Haider Mohammed Jassim Al-Khaikani
College of Physical Education and Sport Science, Iraq

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The Effect of Artificial Intelligence (AI) Lactic Threshold Training Design on Some Neurotransmitters, Hydrogen Circuits and Performance Tolerance in Young Boxers Haider Mohammed Jassim Al-Khaikani
Journal of Education and Sport Science Vol. 7 No. 2 (2026): July
Publisher : Wahid Hasyim University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31942/jess.v7i2.17189

Abstract

Objectives: To examine the effects of training exercises prescribed according to the lactate-threshold load on selected neurotransmitters, biochemical indicators, and physical and motor performance among young boxers. Materials and Methods: A one-group experimental pretest–posttest design was employed with a sample of young boxers. Participants completed a structured exercise program in which the training load was prescribed according to their lactate threshold and supported by artificial intelligence–based methods. Acetylcholine, serotonin, carbonic acid, haemoglobin, and selected physical and motor performance variables were assessed before and after the intervention. The pretest and posttest data were classified, analysed, and compared to determine changes following the program. Results: Significant differences were observed between the pretest and posttest measurements across all investigated variables, with the posttest results consistently favouring improved neurotransmitter responses, biochemical indicators, and physical and motor performance. Conclusions: Lactate-threshold–based training was associated with favourable changes in the measured physiological, physical, and motor variables among young boxers. Incorporating artificial intelligence–supported methods into training-load prescription may assist coaches in individualising exercise intensity and optimising athletic development. Further controlled studies with larger samples are needed to confirm these findings.