Automatic detection of skate strokes in short-track speed skating using one single IMU: validation of a new method
Bibliographic record
Abstract
Greater impulse is a key performance indicator of success in short track speed skating. The main objective of this study was to develop a method to measure skating strokes using a single IMU. Eight elite or world-class speed skaters had one IMU placed against their skin on the lower back, and a camera setup was positioned to capture the test. A maximal speed trial was then executed by each participant, and the data were analysed to estimate agreement between the camera and IMU estimates of skate stroke events. Inter-evaluator reliability was assessed on a dataset of 22 athletes performing speed trials as well. The algorithm detected 100% of the strokes identified on the video capture system with a root mean square error of 0.06s. Bland-Altman analysis showed a bias of 0.03s between the two methods, which corresponds to the frame rate of the camera. The inter-evaluator reliability yielded an intra-class correlation of 1.00 (ICC3,1) from a dataset of 7089 strokes. This study provides an example of on-ice evaluation of speed skating strokes using a single IMU. This equipment is less expensive than that employed by previous authors and can be implemented in training situations with low invasiveness.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".