IMU-based identification of rowing conditions through supervised machine learning
Anna Leber, Tobias Siebert, Walter Rapp, Steffen Held · 2026
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Description
Anna Leber, Tobias Siebert, Walter Rapp, and Steffen Held read rowing setting from trunk sensors, in work from 2026. Rowers split training between water, static machines, and dynamic machines across a season. Body worn motion sensors could sort those settings without a coach watching every session.
Ten youth rowers rowed hard in all three settings wearing trunk motion units. Ten learning models sorted three stroke windows under leave one athlete out checks. The best model ensemble sorted settings with about eighty-six percent accuracy overall. Water rowing read most clearly, while the dynamic machine often blurred into it. Careful reading is urged since class counts skewed hard toward water.
Catalog record
| CREATOR | Anna Leber, Tobias Siebert, Walter Rapp, Steffen Held |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |