Topological data analysis of postural sway: characterizing balance control during childhood development

Area of Science:

• Biomechanics and Motor Control
• Developmental Neuroscience
• Data Science and Topology

Background:

• Postural control development involves refining sway organization, but traditional center of pressure (CoP) measures lack geometric insight.
• Topological Data Analysis (TDA) quantifies sway dynamics' persistence and complexity, offering a novel approach.
• This study investigates developmental and task-related changes in CoP topology using TDA.

Purpose of the Study:

• To apply TDA to analyze the topology of center of pressure (CoP) dynamics during postural control.
• To investigate developmental differences in CoP topology from childhood to adulthood.
• To examine how visual input, base of support, and cognitive load influence CoP topology.

Main Methods:

• 460 healthy participants (ages 7-12 and adults) performed eight standing balance tasks.
• Vietoris-Rips persistence diagrams computed for 30-s CoP trials.
• Four H1-based TDA metrics (Wasserstein distance, Total Persistence, Persistent Entropy, NumLongLoops) extracted and analyzed using ANOVAs.

Main Results:

• All TDA metrics showed significant age effects (p < 0.001), with children exhibiting more persistent and complex sway.
• Vision and single-leg stance significantly modulated TDA metrics; eye closure increased persistence.
• Cognitive dual-tasking moderately altered metrics, while Persistent Entropy was insensitive to visual deprivation.

Conclusions:

• TDA effectively captures developmental shifts in CoP topology from complex childhood sway to simpler adult patterns.
• TDA is a sensitive method for assessing balance maturation and identifying atypical postural control.
• Findings highlight TDA's potential in clinical and developmental contexts for evaluating balance.