Abstract
This research aims to investigate the development of muscle fatigue and the recovery process revealed by tissue oxygenation. The tissue hemodynamics were measured by near-infrared spectroscopy (NIRS) during a 30-min pre-exercise rest, a 40-cycle heel-lift exercise and a 30-min post-exercise recovery. Wavelet transform was used to obtain the normalized wavelet energy in six frequency intervals (I–VI) and inverse wavelet transform was applied to extract exercise-induced oscillations from the hemodynamic signals. During the exercise phase, the contraction-related oscillations in the total hemoglobin signal (ΔtHb) showed a decreasing trend while the fluctuations in the tissue oxygenation index (TOI) displayed an increasing tendency. The mean TOI value was significantly higher (p < 0.001) under recovery (65.04% ± 2.90%) than that under rest (62.35% ± 3.05%). The normalized wavelet energy of the ΔtHb signal in frequency intervals I (p < 0.001), II (p < 0.05), III (p < 0.05) and IV (p < 0.01) significantly increased by 43.4%, 23.6%, 18.4% and 21.6% during the recovery than that during the pre-exercise rest, while the value in interval VI (p < 0.05) significantly decreased by 16.6%. It could be concluded that NIRS-derived hemodynamic signals can provide valuable information related to muscle fatigue and recovery.
Highlights
Muscle fatigue is usually defined as a progressive reduction of sustained muscle force or power output induced by muscle contraction [1,2,3]
1G,H show the time series of iTOI and itHb reconstructed from the wavelet coefficients
1G,H showcomponent the time series of iTOI by andmuscle itHb reconstructed from thegray wavelet coefficients show the time series of itHb iTOI and itHb reconstructed from the wavelet coefficients related to the frequency component induced by muscle contraction
Summary
Muscle fatigue is usually defined as a progressive reduction of sustained muscle force or power output induced by muscle contraction [1,2,3]. Parameters obtained from surface electromyography (EMG) can reflect the development of localized muscle fatigue noninvasively. Studies have demonstrated that the mean power frequency of EMG signal decreases significantly and progressively as fatigue develops [6,7]. One disadvantage of EMG is that it only provides neural information of the selected muscle, whereas studies have indicated that metabolic factors, such as exercise-induced metabolite accumulation and declined tissue oxygenation level, play a key role in muscle fatigue [8,9]. Studies have reported that hypoxia or ischemia exacerbated the process of local muscle fatigue and influenced the endurance capacity of locomotor muscles [8,9]
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