Abnormal Muscle Activity and Variability Before, During, and After the Occurrence of Freezing in Parkinson's Disease
Bibliographic record
Abstract
Freezing of gait (FOG) is often experienced in advanced stages of Parkinson’s disease (PD) and can lead to an increased risk of falls. Although spatiotemporal characteristics of FOG are well described, their underlying neuromuscular mechanisms remain poorly understood. Several studies have demonstrated an abnormal activation of distal muscles of the lower limb and coordination impairments during gait in people with PD (pwPD). However, few have investigated how various characteristics of electromyograms (EMGs) change before, during and after a freezing episode (FE). Our objective was to quantify changes in proximal and distal leg muscle activity associated with FEs. In this study, twelve pwPD, confirmed as freezers, performed a repetitive stepping-in-place task used to elicit FE. Surface EMGs were collected from proximal (rectus femoris and biceps femoris (BF)) and distal (tibialis anterior (TA) and gastrocnemius medialis (GM)) muscles. Data epochs of 500 ms were extracted from EMG time series at four different periods: baseline, 2 s before a FE, during a FE, and 2 s after a FE. For each epoch, EMG amplitude (root-mean-square (RMS)), variability (coefficient of variation (CoV)), and inter-muscle functional connectivity (mutual information) were quantified. Results from the analysis of 21 FEs show a significant main effect of Period for EMG amplitude in bilateral TA and in the least affected GM (p < 0.01), with decreased activation before freezing that remained low during and after the FE. On the other hand, a main effect of Period was also found in bilateral BF muscles (p < 0.01) but with increased activation before freezing that was generally sustained during and after FE. Main effects of Period were also found for all measures of variability, except for the least affected GM, showing reduced variability during the FE that returned to baseline in all muscles except both TA. Moreover, an increase in functional connectivity between the least affected distal muscles was seen before the FE. Our findings confirm that many characteristics of EMG patterns of both distal and proximal leg muscles change throughout periods of a FE, suggesting both impairment and adaptive strategies from proximal muscles.
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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) | 0.000 | 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".