| Author: | Bing, Fangbo |
| Title: | Investigation of lower limb biomechanics during cycling for injury prevention |
| Advisors: | Zhang, Ming (BME) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Department: | Department of Biomedical Engineering |
| Pages: | xxii, 210 pages : color illustrations |
| Language: | English |
| Abstract: | Cycling is a popular sport that requires precise biomechanical adjustments to optimize performance and minimize injury risks. Among the factors, workload level and saddle height are important in practical riding and training, which could influence the loads on the lower limbs and cycling efficiency. Although the two factors have been explored in previous studies, the conclusions remain controversial. This research investigates the biomechanical effects of saddle height and workload using experimental measurements, dynamic calculations of musculoskeletal (MSK) model, finite element (FE) analysis, and machine learning techniques. The study aims to provide evidence-based recommendations to prevent overuse injuries and enhance performance while offering tools for personalized adjustments. The first study measured electromyography (EMG) of four major lower-limb muscles under different cycling conditions including five saddle heights (95%, 97%, 100%, 103%, and 105% of the greater trochanteric height, GTH) and three workload levels (25%, 50%, and 75% of functional threshold power, FTP). Twenty-seven amateur cyclists performed 15 × 2 mins riding tests. Results revealed that muscle activations of rectus femoris (RF) and biceps femoris (BF) were predominantly influenced by workload, while the medial gastrocnemius (MG) was significantly influenced by saddle height. Balanced activation among muscles was observed at the saddle height of 100% GTH which might be the optimal choice. The second study developed a MSK multibody model incorporating detailed lower-limb muscles to calculate the muscle forces and joint contact forces under various cycling situations. The model was driven by the markers' trajectories and pedal reaction forces (PRFs) and torques. A good agreement between the predicted and measured muscle activations was observed. Generalized estimating equations were used to assess the impacts of saddle height and workload, as well as their interactions, on the interested outcomes adjusted for gender, BMI, and cadence. The results indicated that lower saddle heights and higher workloads were associated with increased joint forces on the hip, knee, and ankle joints, as well as their surrounding muscles. Therefore, selecting a higher saddle height within the comfortable physiological range and maintaining a moderate workload can help mitigate the risks of overuse injuries. On the other hand, cycling symmetry was analyzed according to PRFs, joint angles, and muscle activations. The optimal symmetry in PRFs occurred at the saddle heights of 100% and 103% of GTH. The asymmetry index of knee joint angles increased with the increase of saddle height. The third study established a FE model of knee joint to assess the influence of saddle heights on stress and strain of menisci and cartilages during cycling. The model was constructed based on MRI of right knee joint of a male subject. Bones were simplified to rigid bodies. Major muscles and ligaments were simulated by connectors with defined mechanical properties. The input force loads were PRFs and muscle forces during the crank angle from 90° to 180°. The displacement constraints were the knee flexion angle. The results revealed that stress and strain on the menisci and cartilages decreased with higher saddle heights. This reduction in joint loading highlights the protective role of increasing saddle height within a physiological range. The last study developed a k-nearest neighbors machine learning model to classify saddle height into high, moderate, and low levels based on the features of hip, knee, and ankle joint angles in cycling. This model demonstrated a high classification accuracy of 99.79%, offering a data-driven method to identify appropriate saddle height tailored to dynamic riding characteristics of individuals. This research concludes that moderate workload and optimal saddle height are crucial for achieving balance in muscle activation, reducing joint stress, and maintaining pedaling symmetry. The workload should be set according to the personal FTP. Saddle height around 100%-103% of GTH is recommended to optimize performance and minimize injury risks. Cyclists and coaches can adopt evidence-based adjustments to prevent overuse injuries and enhance riding efficiency. Clinicians can use the data to develop personalized rehabilitation training protocols. Future research should validate these findings across diverse populations and outdoor riding conditions, incorporating advanced biomechanical modelling and machine learning to further refine cycling optimization strategies. |
| Rights: | All rights reserved |
| Access: | open access |
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