• Title/Summary/Keyword: isotonic contraction exercises

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Relationship between Endurance Times and Frequency Parameters in Surface EMG during Isotonic Contraction Exercises (등장성 수축운동시 표피근전도의 주파수파라미터와 근지구력시간과의 상관성)

  • Lee, Sangsik;Go, Jaewook;Jang, Jeehun;Park, Wonyeop;Lee, Kiyoung
    • Journal of Biomedical Engineering Research
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    • v.33 no.3
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    • pp.135-140
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    • 2012
  • Previous investigators have shown that the frequency compression is related to the muscle fatigue and the decreasing conduction velocity of muscle fibers. The aim of the present study was to investigate the relationship between endurance times and frequency parameters such as mean power frequency and median frequency in the surface EMG signal during isotonic contractions. Eight healthy subjects performed voluntary isotonic contractions of biceps Brachii muscle until their endurance times which were determined when the subject could no longer follow the contraction cycle. The regressive slopes of mean power frequency and median frequency were used to describe the frequency compression of the surface EMG signal, and to test the predictability of endurance time. As results of experiment, significant correlations were found between endurance time and the regressive slopes of mean power frequency and mean frequency computed over 50%Tend of endurance time.

Prediction Model of Endurance Time to Isotonic Contraction Exercise for Biceps Brachii using Multiple Regression Analysis with Personal Factors and Anthropometric Data (신체측정치수를 적용하여 다중회귀 분석을 통한 위팔두갈래근 등장성 운동의 근지구력시간 예측모델 연구)

  • Jeong, Ju-Young;Lee, Sang-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.2
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    • pp.178-186
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    • 2015
  • 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 factors 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.