Objectivity and Validity of EMG Method in Estimating Anaerobic Threshold

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.

Estimation of the second ventilatory threshold through ventricular repolarization profile analysis

“…Assessment of EMG activity has been also recursively employed for VT2 estimation. 6,7 Even if some EMG-based approaches render low estimation errors, the use of wearables for EMG recording is far less extended than for cardiac activity recording, which limits their application. On the other hand, the use of HRV has been shown to render high performance.…”

“…However, whereas the former requires repetitive acquisition of blood samples, the latter employs expensive devices, so that its use is limited to laboratories and specialized centers. For these reasons, there is a growing interest in non-invasive estimation of AnT using a variety of approaches, such as the analysis of electromyographic (EMG) activity 6,7 or electrocardiogram (ECG)-derived indices like heart rate (HR) 8 or heart rate variability (HRV). 9,10 A limitation of EMG-based approaches is that the use of wearable devices is not as extended as in the case of cardiac activity assessment.…”

Accuracy of respiratory gas variables, substrate, and energy use from 15 CPET systems during simulated and human exercise

“…1 As small errors in the intensity can lead to exacerbated fatigue, 15 accurate training zone determination is important. Finally, CPET is also often used as the gold-standard method, for example, to determine the validity of other methods for estimating physiological thresholds, 16,17 to examine the accuracy of prediction equations, 5 or to assess the accuracy of wearable technology for estimating VȮ 2 or energy expenditure. 18,19 Physiological variables such as the rate of oxygen consumption (VȮ 2 ), carbon dioxide production (VĊO 2 ), and minute ventilation (VĖ) can be measured using different techniques during CPET's.…”

Evaluation of the Electromyography Test for the Analysis of the Aerobic-Anaerobic Transition in Elite Cyclists during Incremental Exercise

“…After the key study of Lucía et al, there continues to be a discrepancy in the number and interpretation of EMG breakpoints identified during incremental tests [30,31]. Remarkably, automatic methods used by most authors for EMG-threshold detection had the limitation that only one EMG breakpoint could be possibly identified [8,9,32,33]. Essentially, these methods are based on calculating all the two-segment regressions for the data, and then choosing the two-segment regression with the least residual sum of squares, thus yielding a single intersection point.…”