## 1 Introduction  
The primary method of energy production in skeletal muscle is the oxidative metabolism. Nowadays, near-infrared spectroscopy (NIRS) is one of the most used methods to non-invasively measure muscle oxygen consumption. Three different NIRS techniques are common on the market: the continuous-wave (CW) technique, the frequency domain technique, and the time domain technique [1, 2]. Regarding muscle metabolism during active motion, many scientists use the small, lightweight, and cost-efficient CW-NIRS [3, 4, 5, 6].  
A typical field of application is the estimation and comparison of muscle oxygen consumption (mVO\({}_{2}\)) during different motion tasks, thereby covering a broad spectrum from basic research to applied studies in medicine and sport science [7; 8; 9; 10; 11; 12; 13; 14]. The primary parameters of CW-NIRS are the oxygenated (O\({}_{2}\)Hb) and deoxygenated hemoglobin (HHB) from small blood vessels and the total hemoglobin (tHb = O\({}_{2}\)Hb + HHB). In addition, using the spatially resolved spectroscopy method [15], it is possible to calculate the so-called tissue saturation index (TSI), reflecting the dynamic balance between O\({}_{2}\) supply and O\({}_{2}\) consumption [16]. Because CW-NIRS uses the assumption of a constant differential path length factor, it is not possible to measure the absolute concentration changes in HHB and O\({}_{2}\)Hb. Instead, concentration changes are detected relative to a baseline assessed within a defined time period prior to muscle action [2; 17].  
CW-NIRS was found to be a reliable tool for measuring muscle oxygen consumption [18; 19; 20; 21]. However, based on the same hardware and signal(s), three different post-processing options were crystallized to estimate mVO\({}_{2}\) in active muscles: the slope method [22], the amplitude method [23], and the area under the curve method [24]. [PERSON] et al. [25] concluded that the most sensitive, and hence the recommended, method is the calculation of the signal slope using linear regression.  
Although there is agreement that the slope method can be considered the most sensitive approach, the CW-NIRS still comprises O\({}_{2}\)Hb, HHB, and TSI signals; thus, questions arise around which signal (or combination) should be used to analyze and interpret the linear slope. Different approaches are presented in literature., Some authors only used the HHB signal, as this signal is assumed to be less affected by a changing blood volume [26; 27]. Others prefer the interpretation of the O\({}_{2}\)Hb signal [18], or the mean out of the slopes of HHb and O\({}_{2}\)Hb (HBmean) [10; 28; 29]. Additionally, some authors considered the difference between O\({}_{2}\)Hb and HHb (Hbdiff) [30; 31]. Finally, [PERSON] et al. [16] suggest using the TSI signal for the estimation of mVO\({}_{2}\).  
This shows that at least five different ways (O\({}_{2}\)Hb, HHb, Hbdiff, Hbmean, and TSI) to estimate the muscle oxygen consumption using CW-NIRS devices are commonly used in the literature. To the best of our knowledge, there is no information about the comparability of the outcomes of these methods regarding the estimated muscle oxygen consumption. This information is essential, for example, to ponder results and conclusions of different papers that used different approaches of CW-NIRS signal analysis. Hence, the aim of this paper was the comparison of the five presented methods to estimate the muscle oxygen consumption out of CW-NIRS.