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Int J Sports Med 2014; 35(09): 737-742
DOI: 10.1055/s-0033-1361182
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Objectivity and Validity of EMG Method in Estimating Anaerobic Threshold

S.-k. Kang
1   Department of Graduate School of Education, Yongin University, Yongin, Republic of Korea
,
J. Kim
2   Sport & Wellness Research Center, Yongin University, Yongin, Republic of Korea
,
M. Kwon
3   Academic Committee on General Courses, Hankuk University of Foreign Studies, Seoul, Republic of Korea
,
H. Eom
4   School of Sports Science, Sungkyunkwan University, Suwon, Republic of Korea
› Author Affiliations
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Publication History



accepted after revision 21 October 2013

Publication Date:
02 July 2014 (online)

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Abstract

The purposes of this study were to verify and compare the performances of anaerobic threshold (AT) point estimates among different filtering intervals (9, 15, 20, 25, 30 s) and to investigate the interrelationships of AT point estimates obtained by ventilatory threshold (VT) and muscle fatigue thresholds using electromyographic (EMG) activity during incremental exercise on a cycle ergometer. 69 untrained male university students, yet pursuing regular exercise voluntarily participated in this study. The incremental exercise protocol was applied with a consistent stepwise increase in power output of 20 watts per minute until exhaustion. AT point was also estimated in the same manner using V-slope program with gas exchange parameters. In general, the estimated values of AT point-time computed by EMG method were more consistent across 5 filtering intervals and demonstrated higher correlations among themselves when compared with those values obtained by VT method. The results found in the present study suggest that the EMG signals could be used as an alternative or a new option in estimating AT point. Also the proposed computing procedure implemented in Matlab for the analysis of EMG signals appeared to be valid and reliable as it produced nearly identical values and high correlations with VT estimates.

Key words

filtering intervals - ventilator threshold - electromyographic signals - V-slope
 

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