TY - GEN
T1 - Hysteresis compensation for ground contact force measurement with shoe-embedded air pressure sensors
AU - Chinimilli, Prudhvi Tej
AU - Wachtel, Sean Wolfgang
AU - Polygerinos, Panagiotis
AU - Zhang, Wenlong
N1 - Publisher Copyright:
Copyright © 2016 by ASME.
PY - 2016
Y1 - 2016
N2 - This paper reviews the design of smart shoes, a wearable device that measures ground contact forces (GCFs) for gait analysis. Smart shoes utilize four coils of silicone tubes adhered directly underneath the shoe insole at key points of interest. Air pressure sensors connect to each tube coil to measure pressure changes caused by compression. This paper presents static and dynamic calibration performed on each sensing coil to establish a model of internal pressure and the GCF. Based on the model, a phase lead filter is designed to account for the hysteresis effect and visco-elastic properties of the silicone tube in order to provide accurate GCF measurements. To design this filter, the air bladder is modeled using a standard linear solid (SLS) model. The prediction error minimization (PEM) algorithm is then implemented to identify the continuous-time transfer function of this SLS model, which is then transformed to discrete time domain to implement in a digital processor. Mechanical characterization and testing on a healthy subject are performed to validate the model and its capability to compensate for hysteresis in GCF measurement.
AB - This paper reviews the design of smart shoes, a wearable device that measures ground contact forces (GCFs) for gait analysis. Smart shoes utilize four coils of silicone tubes adhered directly underneath the shoe insole at key points of interest. Air pressure sensors connect to each tube coil to measure pressure changes caused by compression. This paper presents static and dynamic calibration performed on each sensing coil to establish a model of internal pressure and the GCF. Based on the model, a phase lead filter is designed to account for the hysteresis effect and visco-elastic properties of the silicone tube in order to provide accurate GCF measurements. To design this filter, the air bladder is modeled using a standard linear solid (SLS) model. The prediction error minimization (PEM) algorithm is then implemented to identify the continuous-time transfer function of this SLS model, which is then transformed to discrete time domain to implement in a digital processor. Mechanical characterization and testing on a healthy subject are performed to validate the model and its capability to compensate for hysteresis in GCF measurement.
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U2 - 10.1115/DSCC2016-9920
DO - 10.1115/DSCC2016-9920
M3 - Conference contribution
AN - SCOPUS:85015818784
T3 - ASME 2016 Dynamic Systems and Control Conference, DSCC 2016
BT - Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation
PB - American Society of Mechanical Engineers
T2 - ASME 2016 Dynamic Systems and Control Conference, DSCC 2016
Y2 - 12 October 2016 through 14 October 2016
ER -