Cutaneous Sensitivity Across Regions of the Foot Sole and Dorsum are Influenced by Foot Posture
Bibliographic record
Abstract
Understanding the processing of tactile information is crucial for the development of biofeedback interventions that target cutaneous mechanoreceptors. Mechanics of the skin have been shown to influence cutaneous tactile sensitivity. It has been established that foot skin mechanics are altered due to foot posture, but whether these changes affect cutaneous sensitivity are unknown. The purpose of this study was to investigate the potential effect of posture-mediated skin deformation about the ankle joint on perceptual measures of foot skin sensitivity. Participants (N = 20) underwent perceptual skin sensitivity testing on either the foot sole (N = 10) or dorsum (N = 10) with the foot positioned in maximal dorsiflexion/toe extension, maximal plantarflexion/toe flexion, and a neutral foot posture. Perceptual tests included touch sensitivity, stretch sensitivity, and spatial acuity. Regional differences in touch sensitivity were found across the foot sole (p < 0.001) and dorsum (p < 0.001). Touch sensitivity also significantly increased in postures where the skin was compressed (p = 0.001). Regional differences in spatial acuity were found on the foot sole (p = 0.002) but not dorsum (p = 0.666). Spatial acuity was not significantly altered by posture across the foot sole and dorsum, other than an increase in sensitivity at the medial arch in the dorsiflexion posture (p = 0.006). Posture*site interactions were found for stretch sensitivity on the foot sole and dorsum in both the transverse and longitudinal directions (p < 0.005). Stretch sensitivity increased in postures where the skin was pre-stretched on both the foot sole and dorsum. Changes in sensitivity across locations and postures were believed to occur due to concurrent changes in skin mechanics, such as skin hardness and thickness, which follows our previous findings. Future cutaneous biofeedback interventions should be applied with an awareness of these changes in skin sensitivity, to maximize their effectiveness for foot sole and dorsum input.
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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".