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Detecting Outliers in Cardiopulmonary Exercise Testing Data of Ski Racers – A Comparison of Methods and their Effect on the Performance of Fatigue Prediction Cover

Detecting Outliers in Cardiopulmonary Exercise Testing Data of Ski Racers – A Comparison of Methods and their Effect on the Performance of Fatigue Prediction

International Journal of Computer Science in Sport
Volume 22 (2023): Issue 1 (March 2023)
By: N. Baumgartner,  C. Kranzinger,  S. Kranzinger,  C. Snyder,  T. Stöggl and  B. Resch  
Open Access
|Jun 2023

Authors

N. Baumgartner

Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria

C. Kranzinger

Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria

S. Kranzinger

Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria

C. Snyder

Red Bull Athlete Performance Center, Thalgau, Austria
Department of Sport and Exercise Science, University of Salzburg, Austria

T. Stöggl

Red Bull Athlete Performance Center, Thalgau, Austria
Department of Sport and Exercise Science, University of Salzburg, Austria

B. Resch

Department of Geoinformatics Z_GIS, University of Salzburg, Austria
Center for Geographic Analysis, Harvard University, Cambridge MA, USA
DOI: https://doi.org/10.2478/ijcss-2023-0005 | Journal eISSN: 1684-4769
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Language: English
Page range: 65 - 79
Published on: Jun 4, 2023
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
CARDIOPULMONARY EXERCISE TESTING,
ERGOSPIROMETRY,
OUTLIER DETECTION,
SKIING,
FATIGUE PREDICTION
Related subjects:
Computer sciences,
Databases and data mining,
Computer sciences, other,
Sports and recreation,
Physical education,
Sports and recreation, other

© 2023 N. Baumgartner, C. Kranzinger, S. Kranzinger, C. Snyder, T. Stöggl, B. Resch, published by International Association of Computer Science in Sport
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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