Age- and cognitive load–related variability and entropy of gait: integrating coefficient of variation, median absolute deviation, and permutation entropy of spatiotemporal parameters into the Semmelweis Study gait assessment framework
摘要
Aging profoundly alters the neuromotor and cognitive systems that support gait control, leading to increased variability and instability that predict functional decline and dementia risk. In this pilot study, conducted to inform the design of the Semmelweis Study gait assessment pipeline, we examined how aging and cognitive load influence the magnitude and temporal organization of gait fluctuations. The Semmelweis Study is a large, prospective workplace cohort at Semmelweis University designed to identify the determinants of unhealthy aging and the mechanisms that preserve functional resilience across the life course. One hundred three adults aged 23–87 years completed single- and dual-task walking trials on a 20-foot pressure-sensitive walkway. Gait variability was quantified using the median absolute deviation (MAD) and coefficient of variation (CoV) of key spatiotemporal parameters, while permutation entropy (PE) captured the complexity of stride-to-stride dynamics. Aging was associated with progressive increases in both the variability (MAD, CoV) and changes in orderliness (PE) of gait fluctuations, particularly under dual-task conditions, suggesting a dual contribution of neuromotor degradation and compensatory recruitment of higher-order control processes. The amplification of these effects during cognitive load highlights the vulnerability of cognitive–motor integration with advancing age. By integrating robust, relative, and nonlinear variability metrics within a unified analytical framework, this study provides a multidimensional characterization of gait control and establishes sensitive indicators for detecting early functional decline. Within the translational framework of the Semmelweis Study, these quantitative gait measures—together with vascular, metabolic, and cognitive assessments—are expected to serve as informative components of a comprehensive biomarker system aimed at identifying early determinants of unhealthy brain aging and guiding preventive strategies to promote healthy longevity.