The potential influence of cognitive decline on freezing of gait in Parkinson's disease: A case study on gait and gaze behaviour
Bibliographic record
Abstract
Freezing of Gait (FOG) in Parkinson's disease is described as a sudden inability to initiate or continue walking that can be triggered by narrow spaces. The underlying mechanism of FOG is not well understood, but cognitive decline has been proposed as one aspect related to FOG. The aim of this study was to investigate whether cognitive decline could affect gait and gaze of FOG patients while approaching a doorway. Two FOG patients matched in age, symptom severity and most affected side were assessed on the TMT, Corsi Block Test, Line Bisection and 3MS, followed by performance of ten walking trials through a doorway of normal and narrow width. The cognitively declined (CD) patient pesented slower speed, smaller step length, lower cadence, larger base of support, and larger step length and step time variability as well as more gaze fixations on a greater number of locations, and for a longer mean duration than the non-cognitively declined (NCD) patient in both conditions. In addition, the CD patient had greater number of shifts in gaze toward a more variable choice of locations while the NCD had more shifts within task relevant locations. The results showed that even though the CD patient attempted to extract more visual information from the environment, this gaze behaviour did not appear to impact on his gait. In this context, cognitive decline may play a role in FOG since the CD patient appeared to have difficulty searching for relevant stimulus to guide locomotion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".