Time series analysis of spontaneous upper-extremity movements of premature infants with brain injuries
Shohei Ohgi1, Satoru Morita, Kek Khee Loo
1School of Rehabilitation Sciences, Seirei Christopher University, 3453 Mikatahara, Kita-ku, Hamamatsu, Shizuoka 433-8558, Japan. shohei-o@seirei.ac.jp
Insights
Premature infants with brain injuries exhibit more disorganized, unstable, and unpredictable upper-extremity movements compared to healthy infants. This suggests challenges in motor self-organization, highlighting the need for tailored physical therapy interventions.
Area of Science:
- Developmental neuroscience
- Motor control
- Infant neurodevelopment
Background:
- Spontaneous movements offer insights into motor development in premature infants.
- Brain injuries can impact motor ontogeny.
- Understanding movement characteristics aids in identifying developmental abnormalities.
Purpose of the Study:
- To analyze and compare spontaneous upper-extremity movements in premature infants with and without brain injuries.
- To investigate the dynamic and nonlinear characteristics of infant motor behavior.
Main Methods:
- Utilized triaxial accelerometers to record upper-extremity limb acceleration in 3D space.
- Recorded data from 7 premature infants with brain injuries and 7 matched controls.
- Applied nonlinear and linear time series analysis to acceleration data.
Main Results:
- Spontaneous movements in premature infants display nonlinear, chaotic dynamics.
- Infants with brain injuries showed movements with greater dimensionality, increased instability, and unpredictability.
- Nonlinear analysis revealed increased disorganization in movements of infants with brain injuries.
Conclusions:
- Premature infants with brain injuries exhibit disorganized motor patterns, indicating potential self-organization deficits.
- These findings suggest impaired coordination among motor subsystems.
- Physical therapists can foster motor learning by supporting subsystem interactions and providing individualized sensorimotor experiences.
Background And Purpose:
Comparisons of spontaneous movements of premature infants with brain injuries and those without brain injuries can provide insights into normal and abnormal processes in the ontogeny of motor development. In this study, the characteristics of spontaneous upper-extremity movements of premature infants with brain injuries and those without brain injuries were examined with time series analysis.
Subjects:
Participants were 7 premature infants with brain injuries and 7 matched, low-risk, premature infants at the age of 1 month after term.
Methods:
A triaxial accelerometer was used to measure upper-extremity limb acceleration in 3-dimensional space. Acceleration signals were recorded from the right wrist when the infant was in an active, alert state and lying in the supine position. The recording time was 200 seconds. The acceleration signal was sampled at a rate of 200 Hz. The acceleration time series data were analyzed by nonlinear analysis as well as linear analysis.
Results:
The nonlinear time series analysis indicated that spontaneous movements of premature infants have nonlinear, chaotic, dynamic characteristics. The movements of the infants with brain injuries were characterized by larger dimensionality, and they were more unstable and unpredictable than those of infants without brain injuries.
Discussion And Conclusion:
As determined by nonlinear analysis, the spontaneous movements of the premature infants with brain injuries had the characteristics of increased disorganization compared with those of the infants without brain injuries. Infants with brain injuries may manifest problems with self-organization as a function of the coordination of subsystems. Physical therapists should be able to support interactions among the subsystems and promote self-organization of motor learning through the individualized provision of various sensorimotor experiences for infants.
More Related Videos
11:31Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
Published on: December 5, 2014
06:37Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
Published on: July 14, 2023