## 4 Discussion
### Comparison with Previous Studies  
The mathematical method utilized here has clearly identified two breakpoints in the linearity of the EMG recordings in most subjects. However, in reviewing the literature there is clearly a disparity of results regarding the number of EMG breakpoints encountered. The existence of a non-linear increase in EMG amplitude at around the aerobic-to-anaerobic transition intensity was reported by some authors since the 1980s [1, 12], but it was not until 1999 that [PERSON] et al. noted the existence of a second EMG breakpoint occurring at near to maximum intensities [6]. Studies prior to [PERSON]'s findings overlooked and missed this breakpoint, which was most likely due to the great interest in determining the transition between the aerobic and anaerobic metabolism, known to be at lower intensities. For this reason, investigations prior to [PERSON]'s work only detected one non-linear increase in EMG variables at about 60%-70% of VO2 MAX [1, 29]. After the key study of [PERSON] 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. In contrast, the multi-segment linear regression method presented here offers the possibility to fit the data with three linear segments, which allows better adjustment of data and, most importantly, determination of two EMG breakpoints. It might be argued that the two EMG thresholds do not really exist and that they are artificially determined by the algorithm. However, various authors have confirmed the existence of two EMG thresholds by visual analysis [10; 11]. The question remains of why the majority of studies have reported only one EMG threshold instead of two. Several factors may contribute to the conflicting results. First, it has been suggested that the second EMG breakpoint can only be detected when subjects are capable of reaching high intensities during the incremental tests, possibly higher than VT\({}_{2}\). This would explain why EMG\({}_{\text{TZ}}\) is more easily found in professional cyclists: They have the capability of recruiting a sufficient number of motor units at high intensities so as to induce an abrupt detectable increase in EMG activity [6; 11; 33]. The two-threshold response reported here was obtained for well-trained cyclists, which lends further support to this theory. A second factor may be the choice of the fixed pedaling cadence. Indeed, with a fixed cadence, the increase in exercise intensity is reached at the expense of increasing muscular effort, which favors the recruitment of fast motor units and possibly facilitates threshold detection at EMG\({}_{\text{TZ}}\)[6; 34]. Finally, it might be possible that previous studies had problems in finding the both EMG breakpoint because they only assessed one muscle, typically the vastus lateralis. In the present study, we have shown that EMG\({}_{\text{TZ}}\) is more frequently detected in the gluteus maximus than in the vastus, and that EMG\({}_{\text{TZ}}\) is more easily detected when various leg muscles are examined. It is known that the contribution of gluteus maximus to total force is higher at highest workloads [35], and that hip extensors muscles, like gluteus maximus, compensate the loss of force production of knee extensors [36; 37]. As a consequence, the onset of fatigue would be delayed in the gluteus maximus compared to the knee extensors; this would also imply a wider range of EMG amplitudes at the highest workloads, thereby explaining the easier detection of both thresholds in the gluteus maximus.