Running Constraints Shape Multifractal Movement Complexity Beyond Physiological and Mechanical Load: A Pilot Study

Abstract

Movement variability reflects adaptive neuromuscular reorganisation, but linear metrics alone cannot capture its temporal structure. This pilot study examined how running variations shape physiological and mechanical load responses using linear and nonlinear metrics. Fifteen recreationally active adults (31.4 ± 9.4 years; five females) performed six 90-s exercise conditions: high-knee running (HKR), tethered running (TER), shoulder-width running (SWR), core-board skipping (CBS), and treadmill running at 0% (TR0%) and 6% grade (TR6%). Heart rate (HR), muscle oxygenation (SmO2), and player load (PL) were recorded, and PL multifractal structure was quantified via wavelet leader analysis, validated against iterative amplitude-adjusted Fourier transform (IAAFT) and shuffled surrogates. HKR elicited the highest HR mean, while TR6% produced the greatest PL mean. Multifractal parameters—h(0), hmin, Dh (hmin), and left-tail width L—differed significantly across conditions (all p < 0.001), though overall spectral width (Δh) did not. Surrogate validation confirmed genuine temporal multifractality in 85/86 series. Load-adjusted regime analysis showed temporal complexity partly dissociable from load: HKR retained the highest scaling complexity beyond load, CBS combined lowest load with highest ordinal irregularity, and treadmill conditions were temporally constrained. HKR elicited the greatest physiological and mechanical demands, whereas CBS combined the lowest physiological load with the highest movement irregularity, demonstrating distinct exercise-specific response profiles. Given the modest, heterogeneous sample, these findings are presented as pilot evidence for this multi-metric approach, warranting confirmation in larger, sex-balanced cohorts.

The authors' abstract, as published at the source. Sensors, 2026 · DOI ↗