Foot contact forces are imperative to gait analysis for uses such as elderly rehabilitation and athletic training. Previously developed methods for legged locomotion force detection involved convoluted sensing systems and significant external equipment. This thesis builds upon previous developed smart shoe sensors adapted from the MIT Cheetah robot using pressure sensors embedded in urethane rubber, Smooth-On's Vytaflex® 20. Past work developed accurate material models in Abaqus CAE to simulate foot contacts for compression and shear. This thesis builds upon the FEA models for two sensor sizes to create a simple model to measure torque and contact angle given force measured by the sensor. Using experiments with physical footpads on a CNC mill verified by simulations from Abaqus FEA, we derived models for contact angles between 0 to 15 degrees and rolling movement from -7 to 7 degrees at various compressions. Models successfully derive relationships between roll and contact angle versus force. These models can be used as a jumping point for data analysis using the smart shoe sensor.;
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