<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This study explores the design and development of an advanced smart wearable device system tailored for monitoring sports training. This system is engineered to track athletic performance in real-time by integrating embedded wearable devices with sophisticated software. It primarily encompasses the recognition of human movement states, detection of electrocardiogram (ECG) signals, and monitoring of respiratory signals, thereby facilitating comprehensive analysis of human physiological parameters and movement metrics. This, in turn, supports athletes in optimizing their training routines. Empirical results from the study indicate that the mean-square error for both ECG and respiratory signals recorded during testing approximated ±0.8Hz, falling within the predetermined error tolerance range. Additionally, analyses of joint angle variations during running activities confirmed the efficacy of the proposed smart wearable system in improving sports performance.</p>
</abstract>

Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This study explores the design and development of an advanced smart wearable device system tailored for monitoring sports training. This system is engineered to track athletic performance in real-time by integrating embedded wearable devices with sophisticated software. It primarily encompasses the recognition of human movement states, detection of electrocardiogram (ECG) signals, and monitoring of respiratory signals, thereby facilitating comprehensive analysis of human physiological parameters and movement metrics. This, in turn, supports athletes in optimizing their training routines. Empirical results from the study indicate that the mean-square error for both ECG and respiratory signals recorded during testing approximated ±0.8Hz, falling within the predetermined error tolerance range. Additionally, analyses of joint angle variations during running activities confirmed the efficacy of the proposed smart wearable system in improving sports performance.

Application of Smart Wearable Devices in Sports Performance Analysis and Enhancement

Fundamental Education Department (Physical Education Department)

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This...

Application of Smart Wearable Devices in Sports Performance Analysis and Enhancement

Online veröffentlicht: 07. Juni 2024

Seitenbereich: -

Eingereicht: 20. Feb. 2024

Akzeptiert: 29. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1434

Schlüsselwörter
Exercise characteristics, Physiological signal detection, Wearable device, Parameter analysis

© 2024 Linying Du, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Application of Smart Wearable Devices in Sports Performance Analysis and Enhancement

Online veröffentlicht: 07. Juni 2024

Seitenbereich: -

Eingereicht: 20. Feb. 2024

Akzeptiert: 29. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1434

SchlüsselwörterExercise characteristics, Physiological signal detection, Wearable device, Parameter analysis

© 2024 Linying Du, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Exercise characteristics, Physiological signal detection, Wearable device, Parameter analysis