GAIT DEVIATIONS IN CHILDREN WITH CLASSIC HIGH-FUNCTIONING AUTISM AND LOW-FUNCTIONING AUTISM
Bibliographic record
Abstract
The most significant symptoms of autism are abnormal movement patterns that can lead to the decrease of life quality. The purpose of the study was to compare quantitatively the gait strategy of the typical subjects, children with classic high-functioning autism (HFA), and children with low-functioning autism (LFA). Secondly, the comparison and the evaluation of main changes of plantar pressure parameters between groups were presented. The evaluation was carried out on 18 children with HFA, 10 children with LFA, and 30 age-matched children as a control group. A six camera motion capture system, two force plates and a pedobarograph were used to measure gait kinematics, joint kinetics, and pressure distribution under foot during walking. The analysis shows significant differences between children with HFA, LFA, and typical children in velocity, cadence, and magnitude of plantar pressure distribution. The magnitude of plantar pressure was reduced in children with autism under all anatomical masks, which was caused by plano-valgus deformity. Differences were also observed in joint angles and moments during gait cycle. Some of the results can be a source of important information about gait patterns in autistic children. Any exercise treatment prescribed for autistic children should focus on changing the patterns of plantar pressure distribution, which would be similar to patterns of typical children. However, the exercise treatment cannot be generalized due to the high inter-subject variability in children with autism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".