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Endurance Capacity of the Biceps Brachii Muscle Using the High-to-Low Ratio between Two Signal Spectral Moments of Surface EMG Signals during Isotonic Contractions

  • Lee, Sang-Sik (Dept. of Biomedical Engineering, Catholic Kwandong University) ;
  • Jang, Jee-Hun (Dept. of Sport and Leisure Studies, Catholic Kwandong University) ;
  • Cho, Chang-Ok (Korea Paralympic Committee) ;
  • Kim, Dong-Jun (Dept. of Electronic Engineering, Cheongju University) ;
  • Moon, Gun-Pil (Dept. of Sport and Leisure Studies, Catholic Kwandong University) ;
  • Kim, Buom (Dept. of Sports Guidance, Daelim University) ;
  • Choi, Ahn-Ryul (Dept. of Biomedical Engineering, Catholic Kwandong University) ;
  • Lee, Ki-Young (Dept. of Biomedical Engineering, Catholic Kwandong University)
  • 투고 : 2016.03.21
  • 심사 : 2017.03.27
  • 발행 : 2017.07.01

초록

Many researchers had examined the validity of using the high-to-low ratio between two fixed frequency band amplitudes (H/L-FFB) from the surface electromyography of a face and body as the first spectral index to assess muscle fatigue. Despite these studies, the disadvantage of this index is the lack of a criterion for choosing the optimal border frequency. We tested the potential of using the high-to-low ratio between two signal spectral moments (H/L-SSM), without fixed border frequencies, to evaluate muscle fatigue and predict endurance time ($T_{end}$), which was determined when the subject was exhausted and could no longer follow the fixed contraction cycle. Ten healthy participants performed five sets of voluntary isotonic contractions until they could only produce 10% and 20% of their maximum voluntary contraction (MVC). The $T_{end}$ values for all participants were $138{\pm}35s$ at 10% MVC and $69{\pm}20s$ at 20% MVC. Changes in conventional spectral indices, such as the mean power frequency (MPF), Dimitrov spectral index (DSI), H/L-FFB, and H/L-SSM, were extracted from surface EMG signals and were monitored using the initial slope computed every 10% of $T_{end}$ as a statistical indicator and compared as a predictor of $T_{end}$. Significant correlations were found between $T_{end}$ and the initial H/L-SSM slope as computed over 30% of $T_{end}$. In conclusion, initial H/L-SSM slope can be used to describe changes in the spectral content of surface EMG signals and can be employed as a good predictor of $T_{end}$ compared to that of conventional spectral indices.

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참고문헌

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