An Examination of Trunk and Right-Hand Coordination in Piano Performance: A Case Comparison of Three Pianists
Why this work is in the frame
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Bibliographic record
Abstract
Playing the piano at expert levels typically involves significant levels of trial-and-error learning since the majority of practice occurs in isolation. To better optimize musical outcomes, pianists might be well served by emulating some of the practices found in sports, where motor learning strategies are grounded in biomechanics and ergonomics in order to improve performance and reduce risk of performance-related injuries. The purpose of the current study is to examine trunk-hand coordination and preparatory movement strategization in piano performance, while considering the influence of anthropometry, skill level of the performer, and musical context. Using a ten-camera motion capture system, movement of C7 and right-hand distal phalanges was tracked at three different playing speeds during performance of an excerpt from Beethoven's "Appassionata" Sonata. There were three participants: two males and one female of differing anthropometric characteristics and skill levels. Motor strategization was examined. Expertise influenced starting trunk position: Initiation intervals and trunk range of motion (ROM) both suggested anthropometry to be a performance factor. For the shortest performer, trunk movement appeared to be used as an efficiency measure to compensate for a shorter arm reach. Skill level was revealed by examining right-hand velocity at the fastest tempo. The current study hypothesizes that an examination of proximal-to-distal preparatory strategies in terms of anthropometry and skill level can help to optimize motor learning for pianists. To realize piano performance as a whole-body skill and encourage healthy practice, pedagogy needs to educate learners regarding fundamental biomechanical and ergonomic principles, movement optimization, and movement strategization in the service of artful performance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it