Victor Ei-Wen Lo1, Yi-Chen Chiu1, Hsin-Hung Tu2. 1. Department of Occupational Safety and Health, China Medical University, Taichung City 40604, Taiwan. 2. Department of Computer-Aided Industrial Design, Overseas Chinese University, Taichung City 40721, Taiwan.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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-R 2: 0.572-0.609), nor of thumb press and ball of thumb (adjusted-R 2: 0.279-0.443). CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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-R 2: 0.572-0.609), nor of thumb press and ball of thumb (adjusted-R 2: 0.279-0.443). CONCLUSIONS: 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.
Entities:
Keywords:
ball of thumb; grip; lateral pinch; manufacturing; palmar pinch; prediction model; strength; thumb press
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