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Identification of human walking patt...
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University of Maryland, College Park.
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Identification of human walking patterns using three-dimensional dynamic modeling.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Identification of human walking patterns using three-dimensional dynamic modeling./
作者:
Nandy, Kaustav.
面頁冊數:
73 p.
附註:
Adviser: Rama Chellappa.
Contained By:
Masters Abstracts International45-02.
標題:
Biophysics, General. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1439139
ISBN:
9780542959851
Identification of human walking patterns using three-dimensional dynamic modeling.
Nandy, Kaustav.
Identification of human walking patterns using three-dimensional dynamic modeling.
- 73 p.
Adviser: Rama Chellappa.
Thesis (M.S.)--University of Maryland, College Park, 2006.
One of the most common activities of our day to day life is walking. However simulating a human walking motion is one of the most difficult tasks to accomplish. Inherently it is an inverted pendulum like system and involves a large number of degrees of freedom. In this thesis we have modeled the human walking motion. The system is designed using a human body model in the form of a kinematic chain consisting of rigid links and revolute joints. Human walking patterns contain information like identity, presence of physical disability and loading conditions of a person like carrying a backpack. We have extracted some of these information and have used our model to discriminate various walking motions. The information that we have used are joint torque and angle sequences modeled using ARMA modeling and Dynamic Time Warping. Our human walking model is validated by comparing it with Stanford marker data.
ISBN: 9780542959851Subjects--Topical Terms:
1019105
Biophysics, General.
Identification of human walking patterns using three-dimensional dynamic modeling.
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One of the most common activities of our day to day life is walking. However simulating a human walking motion is one of the most difficult tasks to accomplish. Inherently it is an inverted pendulum like system and involves a large number of degrees of freedom. In this thesis we have modeled the human walking motion. The system is designed using a human body model in the form of a kinematic chain consisting of rigid links and revolute joints. Human walking patterns contain information like identity, presence of physical disability and loading conditions of a person like carrying a backpack. We have extracted some of these information and have used our model to discriminate various walking motions. The information that we have used are joint torque and angle sequences modeled using ARMA modeling and Dynamic Time Warping. Our human walking model is validated by comparing it with Stanford marker data.
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