Motorcycle road races last from 30 to 45 min, representing about 20 to 25 laps consisting of 12 to 20 curves. This profile requires thereby 200 brakes and 400 leans per race at velocities generally greater than 200 km/h [1
] that should be managed with accurate synergistic muscle contractions from different part of the body, despite the development of muscle fatigue [2
]. However, only a few studies have investigated muscle fatigability via surface electromyography (sEMG) in riders that were performed either in a laboratory environment [3
] or outside the track [2
]. At present, only two studies have reported an accurate fatigue assessment yielded during a real piloting setup [6
]. Nevertheless, both studies monitored a pilot driving a motorcycle in a motorway or normal road environment, much less demanding and stressful than a racetrack.
Another limitation in studying muscle fatigability during track motorcycle race is related to the interpretation of changes in sEMG during force-varying contractions. It is widely accepted that muscle fatigability represents a progressive decrease in the capacity of an individual to produce high levels of force or to maintain steady force output, a decrease that starts from the beginning of the exercise [8
]. However, such assessments are rather difficult in an “on-track” experimental set-up.
Another common technique to evaluate muscle fatigability is the surface electromyogram (sEMG), which records the electrical activity associated with muscle contraction. During sustained isometric submaximal contractions, fatigue cause an increase in sEMG amplitude (time domain analysis), and a decrease in the power spectrum (frequency domain analysis) [11
]. sEMG amplitude increases could be explained by a combination of an enhanced recruitment of fibers with higher action potential [12
] and an increased synchronization of the motor units [14
]. On the other hand, power spectrum decreases could account for an indirect measure of the metabolic status of the muscle cell membrane [15
], based on matched behavior with conduction velocity of the action potentials that propagate along the muscle fiber membrane, and muscle lactic acid, due to a restricted blood flow [16
]. However, these electrical indices have some limitations during force-varying contractions [17
]. Accordingly, Luttmann et al. [18
] developed the joint analysis of sEMG spectrum and amplitude (JASA), which combines the time and frequency domains of the sEMG signal, allowing to define four quadrants [18
]: (1) force increase (root mean square (RMS) and mean frequency (MF) increase), (2) fatigue (RMS increase and MF decrease), (3) recovery (RMS decrease and MF increase), and (4) force decrease (RMS and MF decrease). This approach allows to determine a reliable pattern of sEMG during repeated tasks with similar force production and has been successfully used to assess neuromuscular fatigue in occupational labor [20
], such as a surgery [18
], wheelchair maneuvers [19
], virtual environments [22
], construction [21
], or cycling [23
Very little information is available about the required muscular load during the different actions that take place during a motorcycle road race. In consequence, we could say that up to now, physical training programs in this sport have been based on empirical knowledge and not on scientific evidence. Therefore, the objectives of this study were (1) to assess the muscle activity changes that occur during riding on a road-race track, and (2) to find out whether muscle fatigue develops when riding a motorcycle during consecutive rounds of a training session on a circuit. We hypothesized that the most demanded muscles should be the flexor superficialis digitorum (FS), as the agonist of the brake-pulling action against the lever [4
], accompanied by the extensor digitorum (ED) considered as the antagonist pair of the FS. Co-contraction of ED and carpi radialis (CR) is supposed to occur during the braking phase and entry of the curve because of their wrist stabilization role already observed in power grip tasks [25
]. Based on the previous hypothesis, we supposed that at the end of the training sessions, at least some of these muscles should get into a fatigue state. Knowing the high inertial forces that must be managed by the motorcycle riders [1
], we additionally hypothesized that a complex interplay should exist between the agonist/antagonist pair mainly responsible for the stabilization of the elbow (biceps brachii versus triceps brachii; BB/TB) as well as for the role of the shoulders, when transmitting forces from de handlebar to the rest of the body and vice versa. With respect to the last hypothesis, the occurrence of fatigue should change the leadership figures and synergies among these muscles.
The relevance of these data should be considered with respect to the difficulty to obtain reliable sEMG recordings while riders drove at high speeds carrying on all measurement instruments despite heat, sudation, and movement artifacts. This challenging experiment opens new area for applied research in motorcycling.
The main objective was to provide, for the first time, sEMG data measured during track motorcycling to define the muscle activity pattern and its changes with fatigue. The results indicated a reliable sEMG pattern for all muscles, with some of them exhibiting signs of fatigue, whereas others showing a progressive increase in the force developed by these muscles across laps and rounds. The main finding of the present study was that in a non-fatigued state, ED, FS, and CR had a substantially higher overall activity than the rest of the analyzed muscles. Additionally, apart from the forearm muscles, TB and DA must be taken into account when riding a motorcycle in an on-track situation. Because of these observations, it is not surprising that these muscles got into a state of fatigue at the end of the track session.
The results confirmed the long-lasting maintenance of an overall considerable activity of the forearm muscles in different layouts of the racetrack throughout the training session. This observation partially explains why a great number of motorcycle riders suffer from the chronic exertional compartment syndrome [28
According to De Luca [16
], a stationarity of the signal is needed to ensure that any electrode movement affects the amplitude of the motor unit action potentials (MUAPs) and to guarantee stability in the motor unit activation pattern. During motorcycle riding, it is impossible to maintain the same contraction levels because the rider moves almost constantly during (1) the braking, (2) side-to-side transitions to lean the motorcycle in the curves, and (3) accelerations during the way out of these curves. From the methodological perspective, it is a great advantage that the majority of the movements are performed repeatedly in the same way to move from one position to another and in the same specific sectors of the circuit, lap by lap. When cornering, the rider maintains the position to be as accurate as possible and tries to not make any sudden movements. On that basis, we analyzed the sEMG signals obtained during a real piloting situation both with single electrical indices and using the JASA method proposed by Luttmann et al. [20
]. For the JASA method, each action that represents the same activity and/or performed with the same body posture is codified. Following the same rationale [18
], we selected sections that involved the same body posture and the same activity. Hence, sEMG signals were consistent and the muscle contractions corresponding to each sector of the track were easily detectable (Figure 1
The data obtained for the arm and the shoulder girdle muscles showed that almost all the RMS slopes were significantly and positively associated with the lap number. If we considered only the sEMG amplitude as a fatigue indicator, our interpretation could be that all muscles were fatigued during the entire session. However, the results of the JASA analysis of the overall curves (Table 2
) indicated that PM and DA muscles were in a fatigue state most of the time. Focusing on those curves with small radii and preceded by higher velocities (C1, C3, and C6), the fact that PM and DA appear in the fatigue quadrant, especially in the R3, indicates the importance of these muscles for the support of the postero-anterior inertia generated during intense braking [27
] as well as for control of the initiation of the “shimmy phenomenon” [32
]. Therefore, we suggest that cornering after a straight line where the preceding velocity is higher than 200 km/h implies a very high involvement of the PM and DA muscles, which leads to fatigue. On the contrary, both the TB and DP muscles showed larger force increase behavior than BB (Table 2
), although in the hardest curves, the latter showed a predominant state of force increase (Figure 4
A). Thus, it is evident that when cornering, these muscles play an important role, probably in withstanding the motorcycle weight and/or in the typical counter-steering maneuver used to modulate the tilt of the motorcycle when getting toward the apex of the curve. Knowing that C2, C3, and C5 were left-sided curves and that the sEMG monitoring was performed only in the right upper limb, it is not surprising that the TB (pushing action during the counter-steering maneuver) was more solicitated in the right-sided curves (C1, C4, and C6) (Figure 2
It is also important to consider the movement chosen to test MVC in baseline condition for normalization purposes, before interpreting changes of muscle activity during a global fatiguing task [33
]. In the present investigation, it is understandable that the BB, DP, and TB activity recorded during the basal MVC were much higher than during piloting the motorcycle. This kind of normalization procedure may facilitate that these three muscles get toward a state of “force increase” during a high percentage of occasions.
Despite showing state variations, the forearm musculature became fatigued in R3, regardless of the curve analyzed, although the ED muscle seemed to suffer more physical loading during riding than the FS and CR. With few exceptions, the ED muscle in particular was the one which experienced the most fatigue, as demonstrated by the RMS and MF slopes and JASA analysis. This finding supports the results obtained by Torrado et al. [5
] who assessed fatigue in the ED muscle after an intermittent fatigue protocol designed for motorcycle riders. These authors suggested, using a motorcycle simulator and protocol duration longer than 30 min, the presence of peripheral fatigue in the ED muscle and changes in cortical excitability, apart from the typical maximal voluntary contraction loss. Nevertheless, this fatigue state was not observed as pronouncedly in the FS and CR muscles, because they changed their position from one quadrant to another (Table 2
and Figure 4
B). Such state alternations occurred in these two muscles especially in R2. It seems that professional riders are more habituated to coactivating the aforementioned muscles to improve precision and sensitivity during braking [4
]. This behavior was observed in R2, normally considered as the best round from the performance point of view. This was because the rider became accustomed to the track and begins to increase the pace without yet suffering from the external manifestations of fatigue. In fact, the fastest laps tend to be obtained from the second round onward during training sessions. The alternation observed here, precisely in the more technical curves (4 and 5 could thus be explained by the necessity of maintaining the finetuning and precision of the riding in spite of fatigue [4
]. Nevertheless, in R3, the fatigue state was clearly present, in agreement with a previous study that confirmed that fatigue was not manifested from the very beginning of a 24 h endurance race [2
]. In this study, the normalized MVC was maintained with respect to the basal value during the first two relays, but afterwards it started to decline because of fatigue.
To our knowledge, there has not been a report on such a level of applied analysis in this sport. This study provides the first scientific and direct assessment of what happens when a pilot rides a motorcycle. However, the recording of the gas handle path and of the pressure exerted on the brake lever by a telemetric system of the kind habitually used by the teams of the MotoGP World Championship could upgrade the present study. Hence, this study is a first step towards the assessment of the fatigue during a race situation.
The limitations of this study come obviously from the reduced sample size. Future investigation should address this topic with a greater number of riders and verify if muscle activity patterns, as well as changes of these patterns with the occurrence fatigue, can be generalized or not. On the other hand, the limited number of available sEMG channels (n
= 8) did not allow us to monitor the left upper limb at the same time. This limitation could certainly cause the underestimation of the muscle activity when cornering the left-sided curves and prevents from comparisons between both limb sides. Another limitation comes from the fact that we used only one racetrack. It could be interesting to monitor the same riders in different racetracks and investigate if the sEMG signal is useful to distinguish different layouts. Finally, it must be mentioned that contrarily to the sEMG amplitude, we must be cautious when interpreting physiological mechanisms derived from changes in the sEMG frequency spectrum. This is because they are not directly related with differences in recruitment and motor unit firing rate of the target muscles [12