Embedded System for Athletes’ Jump Performance Analysis

Achieving peak performance is a primary goal for athletes, and understanding progress is essential for this pursuit. Jump tests are a reliable method for evaluating athletic performance. This study presents an embedded system that leverages the cutting-edge technology present in the SensorTile STEVAL-STLCS01V1 sensor to provide accurate measurements of key performance indicators, such as jump height, power, and reaction time. We propose a wearable technology solution that seamlessly tracks and analyzes these metrics, offering evaluators valuable insights into an athlete’s development. A data collection protocol was implemented involving 22 participants, and the results show that the system’s measurements exhibit a consistent bias relative to the gold standard. A minor bias correction would allow the system to achieve both higher accuracy and precision, demonstrating its potential for practical use in athletic training.

Authors

Institutions

Publication Details

Journal
IEEE Embedded Systems Letters
Published
2025-02-05
DOI
https://doi.org/10.1109/les.2025.3539009
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Embedded System for Athletes’ Jump Performance Analysis

Juan Marcos Toibero, Eugenio Orosco, Jeremías Gaia, Lucas Trigo
IEEE Embedded Systems Letters
Advanced Sensor and Control Systems
article

Embedded System for Athletes’ Jump Performance Analysis

Juan Marcos Toibero, Eugenio Orosco, Jeremías Gaia, Lucas Trigo
article en

Abstract

Achieving peak performance is a primary goal for athletes, and understanding progress is essential for this pursuit. Jump tests are a reliable method for evaluating athletic performance. This study presents an embedded system that leverages the cutting-edge technology present in the SensorTile STEVAL-STLCS01V1 sensor to provide accurate measurements of key performance indicators, such as jump height, power, and reaction time. We propose a wearable technology solution that seamlessly tracks and analyzes these metrics, offering evaluators valuable insights into an athlete’s development. A data collection protocol was implemented involving 22 participants, and the results show that the system’s measurements exhibit a consistent bias relative to the gold standard. A minor bias correction would allow the system to achieve both higher accuracy and precision, demonstrating its potential for practical use in athletic training.

IEEE Embedded Systems LettersVol. 17(6)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), National University of San Juan (AR), Centro Científico Tecnológico - San Juan (AR)
Openalex Percentile: Top 98%
Advanced Sensor and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.