Surface electromyographic profiles during gait initiation in people with Parkinson's disease: The effects of external sensory cueing
Bibliographic record
Abstract
BackgroundImpaired gait initiation is a debilitating motor symptom in people with Parkinson's disease (PD). During self-paced (uncued) gait initiation, anticipatory postural adjustments (APAs) are often absent or attenuated, and the first steps are abnormally short. External sensory cues can significantly improve APAs.ObjectiveThe effect of external cueing on lower limb muscle activation during gait initiation, compared to self-initiated steps, was examined in people with PD and healthy older adults (HOA).MethodsGround reaction forces, center of pressure excursions, and lower-limb surface electromyographic profiles (in seven bilateral muscles) were examined in 32 individuals with PD (off-medication) and 10 age-matched HOA during the APA and first step of self-paced or acoustically cued gait initiation.ResultsAnterior (tibialis anterior, vastus lateralis, rectus femoris) and gluteus medius muscles were primarily activated during the early phases of gait initiation, while later phases predominantly involved posterior (soleus, gastrocnemius, biceps femoris) and gluteus medius activations. Cueing facilitated anterior muscles and suppressed posterior muscle activity in both groups, however, activation patterns in PD were not restored to HOA levels. Instead, the PD group had lower early activity during the APA (compared to HOA) and higher late activity.ConclusionsCueing increased anterior muscle activation during gait initiation, rather than evoking a global gain across muscles and timings, demonstrating that cueing predominantly facilitates neural circuitry critical for early APA phases. People with PD showed enhanced late phase activity, probably to compensate for ineffective APAs, and thus have a stronger need to facilitate cue-evoked improvements.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".