Department of Occupational Safety and Health, China Medical University, Taichung City 40604, Taiwan.
Department of Computer-Aided Industrial Design, Overseas Chinese University, Taichung City 40721, Taiwan.
Int J Environ Res Public Health. 2021 Jan 20;18(3):856. doi: 10.3390/ijerph18030856.
There are different types of hand motions in people's daily lives and working environments. However, testing duration increases as the types of hand motions increase to build a normative database. Long testing duration decreases the motivation of study participants. The purpose of this study is to propose models to predict pinch and press strength using grip strength.
One hundred ninety-eight healthy volunteers were recruited from the manufacturing industries in Central Taiwan. The five types of hand motions were grip, lateral pinch, palmar pinch, thumb press, and ball of thumb press. Stepwise multiple linear regression was used to explore the relationship between force type, gender, height, weight, age, and muscle strength.
The prediction models developed according to the variable of the strength of the opposite hand are good for explaining variance (76.9-93.1%). Gender is the key demographic variable in the predicting models. Grip strength is not a good predictor of palmar pinch (adjusted-: 0.572-0.609), nor of thumb press and ball of thumb (adjusted-: 0.279-0.443).
We recommend measuring the palmar pinch and ball of thumb strength and using them to predict the other two hand motions for convenience and time saving.
在日常生活和工作环境中，人们的手部动作有不同的类型。然而，为了构建一个规范的数据库，随着手部动作类型的增加，测试的持续时间也会增加。测试持续时间过长会降低研究参与者的积极性。本研究旨在提出使用握力预测捏力和按压力的模型。
从台湾中部的制造业中招募了 198 名健康志愿者。五种手部动作类型分别为握力、侧捏力、掌捏力、拇指按压力和拇指球按压力。逐步多元线性回归用于探索力类型、性别、身高、体重、年龄和肌肉力量之间的关系。
根据对侧手部力量变量开发的预测模型很好地解释了方差（76.9-93.1%）。性别是预测模型中的关键人口统计学变量。握力不是掌捏力（调整后：0.572-0.609）、拇指按压力和拇指球按压力（调整后：0.279-0.443）的良好预测因子。
我们建议测量掌捏力和拇指球按压力，并将其用于预测其他两种手部动作，以方便和节省时间。
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