## 1 Introduction  
Kinematic analysis in cycling is a line of research widely developed in the literature due to its applications at the clinical (e.g., rehabilitation treatments) and sports (e.g., performance optimisation) levels. Different types of technology have been used in the literature for kinematic recording of cycling: goniometers [1], video captures [2], LEDs [3], inertial sensors [4] and videogrammetry [5]. Videogrammetry [5] is currently the most widely accepted by the scientific community. Most kinematic analyses in cycling are focused on the lower body because of its relevance in the development of this task [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]. Most of the pedalling analyses are focused only on the sagittal plane, such as those performed by [PERSON] et al. [6, 7], because this plane contains greater ROM. Outside this plane, the results are very sensitive to possible errorsdue to marker placement or alterations in the trajectory of the markers due to a soft tissue artefact (STA) [18]. However, movements outside the sagittal plane are important from a clinical point of view, as they are the main cause of possible joint overload, pain or injury [13; 19; 20; 21; 22]. To increase the reliability of the kinematic results, it is necessary to define a protocol adapted to the activity to be analysed. To the best of our knowledge, all the analysed articles use marker protocols designed for gait analysis. However, these protocols have some drawbacks when analysing a specific activity like cycling. There are two main drawbacks. First, the existing protocols often use markers that are hidden by the cyclist's posture. For example, markers placed on the anterior superior iliac spine are often partially or completely hidden when the participant is positioned on the bicycle [5; 8; 9; 10; 11; 12; 13; 14; 15; 16]. Second, it is common to place markers in areas where large muscle contractions occur, for example, in the thigh and calf areas. Pedalling can provoke a much higher level of activation in these areas than walking does, resulting in more pronounced muscular contractions and STA. Consequently, the trajectory of markers placed in these areas may change, affecting the results, particularly for those with a small ROM (movements outside the sagittal plane). Some studies [3; 9; 11; 12; 13; 14; 15; 16] have obtained the kinematics by implementing the Least-Square Pose Estimators [23] methodology. This approach is widely used in gait analysis. It is based on the use of a redundant number of markers, with the aim of reducing the effect of STA or loss of marker trajectory. But marker protocols designed with this methodology use a large number of markers, which can affect participant comfort and natural movement during the pedalling test. An alternative to this type of protocols is the use of nonoptimal pose estimators based on a minimum number of physical markers [23]. Papers in the literature [8] that calculate 3D cycling kinematics tend to use the Plug-in-Gait (PiG) [24] marker protocol. Although this protocol does not affect the comfort of the participants, its characteristics have a high impact on the results obtained [23]. This protocol places markers in the anterior superior iliac spines and in the adipose areas of the thighs and calves [24], areas that are highly affected when the subject pedals. This fact, along with the use of a minimum number of markers, means that the results in cycling using the PiG are highly affected by the placement of the markers, which means that it is not recommendable to use this protocol for the 3D cycling analysis. This limitation is addressed in the study conducted by [PERSON] et al. [12]. In their work, a protocol based on Least-Squares Pose Estimators, utilising 46 markers, was employed. These markers included, among others, those positioned on the anterior superior iliac spines, as well as on the adipose regions of the thighs and legs.