{"title":"腰椎建模和仿真的一般框架","authors":"Ayman Kassem, A. Sameh","doi":"10.1504/IJHFMS.2008.022477","DOIUrl":null,"url":null,"abstract":"A general framework for modelling and simulation of the dynamic, three-dimensional motion response of the human lumbar-spine is presented in this paper. Lumbar vertebrae are modelled as rigid bodies and all other Flexible Joint Structures (FJS) (i.e., ligaments, cartilage, muscles, and tendons) are modelled collectively as massless springs and dampers. Coupling coefficients, providing additional constraints, are incorporated into the model. Unknown model coefficients (nominally spring, damping and coupling coefficients) are automatically determined by systematically matching the model predictions to spine forced displacement-time data. A robust parameter optimisation module (Monte Carlo routine and Genetic Algorithm (GA)) was developed for this purpose. Two test cases were included for parameters estimation and model verification.","PeriodicalId":417746,"journal":{"name":"International Journal of Human Factors Modelling and Simulation","volume":"64 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A general framework for lumbar spine modelling and simulation\",\"authors\":\"Ayman Kassem, A. Sameh\",\"doi\":\"10.1504/IJHFMS.2008.022477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A general framework for modelling and simulation of the dynamic, three-dimensional motion response of the human lumbar-spine is presented in this paper. Lumbar vertebrae are modelled as rigid bodies and all other Flexible Joint Structures (FJS) (i.e., ligaments, cartilage, muscles, and tendons) are modelled collectively as massless springs and dampers. Coupling coefficients, providing additional constraints, are incorporated into the model. Unknown model coefficients (nominally spring, damping and coupling coefficients) are automatically determined by systematically matching the model predictions to spine forced displacement-time data. A robust parameter optimisation module (Monte Carlo routine and Genetic Algorithm (GA)) was developed for this purpose. Two test cases were included for parameters estimation and model verification.\",\"PeriodicalId\":417746,\"journal\":{\"name\":\"International Journal of Human Factors Modelling and Simulation\",\"volume\":\"64 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human Factors Modelling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJHFMS.2008.022477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human Factors Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJHFMS.2008.022477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A general framework for lumbar spine modelling and simulation
A general framework for modelling and simulation of the dynamic, three-dimensional motion response of the human lumbar-spine is presented in this paper. Lumbar vertebrae are modelled as rigid bodies and all other Flexible Joint Structures (FJS) (i.e., ligaments, cartilage, muscles, and tendons) are modelled collectively as massless springs and dampers. Coupling coefficients, providing additional constraints, are incorporated into the model. Unknown model coefficients (nominally spring, damping and coupling coefficients) are automatically determined by systematically matching the model predictions to spine forced displacement-time data. A robust parameter optimisation module (Monte Carlo routine and Genetic Algorithm (GA)) was developed for this purpose. Two test cases were included for parameters estimation and model verification.