A multi-level analysis of motor and behavioural dynamics in 9-month-old preterm and term-born infants during changing
Yu Wei Chua1,2,3,4, Lorena Jiménez-Sánchez5, Victoria Ledsham6
1Strathclyde Institute of Education, University of Strathclyde, Lord Hope Building, Glasgow, G4 0LT, UK. yu.wei.chua@liverpool.ac.uk.
Insights
Preterm infants exhibit distinct movement patterns, with greater complexity in ankle and torso motion compared to full-term infants. This study uses advanced computational methods to analyze infant motor development and emotional self-regulation.
Area of Science:
- Developmental neuroscience
- Computational biology
- Infant motor development
Background:
- Infant movement analysis offers insights into developmental health.
- Preterm birth can impact motor development.
- Emotional and social contexts influence infant behavior.
Purpose of the Study:
- To investigate the effects of preterm birth on infant movement kinematics.
- To examine how emotional and social contexts alter infant motor behavior.
- To apply dynamic analyses to characterize infant movement and self-regulation.
Main Methods:
- Multiscale permutation entropy analysis of kinematic data from IMU sensors (torso, wrists, ankles).
- Recurrence Quantification Analysis of observational behavioral data on emotional self-regulation.
- Study included 9-month-old infants (N=32 for kinematics, N=111 for behavior), comparing term and preterm groups.
Main Results:
- Preterm infants showed significantly greater permutation entropy in left ankle and torso movements compared to term infants.
- No significant effects of preterm birth or emotional context on micro-level behavioral dynamics were found.
- Frequency-specific effects of context on permutation entropy were observed.
Conclusions:
- Dynamic analysis, particularly multiscale entropy, is a promising tool for studying infant motor development.
- Movement complexity differs between preterm and term infants, especially in specific body parts.
- Further methodological development is needed for applying dynamic analysis to infant emotional self-regulation.
Abstract:
Computational analysis of infant movement has significant potential to reveal markers of developmental health. We report two studies employing dynamic analyses of motor kinematics and motor behaviours, which characterise movement at two levels, in 9-month-old infants. We investigate the effect of preterm birth (< 33 weeks of gestation) and the effect of changing emotional and social-interactive contexts in the still-face paradigm. First, multiscale permutation entropy was employed to analyse acceleration kinematic timeseries data collected from Inertial Measurement Unit (IMU) sensors on infants' torso, wrists, and ankles (N = 32: 10 term; 22 preterm). Second, Recurrence Quantification Analysis was used to characterise patterns of second-to-second behavioural changes, from observationally coded behavioural timeseries on infants' emotional self-regulation (N = 111: 61 term; 50 preterm). We found frequency-specific effects of context on permutation entropy. Relative to infants born at term (> 37 weeks of gestation), infants born preterm showed greater permutation entropy in their left ankle and torso movements, but not in right ankle or wrist movements. We did not find effects of preterm birth or emotional context on micro-level behavioural dynamics. Our methodology and findings inform future work using multiscale entropy to study infant development. Dynamic analysis of behaviour is a relatively young field, and applications to emotional self-regulation requires further methodological development.
Related Concept Videos
01:30Socioemotional Development during Infancy
Primary Temperament Types
01:14Piaget's Stage 1 of Cognitive Development
01:20Attachment