New Technology in Education on Performance Analysis. Wearable Sensors Utility on Alpine Skiing

Sandu Razvan Enoiu, Denisa Iulia Brus and Veronica Mindrescu
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Sandu Razvan Enoiu: Department of Motor Performance, Transilvania University of Brasov, Brasov 500036, Romania
Denisa Iulia Brus: Interdisciplinary Doctoral School, Transilvania University of Brasov, Brasov 500036, Romania
Veronica Mindrescu: Department of Motor Performance, Transilvania University of Brasov, Brasov 500036, Romania

Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, 2023, vol. 15, issue 4, 279-296

Abstract: The study explains how employing sensors while alpine skiing may raise an athlete's technical proficiency. The sensors offer a reliable set of data that enables the creation of a picture of the athlete's technical dexterity. Through statistical analysis of this data, it is possible to derive the equation for multiple linear regression, which illustrates the relationship between the athlete's time recording (which is regarded as the dependent variable) and the sensor-monitored parameters (considered independent variables). In the study, two linear regression equations were developed, with the number of independent variables considered determining which one was used. The quantity of athletes being watched and their technical proficiency have an impact on how accurate multiple linear regression is. The educational utility of the study derives from the mathematical model provided. This model will enable the athlete to concentrate primarily on the technical aspects of performance improvement while also understanding how improvement in specific technical elements affects the potential time to be achieved.

Keywords: alpine ski; wearable sensor; performance analysis; linear regression (search for similar items in EconPapers)
JEL-codes: I2 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:lum:rev1rl:v:15:y:2023:i:4:p:279-296

DOI: 10.18662/rrem/15.4/793

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