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The Effect of the Artificial Intelligence Techniques Towards Psychomotor Performance Modelling to Improve Sports Performance in Karate

Received: 24 June 2022    Accepted: 12 July 2022    Published: 29 August 2022
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Abstract

The study aims to: Recognize how artificial intelligence techniques affect psychomotor performance modeling to improve sports performance in karate and it is important to help the practitioner improve the implementation of the specific technique, such as performance, energy consumed, skill strength, acceleration and correct posture. Improving psychokinetic modelling, in quantitative, where research is currently focused on detecting posture or shocking movements, but not on the implementation of techniques, improving interactive design to make virtual reality more realistic environment and building smart environments that provide multiple senses with reactions. The researcher used the descriptive method. The sample of the study was chosen in a random way, represented by karate players in Kafr El-Sheikh region, where they numbered (10) player. Especially with the skill of Ura mawashi grei, the recommendations were to provide those techniques in various sports field Conclusions Through the study, it is necessary to provide customized smart support in karate training so that we can create kinetic self-modeling and this was demonstrated through the techniques that were used in the analysis for modeling work, and this helps the coaches to improve sports performance through the analysis of that sport and the special skill of the study URA MAWASHI GERI), and the modeling of the skill of URA MAWASHI GERI came to give a kind of ideal for that skill and to be an example for others, we provide a deep learning computer vision algorithm (Open Pose) to predict the opponent’s movement in the counterattack, an analysis of the player’s psycho-kinetic state through the emotional state of his face Discount during performance.

Published in Automation, Control and Intelligent Systems (Volume 10, Issue 3)
DOI 10.11648/j.acis.20221003.11
Page(s) 35-40
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Artificial Intelligence Techniques, Kinaesthetic Modelling, Improving Athletic

References
[1] Lavarez, N., Sanchez Ruiz, A., Cavazza, M., Shigmatsu, M., and Prender, H.; (2021). Management in the application of smart training for skill safety to improve the performance of motor skills. Journal of Artificial Intelligence in Education (25), 1, 35-59.
[2] Muhammad Asim, Mazen Al-Shammari. (2021). Assessment of skill performance in physical education sciences, first edition, p. 201. Jordan: Dar Safa for Publishing and Distribution.
[3] Muhammad Asim Ghazi. (2020). Artificial intelligence and digital globalization in physical education curricula, first edition, pp. (198-199). Jordan: Dar Amjad for Publishing and Distribution.
[4] Muntazer Majeed Ali. (2018). The effect of feedback exercises according to the preference of sensory modeling in the development of some aspects of learning the front and back ground strokes in tennis. Journal of Physical Education and Sports Science, University of Al-Baseera, 1-12.
[5] Ahmadi, A. R. (2016). Investigating the translational and rotational motion of the swing using accelerometers for the athlete skill assessment. 5th IEEE Conference on Sensors, 980–983.
[6] Baker, M. (2020). The roles of models in artificial intelligence in education research: a prospective view. Journal of Artificial Intelligence in Education, 11 (2), 122–143.
[7] Cabrera, L. M. (January 21th, 2020.). Biomechanical analysis of the Mawashi Geri Jodan kick in karate-do. Universidad de Pinar del Río "Hermanos Saíz Montes de Oca". Facultad de Cultura Física "Nancy Uranga Romagoza". Pinar del Río, Cuba., 22-32.
[8] Cowie, M., & Dyson, R. A. (2016). Short History of Karate. Available online: www.kenkyoha.com (accessed on 1 December 2021). [CrossRef]. p. p. 156.
[9] Hariri, S., & Sadeghi, H. (2018). Biomechanical Analysis of Mawashi-Geri in Technique in Karate: Review Article. international journal of Sport Studies for Health, 1-8.
[10] Kinesiology, V. m.-g. (2012). USA Patent No. 2012, 44, 155–165.
[11] TechTarget. (2021, 12 28). Machine learning platforms. Retrieved from TechTarget network of technology: https://www.techtarget.com/searchenterpriseai/feature/How-to-achieve-explainability-in-AI-models
[12] Zhi-chao, C. (2019). Key pose recognition toward sports scene using deeply-learned model. Journal of Visual Communication and Image Representation, 101-121.
Cite This Article
  • APA Style

    Mohammed Asim Ghazi. (2022). The Effect of the Artificial Intelligence Techniques Towards Psychomotor Performance Modelling to Improve Sports Performance in Karate. Automation, Control and Intelligent Systems, 10(3), 35-40. https://doi.org/10.11648/j.acis.20221003.11

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    ACS Style

    Mohammed Asim Ghazi. The Effect of the Artificial Intelligence Techniques Towards Psychomotor Performance Modelling to Improve Sports Performance in Karate. Autom. Control Intell. Syst. 2022, 10(3), 35-40. doi: 10.11648/j.acis.20221003.11

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    AMA Style

    Mohammed Asim Ghazi. The Effect of the Artificial Intelligence Techniques Towards Psychomotor Performance Modelling to Improve Sports Performance in Karate. Autom Control Intell Syst. 2022;10(3):35-40. doi: 10.11648/j.acis.20221003.11

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  • @article{10.11648/j.acis.20221003.11,
      author = {Mohammed Asim Ghazi},
      title = {The Effect of the Artificial Intelligence Techniques Towards Psychomotor Performance Modelling to Improve Sports Performance in Karate},
      journal = {Automation, Control and Intelligent Systems},
      volume = {10},
      number = {3},
      pages = {35-40},
      doi = {10.11648/j.acis.20221003.11},
      url = {https://doi.org/10.11648/j.acis.20221003.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20221003.11},
      abstract = {The study aims to: Recognize how artificial intelligence techniques affect psychomotor performance modeling to improve sports performance in karate and it is important to help the practitioner improve the implementation of the specific technique, such as performance, energy consumed, skill strength, acceleration and correct posture. Improving psychokinetic modelling, in quantitative, where research is currently focused on detecting posture or shocking movements, but not on the implementation of techniques, improving interactive design to make virtual reality more realistic environment and building smart environments that provide multiple senses with reactions. The researcher used the descriptive method. The sample of the study was chosen in a random way, represented by karate players in Kafr El-Sheikh region, where they numbered (10) player. Especially with the skill of Ura mawashi grei, the recommendations were to provide those techniques in various sports field Conclusions Through the study, it is necessary to provide customized smart support in karate training so that we can create kinetic self-modeling and this was demonstrated through the techniques that were used in the analysis for modeling work, and this helps the coaches to improve sports performance through the analysis of that sport and the special skill of the study URA MAWASHI GERI), and the modeling of the skill of URA MAWASHI GERI came to give a kind of ideal for that skill and to be an example for others, we provide a deep learning computer vision algorithm (Open Pose) to predict the opponent’s movement in the counterattack, an analysis of the player’s psycho-kinetic state through the emotional state of his face Discount during performance.},
     year = {2022}
    }
    

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    AU  - Mohammed Asim Ghazi
    Y1  - 2022/08/29
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    AB  - The study aims to: Recognize how artificial intelligence techniques affect psychomotor performance modeling to improve sports performance in karate and it is important to help the practitioner improve the implementation of the specific technique, such as performance, energy consumed, skill strength, acceleration and correct posture. Improving psychokinetic modelling, in quantitative, where research is currently focused on detecting posture or shocking movements, but not on the implementation of techniques, improving interactive design to make virtual reality more realistic environment and building smart environments that provide multiple senses with reactions. The researcher used the descriptive method. The sample of the study was chosen in a random way, represented by karate players in Kafr El-Sheikh region, where they numbered (10) player. Especially with the skill of Ura mawashi grei, the recommendations were to provide those techniques in various sports field Conclusions Through the study, it is necessary to provide customized smart support in karate training so that we can create kinetic self-modeling and this was demonstrated through the techniques that were used in the analysis for modeling work, and this helps the coaches to improve sports performance through the analysis of that sport and the special skill of the study URA MAWASHI GERI), and the modeling of the skill of URA MAWASHI GERI came to give a kind of ideal for that skill and to be an example for others, we provide a deep learning computer vision algorithm (Open Pose) to predict the opponent’s movement in the counterattack, an analysis of the player’s psycho-kinetic state through the emotional state of his face Discount during performance.
    VL  - 10
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Author Information
  • Faculty of Physical Education, Alexandria University, Alexandria, Egypt

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