基于自适应神经模糊推理系统的客观疲劳测量

Sina Ameli, F. Naghdy, D. Stirling, G. Naghdy, M. Aghmesheh
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引用次数: 1

摘要

体育运动引起的疲劳的定量测量是体育工程的一个重要需求。疲劳会降低运动员的体能表现,缺乏适当的测量会造成有害的伤害。本研究采用自适应神经模糊推理系统(ANFIS)方法对体育锻炼引起的疲劳进行综合客观评价。通过附着在人体各节段上的17个无线惯性传感器,收集了一组23个人体节段的运动数据。随后,通过ANFIS对惯性数据进行训练,以识别包括男性和女性在内的8名受试者的加速度数据、身体姿势和产生的动能之间的关系。结果清楚地显示了ANFIS在测量疲劳对一般运动性能的影响方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Objective fatigue measurement through adaptive neuro-fuzzy inference system
Quantitative measurement of physical exercises-induced fatigue is a crucial need in sports engineering. Fatigue reduces physical performance of sports players and lack of appropriate measurement causes harmful injuries. This study provides a comprehensive objective evaluation of physical exercises-induced fatigue by using adaptive neuro fuzzy inference system (ANFIS) method. A set of kinematic data of 23 body segments are collected through 17 wireless inertial sensors attached to body segments. The inertial data are subsequently trained through ANFIS to identify the relationship between acceleration data, body postures and the amount of kinetic energies produced by 8 subjects including male and female. The results clearly show the advantages of ANFIS in measuring the fatigue effects on general ambulatory performance.
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