本研究的目的為使用結構方程模型(SEM)重新分析皮膚溫度、 肌電 (EMG)、 性別、 手的大小、年齡、濕度、 房間溫度和 MVC 對靈活度的影響。結構方程模型是由國防大學及臺灣科技大學協作研究所建立的輔助資料。先前的實驗收集皮膚溫度、 肌電圖、 人體測量學、 年齡、 環境條件、 MVC 和靈活度資料，分別由十二位男性與十二位女性受測者將手浸泡於溫水內15分鐘，再浸泡於冷水內 40 分鐘。本文建立了兩種結構方程模型，為粗糙與精細靈活度。粗糙靈活度，由結構方程模型觀察證明冷浸泡對皮膚溫度有顯著的影響，而後影響肌電圖和靈活度。性別就手的大小而言對MVC有顯著的影響，隨後影響粗糙靈活度。室內溫度和濕度也影響 MVC，之後影響粗糙靈活度。相反的，唯一的年齡和皮膚溫度顯著的影響精密靈活度。
相關工業: 手對於日常生活有重大影響。手動和精密動作靈活度的結構方程建模結果可被用於量化和預測在冷暴露過程中，裝備人員在完成任務期間，手的表面與物件和工具接觸之靈活度。

The purpose of this study is to reanalyze the effect of skin temperature, EMG, gender, hand size, age, humidity, room temperature, and MVC on hand dexterity using Structural Equation Modeling (SEM). SEM was built based on secondary data from collaboration research between National Defense University and National Taiwan University of Science and Technology. The previous experiments collected skin temperature, EMG, anthropometric, age, ambient condition, MVC, and dexterity data from twelve male and twelve female participants who immersed their hands in a cold water for 40 minutes, followed by warm water for 15 minutes. Two SEM models, gross and fine dexterity, were developed in this paper. For gross dexterity, SEM proved that cold immersion had a significant effect on skin temperature, which later affected EMG and dexterity. Gender in terms of hand size had significant effect on MVC which subsequently affected gross dexterity. Room temperature and humidity also influenced MVC which afterwards affected gross dexterity. In contrast, only age and skin temperature had significant effect on fine dexterity.
Relevance to industry: Hand has a significant influence on daily activity. The results of SEM for both manual and fine motor dexterity may be used to quantify and predict ability of a person’s dexterity during completion of assembly task as the hand interfaces with objects and tools during cold exposure.

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