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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