Establishment of Three-dimensional Full-body Musculoskeletal Model for Cycling Analysis
|關鍵字:||肌肉骨骼系統模型;腳踏車;數值最佳化;騎乘傷害;電腦模擬;室內騎乘;musculoskeletal model;bicycle;numerical optimization;cycling injuries;computer simulation;indoor cycling|
Following the rise of environmental consciousness, issues related to energy conservation and healthcare have already drawn numerous attentions. Since cycling has been proven by many studies to be feasible to reduce the risk of diabetes, high blood pressure and other cardiovascular diseases, it has become a popular exercise and been promoted by government utmostly. However, cycling injuries are common during cycling process. Former studies usually used two-dimensional model, e.g. without hip abductioin/abduction, to study cycling movements and potential injury mechanisms. Lack of hip abduction/adduction movements during cycling may not provide enough informaiton on real cycling. Therefore, the objective of this research was to develop a three-dimensional (3D) full-body musculoskeletal model for evaluating individualized cycling movements and injury risk, such as patellofemoral syndromes, and for designing new bikes. The study consists of three majoy stages: First, establishing a musculoskeletal model using a musculoskeletal simulation software and designing a marker set for cycling movement measurements; Second, acquiring human motion data, crank torque and electromyography (EMG) signals during cycling, and measuring individual anthropometry for model analysis; Third, modifying established musculoskeletal model by comparing model-predicted pedaling torque and muscle activities with experimental data of pedaling torque and EMG signals. Results showed that the EMG signals are similar to analyzed muscle activation on specific muscles. Besides, High similarity between EMG and model-predicted muscle activities was observed in tibialis anterior (TA) and biceps femoris (BF) muscles with variations between subjects, after matching the model crank torque with experiemntal measurements. Model-predicted vastus lateralis (VL), BF and TA muscle activation timing were closed to experimetnal results, while model-predicted deactivation timing of BF agreed with experimental data.. As for the proportion of activation duration in a cycle¸ model-predicted results were significantly shorter than experimental data with the highest statistical differences occurred in VL and TA (VL: p=0.03, TA: p=0.004). In conclusion, this thesis presents a three-dimensional muscluskeletal model, validated by experiment, and procedures for individualized cycling evaluation. The platform could be used to evaluate individual cycling performance and injury risk, and be employed for bike design.