通过人工智能技术提高运动分析作为临床工具的有效性

S. Simon, K. Johnson
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引用次数: 4

摘要

支持人体运动分析的技术已经取得了巨大的进步,但其临床应用却没有以同样的速度增长。其临床价值的问题与口译所需的时间长度、成本和口译质量有关。来自人工智能的技术,如神经网络和基于知识的系统可以帮助克服这些限制。在这里,作者给出了这些技术的概述,并描述了目前在人体运动分析领域应用这些技术的研究成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the efficacy of motion analysis as a clinical tool through artificial intelligence techniques
Technology supporting human motion analysis has advanced dramatically and yet its clinical application has not grown at the same pace. The issue of its clinical value is related to the length of time it takes to do an interpretation, the cost, and the quality of the interpretation. Techniques from artificial intelligence such as neural networks and knowledge-based systems can help overcome these limitations. Here, the authors give an overview of these techniques and describe current research efforts that apply these techniques in the field of human motion analysis.
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