Molavian Rozhin, Fatahi Ali, Abbasi Hamed, Khezri Davood
Department of Sport Biomechanics, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Department of Sport Injuries and Corrective Exercises, Sport Sciences Research Institute, Tehran, Iran.
J Biomed Phys Eng. 2023 Oct 1;13(5):383-402. doi: 10.31661/jbpe.v0i0.2305-1621. eCollection 2023 Oct.
Artificial neural network helps humans in a wide range of activities, such as sports.
This paper aims to investigate the effect of artificial intelligence on decision-making related to human gait and sports biomechanics, using computer-based software, and to investigate the impact of artificial intelligence on individuals' biomechanics during gait and sports performance.
This review was conducted in compliance with the PRISMA guidelines. Abstracts and citations were identified through a search based on Science Direct, Google Scholar, PubMed, Elsevier, Springer Link, Web of Science, and Scopus search engines from 1995 up to 2023 to obtain relevant literature about the impact of artificial intelligence on biomechanics. A total of 1000 articles were found related to biomechanical characteristics of gait and sport and 26 articles were directly pertinent to the subject.
The extent of the application of artificial intelligence in sports biomechanics in various fields. In addition, various variables in the fields of kinematics, kinetics, and the field of time can be investigated based on artificial intelligence. Conventional computational techniques are limited by the inability to process data in its raw form. Artificial Intelligence (AI) and Machine Learning (ML) techniques can handle complex and high-dimensional data.
The utilization of specialized systems and neural networks in gait analysis has shown great potential in sports performance analysis. Integrating AI into this field would be a significant advancement in sport biomechanics. Coaches and athletes can develop more precise training regimens with specialized performance prediction models.
人工神经网络在广泛的活动中帮助人类，例如体育活动。
本文旨在使用基于计算机的软件研究人工智能对与人类步态和运动生物力学相关的决策的影响，并研究人工智能在步态和运动表现期间对个体生物力学的影响。
本综述按照PRISMA指南进行。通过基于科学Direct、谷歌学术、PubMed、爱思唯尔、施普林格Link、科学网和Scopus搜索引擎从1995年到2023年进行搜索来识别摘要和引文，以获取关于人工智能对生物力学影响的相关文献。共发现1000篇与步态和运动的生物力学特征相关的文章，其中26篇与该主题直接相关。
人工智能在体育生物力学各个领域的应用程度。此外，可以基于人工智能研究运动学、动力学和时间领域的各种变量。传统的计算技术受到无法处理原始形式数据的限制。人工智能（AI）和机器学习（ML）技术可以处理复杂的高维数据。
在步态分析中利用专门系统和神经网络在运动表现分析中显示出巨大潜力。将人工智能整合到该领域将是运动生物力学的一项重大进步。教练和运动员可以通过专门的表现预测模型制定更精确的训练方案。
