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Endurance time is very important indicator to estimate muscle fatigue. In the case of measuring endurance time directly, it is dangerous for subject to perform a test until the point of failure to main time force. Therefore, this paper presents the model to estimate endirance time using indirect measurements such as personal fators and anthropometrical data. Previous studies had shown that personal factors such as gender and age were not related to endurance time, but recently studies have shown that it is estimated by using independent variable or predictor such as GTA (Gravitational Torque of the horizontal, stretched arm) and MVC (Maximum Voluntary Contraction). The present study investigated variables to estimate endurance time using personal factors and anthrometrical data during isotonic contractions. Twenty five healthy subject volunteered for this study, and performed three test sessions of isotonic contraction exercises at 10~50% respectively. Afterward the correlation coefficient and p-values were compared among regression models using personal factors and anthropometrical data. The results demonstrated that multi-regression model had significant coefficient of correlation, and was useful estimate endurance time.

han-gug jeongbo jeonja tongsin gisul haghoe nonmunji/han-guk jeongbo jeonja tongsin gisul hakoe nonmunji

Prediction Model of Endurance Time to Isotonic Contraction Exercise for Biceps Brachii using Multiple Regression Analysis with Personal Factors and Anthropometric Data