Ankle proprioception during gait in individuals with incomplete spinal cord injury
Bibliographic record
Abstract
INTRODUCTION: Proprioception is known to be affected after a spinal cord injury (SCI). However, it is currently assessed during simple tasks that do not reflect activities of daily living. To better understand how proprioception affects movement, assessing it during a functional sensorimotor task such as walking is therefore of primary importance. Therefore, the objectives of this study were as follows: (a) measure the protocol reliability of a new robotic test in nondisabled controls; (b) evaluate the effect nonlesion-related factors such as sex, age, pain, and gait speed on ankle proprioception; and (c) assess ankle proprioception during walking in individuals with SCI. METHODS: In the current study, ankle proprioception was assessed during gait in individuals with an incomplete spinal cord injury (iSCI; n = 15) using an electrohydraulic robotized ankle-foot orthosis (rAFO). Ankle proprioceptive threshold was quantified as the participants' ability to detect torque perturbations of varied amplitude applied during swing by the rAFO. In addition, test-retest reliability and the potential effect of nonlesion-related factors (sex, age, pain, and gait speed) were evaluated in nondisabled (ND; n = 65) participants. RESULTS: During gait, individuals with iSCI had a 53% poorer proprioceptive threshold than ND controls (p < .05). Test-retest reliability was good (ICC = 0.78), and only gait speed affected proprioceptive threshold (p = .018). CONCLUSION: This study is the first to show that ankle proprioception assessed during gait is impaired in individuals with an iSCI. The developed test can now be used to better characterize proprioception in population with other neurological conditions and has potential to maximize functional recovery during gait training in those populations.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".