Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks
Stuart M Chesher, Carlo Martinotti, Dale W Chapman, Simon M Rosalie, Paula C Charlton, Kevin J Netto, Federico Roggio, Mark Elliott · 2024
Read Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks by Stuart M Chesher, Carlo Martinotti, Dale W Chapman, Simon M Rosalie, Paula C Charlton, Kevin J Netto, Federico Roggio, Mark Elliott (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11676696.txt.
Description
Triathletes and their coaches would love a single sensor that counts strokes, pedal turns, and strides across all three sports. Stuart Chesher and co-authors build such a tool in 2024, pairing a peak counting algorithm with a learning model fed by one trunk mounted sensor. Six athletes raced a full triathlon wearing it, filmed for checking.
The counter caught about ninety-nine percent of strokes and strides and ninety-eight percent of pedal turns. The model also told seated from standing cycling with ninety-four percent accuracy, though it confused seated riding with coasting. A second group of riders helped train the model further. The authors present the pair as a practical aid for measuring race rhythm.
Catalog record
| CREATOR | Stuart M Chesher, Carlo Martinotti, Dale W Chapman, Simon M Rosalie, Paula C Charlton, Kevin J Netto, Federico Roggio, Mark Elliott |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |