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Gait Modeling Using Genetic Algorith...
~
Hamather, Hazen James.
Gait Modeling Using Genetic Algorithm Optimized Four-Bar Linkages.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Gait Modeling Using Genetic Algorithm Optimized Four-Bar Linkages./
作者:
Hamather, Hazen James.
面頁冊數:
1 online resource (102 pages)
附註:
Source: Masters Abstracts International, Volume: 57-06.
Contained By:
Masters Abstracts International57-06(E).
標題:
Kinesiology. -
電子資源:
click for full text (PQDT)
ISBN:
9780355940930
Gait Modeling Using Genetic Algorithm Optimized Four-Bar Linkages.
Hamather, Hazen James.
Gait Modeling Using Genetic Algorithm Optimized Four-Bar Linkages.
- 1 online resource (102 pages)
Source: Masters Abstracts International, Volume: 57-06.
Thesis (M.S.)--Rose Hulman Institute of Technology, 2018.
Includes bibliographical references
Important in diagnosing gait abnormalities and pathologies is knowing the position of the leg at various points throughout the gait cycle. This is currently done with motion capture technology but the demand for Inertial Measurement Unit (IMU) based navigation and position tracking has been on the rise. A required component of this alternative is a gait model that can accurately predict the position of points of interest.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355940930Subjects--Topical Terms:
721210
Kinesiology.
Index Terms--Genre/Form:
554714
Electronic books.
Gait Modeling Using Genetic Algorithm Optimized Four-Bar Linkages.
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Important in diagnosing gait abnormalities and pathologies is knowing the position of the leg at various points throughout the gait cycle. This is currently done with motion capture technology but the demand for Inertial Measurement Unit (IMU) based navigation and position tracking has been on the rise. A required component of this alternative is a gait model that can accurately predict the position of points of interest.
520
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In this thesis, a Kalman Filter is constructed using a contrived model to test if, given an accurate gait model, the filter can converge to an accurate and true position solution. Also presented is a Genetic Algorithm approach to dynamic system modeling. The dynamic system is made up of a four-bar linkage and has the ability to adapt to different gaits, both healthy and pathological.
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Results for the Kalman Filter are illustrated through convergence plots, and final position solutions and results for the Genetic Algorithm are given by position solutions of the four-bar linkage. These results show that a genetic approach is robust and has application in gait analysis.
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click for full text (PQDT)
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