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本文引用的文献

1
Movement variability cannot be determined reliably from no-marker conditions.无法从无标记条件可靠地确定运动变异性。
J Biomech. 2006;39(16):3076-9. doi: 10.1016/j.jbiomech.2005.10.020. Epub 2005 Dec 28.
2
The science and medicine of cricket: an overview and update.板球运动的科学与医学:概述与更新
J Sports Sci. 2003 Sep;21(9):733-52. doi: 10.1080/0264041031000140257.
3
The use of artificial intelligence in the analysis of sports performance: a review of applications in human gait analysis and future directions for sports biomechanics.人工智能在运动表现分析中的应用:人体步态分析应用综述及运动生物力学的未来方向
J Sports Sci. 1995 Jun;13(3):229-37. doi: 10.1080/02640419508732232.

体育生物力学中的人工智能:新曙光还是虚假希望?

Artificial intelligence in sports biomechanics: new dawn or false hope?

作者信息

Bartlett Roger

机构信息

School of Physical Education, University of Otago , Dunedin, New Zealand.

出版信息

J Sports Sci Med. 2006 Dec 15;5(4):474-9.

PMID:24357939
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3861744/
Abstract

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques') and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key PointsExpert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis.Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear.Other AI applications, including Evolutionary Computation, have received little attention.

摘要

本文回顾了过去十年人工智能(AI)在运动生物力学中的应用发展。概述了专家系统作为评估运动动作(“技术”)缺陷的诊断工具的可能用途,并给出了此类专家系统的一些示例知识规则。接着将专家系统迄今在其中应用较少的运动技术分析,与日常使用专家系统的步态分析进行了比较。然后探讨了人工神经网络(ANN)在运动生物力学中的应用,重点介绍了在技术分析中应用最广泛的Kohonen自组织映射,以及在整个生物力学领域应用更为广泛的多层网络。文中给出了ANN在标枪、铁饼投掷、铅球和足球踢球等运动生物力学中的应用示例。我还给出了进化计算在足球掷界外球动作优化中的应用示例,该计算预测出了一种与教练文献中相近的最优技术。在简要概述了AI在体育科学和生物力学中的总体应用后,本文最后对AI在运动生物力学中的未来应用进行了一些推测。要点专家系统在运动生物力学中几乎仍未得到应用,这与步态分析这一类似学科不同。人工神经网络,尤其是Kohonen映射,虽已得到应用,但其全部价值仍不明确。包括进化计算在内的其他AI应用几乎未受到关注。