徒手與穿戴手套箱手套之握力與指捏力模型預測之建立

Modeling of Grip and Key Pinch Strength Prediction for Bare and Glovebox Gloved Hand

鄭凱蔚(Kai-Wei Cheng)

指導教授 ： 宋鵬程

朝陽科技大學/理工學院/工業工程與管理系/碩士(2010年)

摘要

上肢的累積性傷害是人因工程研究中主要的一部分，而握力與捏力皆是造成手及手腕累積性傷害之一項主要風險因子。評估握力及捏力可以藉此提供與工作有關的訊息，有學者研究指出，肌力若無法跟作業配合，會因過度使用而造成嚴重傷害，因此這些訊息可用於設備或工作站的設計，降低其所需之肌力。
本研究探討手套材質與厚度對握力與指捏力之影響。三種市面上可買到的手套箱手套，包括丁基合成橡膠手套、氯璜化聚乙烯手套與氯丁橡膠手套，各有0.015英吋與0.03英吋兩種。利用逐步迴歸法與倒傳遞類神經網路法建構握力與指捏力模型。
研究顯示，穿戴手套會減少握力大小，男性握力與指捏力均大於女性，薄手套可保持較高的握力與指捏力，使用丁基合成橡膠材質可保持較高的握力。依據結果建議，穿戴厚度為0.015英吋的丁基合成橡膠手套，可將手套箱手套對握力與指捏力的影響減到最小；利用倒傳遞類神經網路對握力及指捏力有較佳之預測結果。

關鍵字

手套 ； 類神經網路 ； 指捏力 ； 握力

並列摘要

Cumulative trauma disorders（CTDs）of the upper extremities are one of the major ergonomics parts of research. Gripping and pinching both are the common risk factors which are caused the hand and wrist CTDs. The evaluation of grip strength and pinch strength are essential in order to provide information which is related to work capacity. If the muscle strength doesn’t match the tasks, it can cause serious overuse injuries. This information can be used for designing equipments and workstations to fit the strength in order to reduce the force relative to the muscular strength available.
This study evaluates the effect on the grip strength and the key pinch strength on the glove material and the glove thickness. Three commercially available glovebox gloves, namely butyl, hypalon and neoprene in 0.015 and 0.03 inch thickness. Using the stepwise regression and back-propagation neural network（BPNN）to model the grip and key pinch strength.
The results show that the gloved hands decrease the grip strength. Both male grip and key pinch strength are batter than female. Thin gloves retain better grip and key pinch strength compared to thick gloves. Butyl material retains better grip strength than hypalon and neoprene materials. Based on the results, 0.015 inch butyl glove is recommended to minimize the effects on grip and key pinch strength. To use the BPNN can get better prediction on grip and key pinch strength.

並列關鍵字

Grip strength ； Gove ； Artificial neural network ； Key pinch strength

參考文獻

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