Document Type : Original research papers
Authors
1
Exercise Physiology, Faculty of Education and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
2
Physical Education & Sport Sciences Dep. - University of Mohaghegh Ardabili - Ardabil - Iran.
3
Department of Exercise Physiology, Faculty of Education and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
4
Assistant Professor, Department of Statistics and Computer Science, University of Mohaghegh Ardabili, Ardabil, Iran
5
Assistant Professor, Department of Electrical and Computer Engineering, Faculty of Technical and Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
6
Assistant Professor, Department of Computer Engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
7
Department of biological sciences in sports faculty of sports science and health Shahid Beheshti University, Tehran, Iran.
Abstract
Introduction
Polarized training is recognized as an effective model for improving endurance performance. However, accurate determination of aerobic and anaerobic thresholds remains challenging because conventional methods such as cardiopulmonary exercise testing or blood lactate measurement have technical and practical limitations.
Background
This study aimed to design and validate an algorithm based on the Short Distance Maximum (S.Dmax) method to estimate metabolic thresholds and to provide individualized polarized training prescriptions.
Methods
This applied-developmental study was conducted with 30 elite football players from the Iranian national deaf team. Heart rate data were recorded during a progressive treadmill test to exhaustion using a Polar device, and heart rate performance curves (HRPC) were plotted. Aerobic and anaerobic thresholds were calculated using the Narita equation and the Dmax method. Subsequently, a dedicated software was developed to automatically identify thresholds, determine training ranges, and generate polarized training prescriptions with a 3:1 low- to high-intensity ratio.
Results
Independent t-test analysis indicated no statistically significant differences (p > 0.05) between training ranges determined by the developed software and the standard Dmax method. The software successfully extracted accurate thresholds and provided individualized polarized training prescriptions.
Discussion
The findings suggest that the proposed S.Dmax-based algorithm can reliably determine metabolic thresholds without the need for invasive procedures. By offering accurate and individualized training zones, this method supports the practical application of polarized training in professional sports settings.
Conclusion
The developed S.Dmax-based algorithm and software proved to be a valid, reliable, and non-invasive tool for determining metabolic thresholds and prescribing polarized training. This approach provides a cost-effective alternative to laboratory methods and can be applied effectively in sports, research, and educational contexts.
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