Understanding the role of lower limb kinetic adaptations in dynamic stability during novel forward walking
Bibliographic record
Abstract
Introduction During asymmetrical gait perturbations, adaptive alterations in spatiotemporal (i.e., step width & length) and kinematic parameters (i.e., margins of stability (MoS)) have become an important means to probe the mechanisms of stability control. Recent work has linked eccentric ground reaction force (GRFnet) control to ML instability during normal and fast paced walking, potentially yielding insight into proactive and reactive mechanisms of stability control. Using a split-belt treadmill, where gait perturbations can be administered by decoupling individual belts, this study sought to examine adaptations in the kinetic mechanisms underlying stability in gait, which have yet to be examined. The timing and magnitude of the angle of GRFnet eccentricity (θd) were examined during the double support phase to better understand how younger adult individuals modulate forces in relation to situational demands to maintain stability. Objective To examine timing and magnitude of potential proactive and reactive control indices of stability (i.e., initial (P1) and later phase (P2) GRFnet eccentricities) to better understand how individuals modulate forces to maintain dynamic stability in the presence of a novel gait pattern. Methods Whole-body kinematic and kinetic data were collected from twenty-eight young adult participants. Participants completed a 15 min split-belt protocol in which the left belt (0.75 m/s) was slower than the right belt (1.5 m/s). This continuous perturbation was used to provoke instability in which adaptation in control mechanisms could be observed during early adaptation (EA) and late adaptation (LA) time points. Step width and margins of stability were calculated, and specific focus was placed on the on angle of divergence of the net ground rection force. Two-way repeated measures ANOVAs were used to assess adaptation across time points and between individual limbs to further our understanding of dynamic stability. Results During EA participants exhibited conservative control strategies as observed by increased MoS coupled with decreased initial GRFnet (P1) eccentricity and increases in later GRFnet (P2) eccentricity, while no differences in timing were observed. Additionally, step-to-step variability increases in MoS, P1, and P2 magnitude were noted during EA. During LA individuals exhibited similar control strategies relative to baseline, demonstrated by reduced MoS and increases in P1. Further, decreases in step-to-step variability of stability control parameters were also noted during LA. Discussion Findings suggest that changes in spatiotemporal and force related control mechanisms during a continuous whole-body perturbation are requirements of stability preservation. Further, our results suggest that some ML control parameters exhibit adaptive changes, that is, over time there is a lesser reliance on reactive control measures – these results may be exclusive to a population which can offset instability by allocating control appropriately between limbs to achieve suitable maintenance of dynamic stability. Further work is necessary to examine the potential for such adaptive changes among older adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".