# Quantification of changes in balance control with tasks and injury using detrending methods for time series analysis

## TL;DR

This study uses time series analysis to understand how balance control changes with tasks and injury, revealing distinct patterns in postural responses.

## Contribution

The study introduces detrending methods to detect subtle changes in balance control due to injury or task difficulty.

## Key findings

- Balance recordings showed long-range autocorrelated behavior with a crossover point between random and structured dynamics.
- Injury and task difficulty altered scaling behavior above the crossover point, revealing two distinct postural responses.
- DFA and WTS proved effective in identifying subtle impairments in postural control.

## Abstract

Human balance control is regulated by complex temporal processes that may be disrupted by injury or increased task difficulty.

We examined long-range temporal characteristics of force platform recordings during quiet standing in 76 physically active participants with or without lower-limb injury, and in 13 non-injured participants standing with eyes closed or on one leg. Detrended fluctuation analysis (DFA) and wavelet transform spectral analysis (WTS) were used to quantify the temporal dynamics of postural control.

All recordings showed long-range autocorrelated behavior, with a visible crossover point separating random fluctuations at small time scales from structured dynamics at higher time scales (100 ms to 1 s). Changes in scaling behavior occurred only above the crossover point in response to altered stance or injury. Specifically, standing on one leg increased DFA and WTS slopes, likely due to enhanced amplitudes of characteristic peaks at approximately 250 ms and 650 ms. Two distinct postural responses to injury emerged: (1) compensation - characterized by increased amplitudes of all high-scale WTS modes and a crossover shift to smaller scales; and (2) underachievement - marked by decreased amplitudes and a shift of the crossover to larger time scales.

These findings support the potential of DFA, WTS, and similar time series techniques as sensitive tools for assessing subtle impairments in postural control.