This study aims to develop and evaluate a cycling-specific marker protocol that minimises the number of markers while accounting for the unique biomechanics of cycling. Although movements in the frontal and transverse planes during cycling are limited, they are clinically relevant due to their association with overuse injuries. Existing gait-based marker protocols often fail to consider cycling-specific factors such as posture, range of motion, marker occlusion, and muscle-induced artifacts. The proposed protocol (PP) uses 15 physical and 8 virtual markers. In the absence of a gold standard for 3D pedalling kinematics, the PP was evaluated by comparing it with established gait analysis protocols. The protocol demonstrated high correlation in gait (CCC > 0.98 for hip and knee in the sagittal plane), low intra-subject variability (CV < 15% for hip, knee, and ankle), and high repeatability. During pedalling, position, velocity, and acceleration were measured in all three spatial directions. Notably, angular velocity and linear acceleration showed significant components outside the sagittal plane, particularly for angular velocity. These findings highlight the importance of considering 3D motion when estimating forces, joint moments, and joint-specific powers in cycling biomechanics.

This study proposes a methodology for conducting computational simulations of pathological gait. The literature shows a consensus that biomechanical models for gait analysis should be formulated as control problems. To achieve this, it is common practice to guide the solution using kinematic or kinetic data to prevent temporal instability. The aim of this study is to implement a biomechanical model of the Charcot–Marie–Tooth disease in OpenSim software that enables more comprehensive simulations, which may in future involve the musculoskeletal system of patient and predictive studies. In this way, it will be possible to design specific active assistive devices tailored to each patient. Experimental gait data from six Charcot–Marie–Tooth patients were used. The dataset comprises three-dimensional trajectories of reflective markers placed according to the Davis-Heel protocol. The acquired data allowed a patient-specific adjustment of the biomechanical model. The inverse kinematic was solved, and the results were validated by comparing them with those obtained using the commercial BTS Bioengineering^® software. The results show a strong alignment in ankle kinematics between the OpenSim model and the data generated by BTS Bioengineering^®. Additionally, the kinematic results have been compared with normative curves, allowing the identification of potential areas for intervention using active assistive devices aimed at improving movement patterns of patients.

Background and introduction: The assessment of lower-limb joint moment asymmetries during cycling is critical, as inter-limb imbalances may lead to performance decrements, overload, or injury risk. While most investigations have focused on the sagittal plane, asymmetries may also arise in the frontal and transverse planes, with potential implications for both performance and health. The present study performed a three-dimensional analysis of joint moment asymmetries and examined the influence of pedalling power on their magnitude in ten amateur cyclists under three power conditions. Methodology: Asymmetries were quantified using a modified version of the Normalised Symmetry Index (NSI), the Cross-Correlation Coefficient (CCC), and the newly proposed metric Asymmetries During Cycle (ADC) index. Results: Results indicated that these indices must be applied jointly to identify whether asymmetries arise from magnitude differences, temporal pattern discrepancies, or both. The greatest asymmetries were observed in the frontal and transverse planes, and their magnitude decreased progressively with increasing pedalling power. Discussion: The novelty of this work resides in the combined application of NSI, CCC, and the ADC index to three-dimensional joint moment analysis, which together provide a comprehensive and mechanistic understanding of asymmetries throughout the pedalling cycle, an approach not previously reported in cycling biomechanics.