Evidence of an upper entrainment limit for walking with fractal auditory stimuli
Bibliographic record
Abstract
Background: Variability exists in all biological signals, and in human gait research it has been found to be an indicator of neuromuscular system functioning. Detrended fluctuation analysis (DFA), a nonlinear method used to quantify the strength of long-range correlations in the temporal structure of stride-to-stride gait variability, has revealed gait differences in certain populations that are not observed with traditional linear measures like standard deviation. Previous research suggests that humans can adapt gait patterns to match different variability structures through sensory cues, such as auditory metronomes. However, the upper limits of adaptability and the strength of long-term correlations in gait variability remain unclear. Exploring these limits not only deepens our understanding of neuromuscular control mechanisms but could also inform the design of targeted interventions, such as rehabilitation strategies, to enhance motor control in clinical populations. The aim of this study was to investigate the possible upper limits of long-term correlations in stride-to-stride gait variability, characterized by the fractal scaling index (FSI) using DFA. Methods: Fourteen healthy young adults (age 25 ± 3 years; seven females) completed seven treadmill walking trials at a fixed, self-selected speed. The first trial was uncued, and during the remaining six trials participants timed their steps to an auditory metronome with FSI ranging between 1.00 and 1.25. Gait FSI, velocity, stride time, cadence, and the time difference between heel contact and the associated metronome "tones" were calculated. Results: Uncued gait FSI averaged 0.76 (±0.1). As the metronome FSI increased from 1.00 to 1.15, gait FSI approximated 1.00. Beyond 1.15 (metronome FSI values of 1.20 and 1.25), gait FSI dropped below 0.70, resembling uncued walking. Other gait measures remained unchanged. These findings suggest an upper gait FSI limit of approximately 1.00 during entrainment to metronome FSI values <1.20, beyond which adaptability diminishes. Conclusions: This study establishes the upper entrainment limit for gait FSI during synchronization with fractal auditory stimuli, with implications for designing effective gait rehabilitation interventions targeting specific variability patterns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".