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논문 기본 정보

자료유형
학술저널
저자정보
Sang-Sik Lee (Catholic Kwandong University) Jee-Hun Jang (Catholic Kwandong University) Chang-Ok Cho (Korea Paralympic Committee) Dong-Jun Kim (Cheongju University) Gun-Pil Moon (Catholic Kwandong University) Buom Kim (Daelim University) Ahn-Ryul Choi (Catholic Kwandong University) Ki-Young Lee (Catholic Kwandong University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.12 No.4
발행연도
2017.7
수록면
1,641 - 1,648 (8page)

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초록· 키워드

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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<SUB>end</SUB>), 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 Tend values for all participants were 138 ± 35 s at 10% MVC and 69 ± 20 s 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 Tend as a statistical indicator and compared as a predictor of T<SUB>end</SUB>. Significant correlations were found between T<SUB>end</SUB> and the initial H/L-SSM slope as computed over 30% of T<SUB>end</SUB>. 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<SUB>end</SUB> compared to that of conventional spectral indices.

목차

Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
5. Conclusion
References

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