3.18 Assessing changes in gait of concussed adolescents during treadmill walking with randomized obstacle stepping and cognitive task exposure
Bibliographic record
Abstract
Objective Identify gait variations between concussed and healthy participants during treadmill walking with random exposure to challenging conditions. We hypothesized that concussed individuals would be different acutely but improve with time. Design Mixed experimental design combining repeated measures and group comparison. Setting University research laboratory. Participants 13 adolescent student athletes [7 control (14.9±1.3 y.o., 62.4± 13.7kg, 1.66± 0.06m) and 6 concussion (13.5±2.0 y.o., 61.3± 11.6kg, 1.69± 0.14m)]. Concussions were diagnosed by healthcare professionals within two weeks of initial testing. Interventions Participants completed post-injury baseline (T0) at 7.5±4.9 days after concussion and follow-up (T1) at 14.5±3 days following baseline. Sessions included five randomized repetitions of four treadmill-walking conditions: (1) normal walking, (2) cognitive task, (3) obstacle stepping task and (4) combined obstacle stepping and cognitive task. Outcome Measures Stride duration, stride length and mean values of maximal toe clearance (MTC). Main Results Stride duration at T0 (1.18 ±0.05 versus 1.13 ± 0.04, p= 0.047) was longer for concussion than control group respectively. At T0, MTC was not different (p=0.29) between concussion (95.7±11.2mm) and control (88.3±12.6mm) groups but was smaller (p=0.002) at T1 for the concussion (127.6±47.3mm) compared with the control group (214.5mm±31.3mm). MTC was smaller (p<0.001) for the control group over time, but was not different for the concussion group (p=0.149). Conclusions Control group MTC increased over time while the concussion group did not change, indicating a possible lack of adaptation during walking in challenging environments for concussed individuals. Future studies should examine whether a training program could benefit MTC adaptation in concussed individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".