Biomechanical Research on Bowed String Musicians: A Scoping Study
Bibliographic record
Abstract
UNLABELLED: Performing arts biomechanics is concerned with quantifying the musculoskeletal demands of artistic tasks. The growing body of related research has prompted this scoping study, solely focused on quantitative research, to summarize the state of the science, identify knowledge gaps, and identify opportunities for future research. OBJECTIVES: To identify, summarize, and categorize quantitative research on the biomechanics of violin, viola, cello, and double bass players, using scoping study methodology. METHODS: Established scoping study methodology was used to identify and categorize existing research. We identified 74 articles for review. Of these, 34 met our scoping study criteria and were included in this study. RESULTS: Twenty-one of the 34 articles that met the scoping criteria were published since 2000. Investigations using electromyography (16 studies) and kinematics (15 studies) comprise the bulk of the research. Two studies employed force transducers for data collection. Violinists were the most frequently studied musicians (22 studies) and double bass players were the least (1 study). Fewer than half of the studies used solely professional musicians as their subjects (13 studies). CONCLUSIONS: This scoping study confirmed that quantitative biomechanical research into bowed string musicians has been performed with increasing frequency and that there are voids in the research, particularly in investigating mechanisms of injury and protective strategies. Currently, arts biomechanics research is largely descriptive in nature. There are few studies that investigate protective strategies, although it is expected that the field will progress to incorporate this type of research.
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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 | 0.028 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".