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Model Based Inertial Sensing of Human Body Motion Kinematics in Sit-to-Stand Movement (CROSBI ID 529522)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Musić, Josip ; Kamnik, Roman ; Munih, Marko Model Based Inertial Sensing of Human Body Motion Kinematics in Sit-to-Stand Movement // Proceedings of the 6th EUROSIM Congress on Modelling and Simulation (Vol. 1 & Vol. 2) / Zupančič B. , Karba R. , Blažič S. (ur.). Ljubljana: ARGESIM - ARGE Simulation News, 2007. str. Vol. 1 (226) ; V-x

Podaci o odgovornosti

Musić, Josip ; Kamnik, Roman ; Munih, Marko

engleski

Model Based Inertial Sensing of Human Body Motion Kinematics in Sit-to-Stand Movement

In this paper the design and validation of three-segment human body model is presented. The model is aimed at reconstruction of motion trajectories of shank, thigh and HAT (Head-Arms- Trunk) segments in sit-to-stand transfer. For this purpose the Extended Kalman filter (EKF) is applied for fusion of model data and data acquired through measurements with low cost inertial motion sensors (consisting of accelerometers and rate gyroscopes). The simplifications, like motion constraint to sagittal plane, symmetry of movement, assumption of ideal joints, etc., are introduced in the model. Three-segment human body model is constructed using principles of Lagrangian dynamics resulting in three nonlinear, highly coupled second order differential equations. From these equations human body model in Matlab - Simulink environment is constructed and implemented. In conjunction with classical definition of angle, angular rate of change and angular acceleration one can get complete set of data describing human sit-to-stand movement. The inputs that were used in the modeling phase include moments at three joints (ankle, knee and hip joint) by using inverse dynamic approach and free-body diagram technique. Calculated moments include both active and passive joint moments. Several EKF architectures were tested in search for optimal performance. Model validation (in conjunction with EKF) was performed on simulated data using Matlab-Simulink environment, and on actual measurements data acquired with Optotrak optical motion analysis system. Obtained results are presented and discussed, and conclusions are drawn.

lagrangian dynamics; sit-to-stand; extended kalman filter

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Podaci o prilogu

Vol. 1 (226) ; V-x.

2007.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the 6th EUROSIM Congress on Modelling and Simulation (Vol. 1 & Vol. 2)

Zupančič B. , Karba R. , Blažič S.

Ljubljana: ARGESIM - ARGE Simulation News

978-3-901608-32-2

Podaci o skupu

6th EUROSIM Congress on Modelling and Simulation

predavanje

09.09.2007-13.09.2007

Ljubljana, Slovenija

Povezanost rada

Elektrotehnika, Temeljne tehničke znanosti, Drvna tehnologija