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Experimental Methods to Study Human Postural Control
Published on: September 11, 2019
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Age and Visual Contribution Effects on Postural Control Assessed by Principal Component Analysis of Kinematic Marker
1Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand.
Sports (Basel, Switzerland)
|May 26, 2023
Summary
Older adults exhibit greater neuromuscular control needs for postural sway, especially with eyes closed. Age and visual input significantly impact how the body maintains balance.
Area of Science:
- Biomechanics
- Human Movement Science
- Gerontology
Background:
- Postural control is vital for health and daily function.
- Aging and visual input are known factors influencing balance.
- Understanding age-related changes in postural control is crucial.
Purpose of the Study:
- To investigate the effects of age and visual input on postural control.
- To analyze age-related differences in movement synergies during balancing tasks.
Main Methods:
- Principal Component Analysis (PCA) was used to identify principal movements (PMs) from kinematic data.
- Data were collected from young and older adults balancing on stable and unstable surfaces with eyes open and closed.
- PCA-derived variables (PP_rVAR, PA_rVAR, PA_RMS) quantified movement composition and neuromuscular control magnitude.
Main Results:
- Older adults showed significantly greater PA1_rVAR and PA1_RMS compared to young adults.
- Eyes-closed conditions resulted in significantly higher PA1_rVAR and PA1_RMS than eyes-open.
- These effects were most prominent in PM1, related to anteroposterior ankle sway.
Conclusions:
- Older adults require greater neuromuscular control for postural stability, particularly when visual input is reduced.
- Reduced visual reliance exacerbates the need for enhanced neuromuscular control in older adults.
- Age and visual contribution are key determinants of postural control strategies.
Keywords:
agingbalanceclosed eyemovement synergyneuromuscular controlpostural controlprincipal component analysis (PCA)unstable surface
