Lower limb muscle synergies during walking after stroke: a systematic review
Bibliographic record
Abstract
Purpose: The aim of this systematic review was to determine the number of muscle synergies and the distribution of muscle weightings in stroke patients during gait.Material and Methods: This review is registered on PROSPERO (number: CRD42018088701) and is written following the PRISMA guidelines. A systematic search was conducted using following databases: PubMed, Web of Science, Naric, Cochrane and PEDro. Methodological quality was assessed by the Newcastle-Ottawa Scale and data extraction (subject characteristics, outcome measures and walking protocols) was performed by two independent researchers. The amount and structure of the muscle synergies were the two main outcome measures.Results: In total, ten studies were included in this review. While four synergies are common in healthy controls, stroke patients often showed less synergies during gait. Synergies were determined by the number of muscles measured which varied greatly between studies. Only Tibialis Anterior, Soleus, Gastrocnemius and Rectus Femoris were assessed in all studies.Conclusions: A consensus regarding the amount and composition of muscle synergies in stroke patients is difficult. The majority observed three to four muscle synergies. The decrease in amount of synergies can be explained by merging of synergies, often seen in hip/knee extensors with plantar flexors and hip/knee extensors with knee flexors.IMPLICATIONS FOR REHABILITATIONMuscle synergy analyses are a powerful tool for assessing and classifying neurological deficits.A decreased amount of muscle synergies is related to impaired motor function.Differences in coordinated muscle activity was seen in the paretic and non-paretic side.Merging was often seen in hip/knee extensors with plantar flexors and hip/knee extensors with knee flexors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".