Impact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review
Bibliographic record
Abstract
Bodily gestures are essential in piano performance. They allow sound production and, at the same time, facilitate the communication of the expressive content of music. From pianists’ perspective, music expression-related parameters include not only single performance parameters (timing, sound intensity, articulation, etc.), but also more complex parameters (named hereafter abstract parameters), such as music structure features (e.g., phrasing) and extra-musical ideas (e.g., emotions, narratives, etc.). This systematic review aimed to investigate the impact of both performance and abstract parameters related to music expression on kinematics and muscle activity of expert pianists. As complementary objectives, we documented ontological and methodological differences between the studies included, and we addressed how music expression-related parameters affect pianists’ exposure to risk factors of injuries. The search strategy consisted of using concepts and keywords in Medline, Embase, SPORTDiscus, and Web of Science databases, and we followed the PRISMA guidelines. Sixteen studies were included. Eleven studies focused on performance parameters, four studies focused on abstract parameters, and one study addressed both performance and abstract parameters. Performance and abstract music expression-related parameters impacted pianists’ kinematics and muscle activity in a variety of ways. The specific effects were dependent on the type of task and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between music research studies and biomechanics and motor control studies. A set of performance parameters (playing loud, playing fast, staccato articulation, large handspan chords) were identified as potential risk factors of injuries. Further interdisciplinary research mixing methods from empirical music research and biomechanics would help enhance knowledge on the impact of music expression on pianists’ gestures for both performance and injury prevention purposes.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".