自动化学报2017，Vol.43Issue(3)：418-429,12.DOI:10.16383/j.aas.2017.c160197
前交叉韧带断裂后足底压力特征的聚类分析
Cluster Analysis of Plantar Pressure Characteristics after Anterior Cruciate Ligament Deficiency
摘要
Abstract
The gait characteristics of an actor can be recorded accurately on the plantar pressure map in a movement. It can be used to distinguish whether the gait of this actor in a movement is abnormal or not. Using a set of pressure sensors, the plantar pressure during dynamic motion is collected, and the kinetic and dynamic characteristics of gait are extracted. Then extreme learning machines (ELM) neural network cluster algorithm is used to the analyze of the plantar pressure data and identification of normal or abnormal gait is done. Based on actual clinical data, this method carries out an analysis of patients with anterior cruciate ligament deficiency, which is checked according to the doctor's clinical diagnosis results. Result shows that this method is effective.关键词
足底压力/步态特征/极限学习机神经网络/前交叉韧带断裂/聚类分析Key words
Plantar pressure/gait characteristics/extreme learning machines (ELM) neural network/anterior cruciate ligament deficiency/cluster analysis引用本文复制引用
李晓理,黄红拾,王杰,于媛媛,敖英芳..前交叉韧带断裂后足底压力特征的聚类分析[J].自动化学报,2017,43(3):418-429,12.基金项目
国家自然科学基金(61473034,61673053),高等学校博士学科点专项科研基金(2013000611008),内涵发展–引进人才科研启动费,北京市科技新星交叉学科项目(Z161100004916041),低温重点实验室开放基金(CRYO201316,TIPC,CAS),北京大学医–信交叉建设孵化基金(BMU2016-12)资助Supported by National Natural Science Foundation of China(61473034,61673053),Specialized Research Fund for the Doc-toral Program of Higher Education(2013000611008),the Start-up Funding of Content Development and the Introduced Talent Research,Beijing Nova Programme Interdisciplinary Coopera-tion Project(Z161100004916041),Opening Foundation of Key Laboratory of Cryogenics(CRYO201316,TIPC,CAS),and the Incubation Grant for Medicine and Information Sciences of Peking University(BMU2016-12) （61473034,61673053）
