Joint Excursion, Handle Velocity, and Applied Force: a Biomechanical Analysis of Ergonometric Rowing
Bibliographic record
Abstract
Rowers may sacrifice on-water technique during ergonometric training in an attempt to increase stroke output. This cross-sectional study aimed to identify characteristics of ergonometric rowing technique that could be potentially detrimental to an effective and safe on-water performance. Joint excursion, handle velocity, and applied force were measured in 44 athletes while they performed a 2500 meter race on an instrumented ergometer. Results on four subjects are presented here. Their performance is compared to that of a Barcelona Olympic and World champion rower with 12 years of experience to illustrate how athletes deviate from standard on-water technique. Kinematic data showed knee joint oscillations and out-of-phase hip and knee joint reversals. Horizontal handle velocity curves indicated that higher stroke rates were achieved by a decrease in recovery time. Vertical handle velocity curves exhibited bi-directional variations. The largest amplitude occurred at the end of the drive phase during an upward displacement of the handle that was associated with a jerk in the applied force. Force-time curves at different stroke rates showed greater variability in the initial portion of the drive phase. Perpetuation of these technique deviations may be detrimental to on-water performance. Biomechanical analyses may allow coaches to better monitor technique during ergonometric training.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".