## 1 Introduction  
Muscle fatigue is usually defined as a progressive reduction of sustained muscle force or power output induced by muscle contraction [1; 2; 3]. It is generally accepted that muscle fatigue has two physiological origins: central fatigue, which means the central nervous system fails to activate motoneurons sufficiently, and peripheral (or local) fatigue, which may correspond to changes in excitation-contraction coupling and metabolic factors [4; 5]. 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]. Hence, localized muscle fatigue may be related to tissue oxygenation and associated with metabolic perturbation in muscle tissues. Near-infrared spectroscopy (NIRS) can measure tissue oxygenation noninvasively by means of the good transparency of human tissues in the near-infrared region of the spectrum [10]. NIRS techniques use near-infrared light to illuminate human tissues and then detect the optical intensity of the emergent light that penetrates through the tissues [10].Compared to EMG, NIRS provides a relatively high spatial resolution and acceptable signal-to-noise ratios during exercise, when movement artifacts are properly taken into consideration [11]. More importantly, this technique could measure tissue oxygenation and detect hemodynamic oscillations in the microcirculatory system, which could be used to investigate metabolic processes during exercise [12]. Due to its ability to continuously record tissue oxygenation, its low cost, and its portability, NIRS has been widely utilized to assess muscle fatigue and performance in sports science and clinical medicine [13; 14; 15]. According to a recent study, NIRS might be more sensitive to muscle fatigue than EMG, especially at low levels of activity [16]. Several studies have confirmed the ability of NIRS to measure oxygen consumption in exercise muscle tissues, which can reflect muscle oxidative metabolism under different conditions [17; 18; 19]. The hemodynamic components measured by NIRS mostly come from small vessels including capillaries and arteriolar and venular beds [13]. Thus, these signals could sensitively reflect metabolic activities of the surrounding muscle tissues. Currently, most of the studies using NIRS to investigate the development of muscle fatigue were conducted by analyzing the hemodynamic signals in the time domain [15; 16; 20]. Considering that peripheral hemodynamic responses are nonstationary, analysis in the frequency or time-frequency domain may provide additional information that may be useful to comprehensively understand muscle fatigue and the recovery process. Studies have confirmed that blood flow in the peripheral circulation shows a specific frequency characteristic, especially in the low frequency band (0.005-2 Hz), which may contain information related to metabolic responses in local tissues [21; 22; 23]. [PERSON] and colleagues defined six frequency intervals in the low frequency band (0.005-2 Hz) of the hemodynamic signals, with each interval corresponding to one physiological activity: I: 0.6-2 Hz, cardiac activity; II: 0.145-0.6 Hz, respiratory activity; III: 0.052-0.145 Hz, myogenic activity; IV: 0.021-0.052 Hz, neurogenic activity; V: 0.0095-0.021 Hz, endothelial metabolic activity and VI: 0.005-0.0095 Hz, endothelial activity [24; 25; 26].