Document Type : Research Paper I Open Access I Released under (CC BY-NC 4.0) license
Authors
1
PhD Student in Exercise Physiology, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran.
2
Department of Physical Education & Sport Science, University of Mohaghegh Ardabili, Ardabil, Iran
3
Department of Sports Management, Faculty of Psychology and Educational Sciences, Mohaghegh Ardabili University, Ardabil, Iran.
4
Assistant Professor, Department of Statistics and Applications, Faculty of Mathematical Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
5
Assistant Professor, Department of Computer Engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
6
PhD Student in Exercise Physiology, Department of biological sciences in sports faculty of sports science and health Shahid Beheshti University, Tehran, Iran.
Abstract
Abstract
Background: This study aimed to validate a newly developed software based on the Heart Rate Performance Curve and the Distance Maximum-Based algorithm for determining aerobic and anaerobic thresholds and to compare its accuracy with the gas analyzer as the gold standard. Given the practical limitations of gas exchange tests, including high cost, technical complexity, and physiological burden, non-invasive and cost-effective alternatives are needed. Methods: Thirty elite male football players from the Iranian National Deaf Team performed an incremental maximal treadmill test until exhaustion. Heart rate data were continuously recorded at one hertz using a Polar device and analyzed by the software, which applied the Distance Maximum method and Narita’s equation to automatically determine aerobic and anaerobic thresholds. Simultaneously, oxygen uptake, carbon dioxide output, and ventilation were measured by a gas analyzer as reference values. Agreement between methods was assessed using the Intraclass Correlation Coefficient and Bland–Altman analysis. Results: Excellent agreement was observed between thresholds obtained from the software and the gas analyzer. Intraclass Correlation Coefficient values were 0.93 for the aerobic threshold and 1.00 for the anaerobic threshold (p <0.001). Bland–Altman analysis confirmed the absence of systematic bias, with mean differences of –0.41 beats per minute for the aerobic threshold and 0.00 for the anaerobic threshold, and 95% of data points within limits of agreement. Conclusions: The Heart Rate Performance Curve–Distance Maximum-Based software demonstrated high validity and reliability in determining aerobic and anaerobic thresholds. This non-invasive, cost-effective tool can serve as a practical alternative to gas exchange systems for sports performance assessment, personalized training, and continuous physiological monitoring.
Keywords: Aerobic threshold, Anaerobic threshold, Dmax method, Gas analyzer, Heart Rate Performance Curve (HRPC).
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