Biomechanical Analysis And Application Research Of Human Hip Femoroacetabular Impingement(FAI)based On Hill Muscle Model

Hip joint is a very important joint among the human body joints.It is the largest joint of the lower limb,and also the joint that is easily to be injured during movement.Femoroacetabular impingement(FAI),as a relatively late-time identified disease,is currently recognized as the primary potential cause of "unknown" hip pain,and also one of the most common causes of hip joint pain in young and middle-aged people.For a long time,the research on human hip joint diseases has been based more on traditional methods such as clinical medicine,oral transmission and personal experience,including visual and experience-based surgery operations..However,there is still a lack of in-depth,systematic,and quantitative research on hip joint components such as bones,muscles,and tendons through biomechanical research methods.This research combines theoretical research with the derivation and optimization of the Hill muscle model,to conduct in-depth research on important indicators in Femoroacetabular impingement(FAI): α angle,eccentricities,joint cartilage stress distribution,muscle strength,muscle energy,and other parameters.This research also analyzes the correlation between these indicators and hip-femoral impingement,and the quantitative research of human hip joints under different structures and conditions.This thesis conducts a biomechanical and dynamic analysis of the human hip joint model,providing a scientific basis for the study of hip-related diseases.In this research,we complete the following work:(1)Optimizing and improving the model of Hill muscle by considering the influence of viscous damping on the contraction of elastic elements.This new model can be widely applied to human skeletal muscles and also can be used in hip joint biomechanical models and specific analyses of FAI.(2)Improving the selective image feature matching strategy algorithm.By reducing the time required for feature matching,while maintaining a relatively small impact on the number of matched features,this algorithm improves the efficiency of medical image feature extraction and reduces the time and cost of 3D reconstruction.Additionally,a double-blind experiment is conducted to verify the effectiveness of the image matching strategy by testing all hip joint samples.(3)Establishing a 3D finite element model of the human hip joint and compares normal joints and diseased joints as control groups and experimental groups.The model simulates different α angles at three different workloads: sitting,standing,and walking.The stress states of hip articular cartilage in different α angles are validated.(4)Optimizing muscle constraints by using mechanical dynamic analysis system for simulation experiments.The muscle model matches actual human physiology and provides a new method for analyzing lower limb muscle-skeleton system biomechanics and energy distribution.(5)Optimizing the optical system for motion capture,by integrating data collection systems.The clinical data establish a basic framework for building a human lower limb motor rehabilitation database.This framework collects data from different sources for comparison analysis and summary,to provide new methods for treating and rehabilitating various hip joint motor diseases including FAI.