影响手总灵巧度的因素:一种结构方程建模方法

Y. Prasetyo
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引用次数: 9

摘要

总手灵巧性是人因学和工效学的重要组成部分。本研究的目的是探讨影响手总灵巧度的因素。同时分析性别、手掌长度、握力、手部皮肤温度、室温和室内湿度,利用结构方程模型(SEM)预测了手总灵巧度。扫描电镜显示,手皮肤温度是预测总手灵巧度的最重要因素,其次是握力、性别和室温等其他因素。此外,房间湿度、年龄和手的大小对总手灵巧也有显著的间接影响。本研究得出的扫描电镜可以为人为因素工程师、物理治疗师甚至医生提供非常有价值的理论基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Affecting Gross Manual Dexterity: A Structural Equation Modeling Approach
Gross manual dexterity is an important part of human factors and ergonomics. The purpose of the current study was to investigate factors affecting gross manual dexterity. Gender, palm length, grip strength, hand skin temperature, room temperature, and room humidity were analyzed simultaneously to predict gross manual dexterity by utilizing Structural Equation Modeling (SEM) approach. SEM showed that hand skin temperature was the most important factor for predicting gross manual dexterity, followed by several other factors such as grip strength, gender, and room temperature. In addition, room humidity, age, and hand size were also had significant indirect effects on gross manual dexterity. The SEM derived in this study could be a very valuable theoretical foundation which could be very beneficial for human factors engineer, physical therapist, and even medical doctors.
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