# Cycling Biomechanics and Its Relationship to Performance
## 5 Electromyography  
Muscle electrical activity is measured using electromyography (EMG, Figure 4A,B). EMG patterns of the main upper and lower limb muscles involved in cycling are illustrated in Figure 4C,D. The amplitude of the EMG signal has a monotonic relationship with the number of muscle fibers activated [61], and it is therefore a good indicator of the intensity of a contraction. However, EMG signal analysis and interpretation are generally complex and require a certain expertise to understand [62] (see also the SENIAM recommendations). The EMG signal is mostly used to characterize muscle coordination or the intensity of muscle activations, which are useful for comparing the technique associated with different conditions such as different positions on the bicycle (Figure 4C,D). _Coordination_ refers to the relative level of activation of different muscles and their relative timing, and it is thought to represent a critical determinant of mechanical efficiency and power output during cycling [63; 64]. EMG patterns, as well as kinematic patterns, are less variable and more consistent across cycles in experts than in novice cyclists [65; 66], showing that the variability of muscle coordination could be an indicator of expertise. Similarly, the level of antagonist muscle co-activation could be an indicator of the efficiency of a cyclist's technique [67]. Antagonist muscle co-activation refers to the activation of an antagonist of a movement (e.g., the _gastrocnemius_ muscles; cf. Figure 4) during the action of its agonist (the _tibialis anterior_ muscle), and it is often computed as a ratio of antagonist-to-agonist EMG  
Figure 4: Electromyography (EMG). **(A)**. Illustration of a cyclist equipped with a set of electrodes and markers before the cycling tests. The _red circle_ indicates the position of the electrode located on the tibialis anterior muscle. **(B)**. Unprocessed EMG signal in _gray_ (raw EMG) superimposed with its envelope in _red_ (integrated EMG). Envelope of the EMG signal for the lower limb (**C**) and upper limb (**D**) muscles when cycling at approximately 500 W (90 RPM) in the seated and standing positions. Data are the average of approximately 15 cycles. EMG analysis allows one to compare the timing and magnitude of the muscle activations between different conditions (here, seated and standing cycling). BB, biceps brachialis; BF, biceps femoris; Br, brachioradialis; Delt, anterior part of deltoideus; ES, erect spinae L4 to L5 level; Flex, flexor digitorum; GM, gastrocnemius medialis; Gmax, gluteus maximus; LD, latissimus dorsi; RF, rectus femoris; Sol, soleus; ST, semitendinosus; TA, tibialis anterior; Tri, triceps lateralis; VL, vastus lateralis; VM, vastus medialis. signal amplitude (in percentage of the maximal activity). Minimizing antagonist co-activation could be a solution to maximizing performance because if the antagonist muscle is unable to fully relax during its agonist action, it creates a resistance that interferes with the movement. Actually, the level of antagonist co-activation between knee flexors (_biceps femoris_ muscle) and extensors (_rectus femoris_ and the _vastus_ muscles) has been shown to be lower in cyclists than triathletes. This level was associated with better cycling economy in cyclists [67], suggesting that reducing the antagonist co-activation level can improve cycling efficiency. The level of antagonist co-activation is also less between ankle flexors (the _tibialis anterior_ muscle) and extensors (the _gastrocnemius_ muscles in particular) in experts compared with novices [66]. However, no previous studies clearly correlated the cycling performance with the level of antagonist co-activation, and it is worth it to mention that antagonist co-activation is always present in highly trained cyclists [8; 68]. Actually, the notion of antagonist is fundamentally ambiguous when considering bi-articular muscles.