Technique analysis in sports: a critical review
Technique analysis in sports: a critical review
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DOI：
10.1080/026404102320675657
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发表时间：
2002-10-01
影响因子：
3.4
通讯作者：
Lees, A
中科院分区：
文献类型：
--
作者：
Lees, A
本文批判性地回顾了技术分析作为一种分析方法，在运动生物力学作为性能分析的一部分。技术作为“一个特定的动作序列”的概念似乎在文献中得到了很好的确立，但技术分析的概念却没有得到很好的发展。虽然可以确定技术分析的几个描述性和分析性目标，但其使用的主要理由是帮助改进性能。然而，支撑这一过程的概念框架发展得很差，缺乏技术和性能之间的区别。技术分析方法分为定性分析、定量分析和预测分析。定性技术分析的特点是观察和主观判断。确定了几种观测辅助手段，包括相位分析、时间分析和关键特征分析。虽然运动的生物力学原理可以用来形成对技术的判断，但关于这些原理的数量和类别却很少有一致的意见。一个“确定性”的模型可以用来确定影响性能的因素，但在这样做，技术变量往往被忽视。定量技术分析依赖于生物力学数据收集方法。确定影响性能的关键技术变量是一个主要问题，但这些变量与影响性能的其他变量之间的区别很小。定量分析是不适合建立整个技能的特点，但新的方法，如使用人工神经网络，描述了可能能够克服这一限制。基于建模和计算机模拟的其他方法也有可能侧重于整个技能。预测技术分析涵盖了这些发展，并通过视觉动画方法在科学家和教练之间提供了一个有吸引力的界面。我的结论是，生物力学需要澄清的基础理论，框架和范围的各种方法，技术分析。
This paper critically reviews technique analysis as an analytical method used within sports biomechanics as a part of performance analysis. The concept of technique as 'a specific sequence of movements' appears to be well established in the literature, but the concept of technique analysis is less well developed. Although several descriptive and analytical goals for technique analysis can be identified, the main justification given for its use is to aid in the improvement of performance. However, the conceptual framework underpinning this process is poorly developed with a lack of distinction between technique and performance. The methods of technique analysis have been divided into qualitative, quantitative and predictive components. Qualitative technique analysis is characterized by observation and subjective judgement. Several aids to observation are identified, including phase analysis, temporal analysis and critical feature analysis. Although biomechanical principles of movement can be used to form judgements about technique, little agreement exists about the number and categories of these principles. A 'deterministic' model can be used to identify factors that affect performance but, in doing so, technique variables are frequently overlooked. Quantitative technique analysis relies on biomechanical data collection methods. The identification of key technique variables that affect performance is a major issue, but these are poorly distinguished from other variables that affect performance. Quantitative analysis is not suitable for establishing the characteristics of the whole skill, but new methods, such as the use of artificial neural networks, are described that may be able to overcome this limitation. Other methods based on modelling and computer simulation also have potential for focusing on the whole skill. Predictive technique analysis encompasses these developments and offers an attractive interface between the scientist and coach through visual animation methods. I conclude that biomechanists need to clarify the underpinning rationale, framework and scope for the various approaches to technique analysis.