{"title":"定量人体步态分析","authors":"V. Zanchi, V. Papić, M. Cecić","doi":"10.1016/S0928-4869(00)00014-8","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, the methodology for normal gait recognition and estimation is described. Normal gait recognition is derived on the basis of kinematics data of the human locomotion system. Measurements were carried out and the data were processed and statistically analyzed.</p><p>The procedure was done on a group of 20 students. Kinematics data have been presented in phase plane. Sets of data in phase plane for the specific discrete moments in time were statistically processed using the Gaussian and Bootstrap methods. Discrete moments are chosen according to specific gait phases of a gait cycle. Finally, as a result of statistical analysis, the gait quality index (GQI) is obtained for each gait phase.</p></div>","PeriodicalId":101162,"journal":{"name":"Simulation Practice and Theory","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0928-4869(00)00014-8","citationCount":"20","resultStr":"{\"title\":\"Quantitative human gait analysis\",\"authors\":\"V. Zanchi, V. Papić, M. Cecić\",\"doi\":\"10.1016/S0928-4869(00)00014-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, the methodology for normal gait recognition and estimation is described. Normal gait recognition is derived on the basis of kinematics data of the human locomotion system. Measurements were carried out and the data were processed and statistically analyzed.</p><p>The procedure was done on a group of 20 students. Kinematics data have been presented in phase plane. Sets of data in phase plane for the specific discrete moments in time were statistically processed using the Gaussian and Bootstrap methods. Discrete moments are chosen according to specific gait phases of a gait cycle. Finally, as a result of statistical analysis, the gait quality index (GQI) is obtained for each gait phase.</p></div>\",\"PeriodicalId\":101162,\"journal\":{\"name\":\"Simulation Practice and Theory\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0928-4869(00)00014-8\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Simulation Practice and Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0928486900000148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation Practice and Theory","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0928486900000148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, the methodology for normal gait recognition and estimation is described. Normal gait recognition is derived on the basis of kinematics data of the human locomotion system. Measurements were carried out and the data were processed and statistically analyzed.
The procedure was done on a group of 20 students. Kinematics data have been presented in phase plane. Sets of data in phase plane for the specific discrete moments in time were statistically processed using the Gaussian and Bootstrap methods. Discrete moments are chosen according to specific gait phases of a gait cycle. Finally, as a result of statistical analysis, the gait quality index (GQI) is obtained for each gait phase.
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