Changes in gait speed, gastrocnemius strength, and center of pressure for individuals living with Parkinson's disease
Bibliographic record
Abstract
Background: Parkinson’s disease (PD) is a progressive disease that impacts the ability to walk in individuals with PD. Changes in gait abilities can lead to falls, changes in independence, and decreased quality of life. The purpose of this study was to create two regression analyses to investigate the relationship of six factors with gait velocity and then gait endurance (the respective gait factor was included in the regression analysis). A secondary and tertiary purpose was to examine the relationship of changes in center of pressure data, gastrocnemius strength, and gait speed with those living with PD and their healthy peers. Participants: This study included a sample of convenience of 65 individuals with PD and 25 community dwelling adults. Methods: Data collected included 6 Minute Walk Test (6MWT) (gait endurance), Montreal Cognitive Assessment (cognition), Calf Raise Test (gastrocnemius strength), Four Square Step Test (balance), Fatigue Severity Scale (fatigue), Movement Disorders Society – United Parkinson’s Disease Rating Scale Motor Subscale (disease severity), Age, and 10 Meter Walk (10MWT) (gait speed) in addition to Zeno Mat single support center of pressure distance (SS COP). Results and D Discussion: For individuals with PD there was a significant prediction model for both gait speed and gait endurance. The 6MWT was the only significant predictor variable for the 10MWT, (F=21.01, p<.001, adjusted r2=.70). Both the 10MWT and heel raises were predictors for the 6MWT, (F=22.14, p<.001, adjusted r2=.71). Using Analysis of Variance, a statistically significant difference (p<.05) was found in 10MWT speed and SS COP distance between those with moderate PD impairment and those without PD as well as low PD impairment. Using Analysis of Variance, s statistically significant difference (p<.05) was found in average heel raises between those without PD, low PD impairment, and moderate PD impairment. Conclusions: This study highlights the impact of gastrocnemius strength in individuals living with PD. This may help to shift focus onto the gastrocnemius clinically to allow a more comprehensive assessment and treatment. Finally, the Zeno Mat may provide a clinical tool to assess changes in SS COP % in individuals with PD.
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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 | 0.002 |
| 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) | 0.002 | 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".