Validity of linear and nonlinear measures of gait variability to characterize aging gait with a single low back accelerometer

Abstract Purpose This study investigates the validity of the attractor complexity index (ACI), a recently developed gait analysis tool based on nonlinear dynamics. The analysis assesses ACI's sensitivity to motor-cognitive interference and its potential for characterizing age-related changes in gait patterns. Furthermore, the study compares ACI with classical gait metrics to determine its efficacy relative to established methods. Methods A 4x200m indoor walking test with a triaxial accelerometer attached to the lower back was used to compare gait patterns of younger (N = 42) and older adults (N = 60) during normal and metronome walking. The other linear and non-linear gait metrics were movement intensity, gait regularity, local dynamic stability (maximal Lyapunov exponents), and scaling exponent (detrended fluctuation analysis). Results In contrast to other gait metrics, ACI demonstrated a specific sensitivity to metronome walking, with both young and old participants exhibiting altered stride interval correlations. Furthermore, there was a significant difference between the young and old groups (standardized effect size: -0.77). Additionally, older participants exhibited slower walking speeds, a reduced movement intensity, and a lower gait regularity. Inferential statistics using linear mixed-effects models confirmed the responsiveness of ACI to metronome walking and its efficacy in differentiating between the gait patterns of older and younger adults. Conclusion The ACI is likely a sensitive marker for cognitive load during walking and can effectively discriminate age-related changes in gait patterns. Its ease of measurement makes it a promising tool gait analysis in unsupervised (free-living) conditions. Future research will focus on the ACI’s clinical utility for fall risk assessment.