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A dynamical system analysis of the development of spontaneous lower extremity movements in newborn and young infants
Hirotaka Gima1, Shohei Ohgi, Satoru Morita
1School of Physical Therapy, Koriyama Institute of Health Sciences, Fukushima, Japan. h-gima@k-tohto.ac.jp
Insights
Newborn infants
Area of Science:
- Pediatric Neurology
- Developmental Neuroscience
- Biophysics
Background:
- Infant motor development is crucial for assessing neurological health.
- Understanding the underlying dynamics of spontaneous movements provides insights into early motor control.
- Previous research has explored infant movements, but detailed dynamical analysis is less common.
Purpose of the Study:
- To characterize the dynamical properties of spontaneous lower extremity movements in newborns and young infants.
- To investigate developmental changes in these movement characteristics over the first six months of life.
- To apply nonlinear time series analysis to understand the complexity of infant motor control.
Main Methods:
- Utilized a tri-axial accelerometer to record limb movement acceleration in 3D space.
- Collected data from 8 healthy, full-term newborn infants in an active alert state.
- Analyzed movement data using both linear and nonlinear dynamical systems approaches, including optimal embedding dimension and maximal Lyapunov exponent calculations.
Main Results:
- Spontaneous infant lower extremity movements exhibit nonlinear chaotic dynamics with 5 to 7 embedding dimensions.
- Optimal embedding dimension showed a U-shaped developmental trend over the first six months.
- Maximal Lyapunov exponents were consistently positive, indicating chaotic behavior, with mutual information peaking at 0 months.
Conclusions:
- Newborn and young infants' spontaneous lower extremity movements are governed by complex, chaotic dynamic systems.
- These findings suggest that the infant motor system is inherently capable of generating sophisticated, voluntary movements from early life.
- The observed developmental changes in dynamical properties reflect the maturation of the infant's sensorimotor control system.
Abstract:
This study's aim was to evaluate the characteristics of newborn and young infants' spontaneous lower extremity movements by using dynamical systems analysis. Participants were 8 healthy full-term newborn infants (3 boys, 5 girls, mean birth weight and gestational age were 3070.6 g and 39 weeks). A tri-axial accelerometer measured limb movement acceleration in 3-dimensional space. Movement acceleration signals were recorded during 200 s from just below the ankle when the infant was in an active alert state and lying supine (sampling rate 200 Hz). Data were analyzed linearly and nonlinearly. As a result, the optimal embedding dimension showed more than 5 at all times. Time dependent changes started at 6 or 7, and over the next four months decreased to 5 and from 6 months old, increased. The maximal Lyapnov exponent was positive for all segments. The mutual information is at its greatest range at 0 months. Between 3 and 4 months the range in results is narrowest and lowest in value. The mean coefficient of correlation for the x-axis component was negative and y-axis component changed to a positive value between 1 month old and 4 months old. Nonlinear time series analysis suggested that newborn and young infants' spontaneous lower extremity movements are characterized by a nonlinear chaotic dynamics with 5 to 7 embedding dimensions. Developmental changes of an optimal embedding dimension showed a U-shaped phenomenon. In addition, the maximal Lyapnov exponents were positive for all segments (0.79-2.99). Infants' spontaneous movement involves chaotic dynamic systems that are capable of generating voluntary skill movements.
