Development of an IoT system prototype for the acquisition of biomechanical data of a speed skater

This project addresses performance enhancement in speed skating through the utilization of emerging technologies such as the Internet of Things (IoT) and Wearable devices. Currently, the scientific literature in this domain is limited, relying primarily on athletes and coaches as key sources of knowledge to refine techniques. The implementation of measurement systems with inertial sensors is proposed to quantify athlete movements, facilitating more precise training. A wireless IoT system is developed using ESP32 modules and inertial sensors to capture limb acceleration data from the skater. Data are stored on the Thingsboard Cloud Web server using the MQTT protocol. The system architecture comprises a central node and four sensor nodes, communicating via ESP-NOW. In addition, an Android mobile application is created to show data capture and visualize inertial information. The tests were carried out with three skaters with varying level of experience, allowing the characterization of limb acceleration data on straight and curved sections of the track.

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Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/etcm63562.2024.10746031
Citations
2
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
0.96
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article

Development of an IoT system prototype for the acquisition of biomechanical data of a speed skater

Fabián Astudillo‐Salinas, Juan Diego Belesaca, Jorge Barreto, Miguel Beltran Saavedra et al.
2 citations
Sports Performance and Training
0.96
article

Development of an IoT system prototype for the acquisition of biomechanical data of a speed skater

Fabián Astudillo‐Salinas, Juan Diego Belesaca, Jorge Barreto, Miguel Beltran Saavedra, Freddy Tacuri Merchan
article en
2 citations

Abstract

This project addresses performance enhancement in speed skating through the utilization of emerging technologies such as the Internet of Things (IoT) and Wearable devices. Currently, the scientific literature in this domain is limited, relying primarily on athletes and coaches as key sources of knowledge to refine techniques. The implementation of measurement systems with inertial sensors is proposed to quantify athlete movements, facilitating more precise training. A wireless IoT system is developed using ESP32 modules and inertial sensors to capture limb acceleration data from the skater. Data are stored on the Thingsboard Cloud Web server using the MQTT protocol. The system architecture comprises a central node and four sensor nodes, communicating via ESP-NOW. In addition, an Android mobile application is created to show data capture and visualize inertial information. The tests were carried out with three skaters with varying level of experience, allowing the characterization of limb acceleration data on straight and curved sections of the track.

University of Cuenca (EC)
Affordable and clean energy
Openalex Percentile: Top 26%
Sports Performance and Training
0.96
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