Impact of expressive intentions on upper-body kinematics in two expert pianists
Bibliographic record
Abstract
Introduction: Expression is a key aspect of music performance. Studies on pianists' gestures and expression have mainly documented the impact of their expressive intentions on proximal segments and head linear kinematics. It remains unclear how pianists' expressive intentions influence joint angular kinematics as well as exposure to risk factors of injury, such as poor overall posture and distal jerky movements, two kinematic factors linked to injury. The first objective of this exploratory case study was to analyze the influence of pianists' expressive intentions on proximal and distal joint range of motion (ROM) across different musical contexts. The second objective was to evaluate the impact of expressive intentions on the posture of joints that are commonly injured in pianists, as well as distal joint angular jerk. Methods: Two expert pianists (P1 and P2) performed six musical excerpts (E1-E6) in two experimental conditions: normal condition (including expressive intentions) and the control condition (strictly playing the composer's notations written in the score with no subjective interpretation). An inertial measurement unit system recorded upper body kinematics. Methods: Two expert pianists (P1 and P2) performed six musical excerpts (E1-E6) in two experimental conditions: normal condition (including expressive intentions) and the control condition (strictly playing the composer's notations written in the score with no subjective interpretation). An inertial measurement unit system recorded upper body kinematics. Results and discussion: Both proximal and distal joint ROM increased when pianists incorporated expressive intentions. Participants exhibited more static, non-neutral wrist postures when incorporating expressive intentions (right and left wrist for P1 and P2, respectively), suggesting an increased risk of distal injury. On the contrary, the thorax exhibited more dynamic, neutral flexion postures, suggesting a reduced risk of proximal injury. These results suggest that expressive intentions may impact proximal and distal postures differently. Incorporating expressive intentions also led to jerkier, less smooth wrist movements in lyrical, non-virtuosic musical excerpts (E1-E4). However, in more virtuosic excerpts (E5-E6), there were generally no differences between conditions. Spatiotemporal constraints might explain these discrepancies between non-virtuosic and virtuosic musical excerpts. These results provide evidence of the impact of expressive intentions on the entire kinematic chain, while highlighting the implications of the subjective dimension of music expression in relation to exposure to risk factors of injury.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".