific reports · 2025Article
- A multi-level analysis of motor and behavioural dynamics in 9-month-old preterm and term-born infants during changing emotional and interactive contexts.Scientific reports · 2025Article
- Quantifying Arm and Leg Movements in 3-Month-Old Infants Using Pose Estimation: Proof of Concept.Sensors (Basel, Switzerland) · 2024Article
- Remote data collection of infant activity and sleep patterns via wearable sensors in the HEALthy Brain and Child Development Study (HBCD).Developmental cognitive neuroscience · 2024Article
- Associating neuromotor outcomes at 12 months with wearable sensor measures collected during early infancy in rural Guatemala.Gait & posture · 2024Article
- An Algorithmic Approach for Detecting Neuromotor Developmental Disabilities in Infants from Wearable Sensor Data.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024Article
- Reduction in limb-movement complexity at term-equivalent age is associated with motor developmental delay in very-preterm or very-low-birth-weight infants.Scientific reports · 2024Article
- Early full-day leg movement kinematics and swaddling patterns in infants in rural Guatemala: A pilot study.PloS one · 2024Observational
- Barcoding, linear and nonlinear analysis of full-day leg movements in infants with typical development and infants at risk of developmental disabilities: Cross-sectional study.Infancy : the official journal of the International Society on Infant Studies · 2023Article
- Distinct clusters of movement entropy in children's exploration of a virtual reality balance beam.Frontiers in psychology · 2023Article
- Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder.Sensors (Basel, Switzerland) · 2021Article
- A Contactless Method for Measuring Full-Day, Naturalistic Motor Behavior Using Wearable Inertial Sensors.Frontiers in psychology · 2021Article
- How Many Days are Necessary to Represent Typical Daily Leg Movement Behavior for Infants at Risk of Developmental Disabilities?Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We are interested in using wearable sensor data to analyze detailed characteristics of movement, such as repeatability and variability of movement patterns, over days and months to accurately capture real-world infant behavior. The purpose of this study was to explore Sample Entropy (SampEn) from wearable sensor data as a measure of variability of spontaneous infant leg movement and as a potential marker of the development of neuromotor control. We hypothesized that infants at risk (AR) of developmental delay would present significantly lower SampEn values than infants with typical development (TD). Participants were 11 infants with TD and 20 infants AR. We calculated SampEn from 1-4 periods of data of 7200 samples in length when the infants were actively playing across the day. The infants AR demonstrated smaller SampEn values (median 0.21) than the infants with TD (median 1.20). Lower values of SampEn indicate more similarity in patterns across time, and may indicate more repetitive, less exploratory behavior in infants AR compared to infants with TD. In future studies, we would like to expand to analyze longer periods of wearable sensor data and/or determine how to optimally sample representative periods across days and months.
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