An EKF-based approach for estimating leg stiffness during walking

The spring-like behavior is an inherent condition for human walking and running. Since leg stiffness k leg is a parameter that cannot be directly measured, many techniques has been proposed in order to estimate it, most of them using force data. This paper intends to address this problem using an Ex...

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Bibliographic Details
Published in2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2013; pp. 7226 - 7228
Main Authors Ochoa-Diaz, Claudia, Menegaz, Henrique M., Bo, Antonio P. L., Borges, Geovany A.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2013
Subjects
Biological system modeling
Biomechanical Phenomena
Biomechanics
Biomedical Engineering - methods
Computer Simulation
Equipment Design
Estimation
Gait - physiology
Humans
Kalman filters
Leg
Legged locomotion
Mathematical model
Models, Biological
Monitoring, Ambulatory - instrumentation
Monitoring, Ambulatory - methods
Motion
Robotics
Running
Simulation
Software
Walking - physiology
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Summary:The spring-like behavior is an inherent condition for human walking and running. Since leg stiffness k leg is a parameter that cannot be directly measured, many techniques has been proposed in order to estimate it, most of them using force data. This paper intends to address this problem using an Extended Kalman Filter (EKF) based on the Spring-Loaded Inverted Pendulum (SLIP) model. The formulation of the filter only uses as measurement information the Center of Mass (CoM) position and velocity, no a priori information about the stiffness value is known. From simulation results, it is shown that the EKF-based approach can generate a reliable stiffness estimation for walking.
ISSN:1094-687X
1557-170X
1558-4615
DOI:10.1109/EMBC.2013.6611225