UC Davis

Force Sensitive Resistors (FSRs) are commercially available thin film polymer sensors commonly employed in a multitude of biomechanical measurement environments. Reasons for such wide spread usage lie in the versatility, small profile, and low cost of these sensors. Yet FSRs have limitations. It is commonly accepted that temperature, curvature and biological tissue compliance may impact sensor conductance and resulting force readings. The effect of these variables and degree to which they interact has yet to be comprehensively investigated and quantified. This work systematically assesses varying levels of temperature, sensor curvature and surface compliance using a full factorial design-of-experiments approach. Three models of Interlink FSRs were evaluated. Calibration equations under 12 unique combinations of temperature, curvature and compliance were determined for each sensor. Root mean squared error, mean absolute error, and maximum error were quantified as measures of the impact these thermo/mechanical factors have on sensor performance. It was found that all three variables have the potential to affect FSR calibration curves. The FSR model and corresponding sensor geometry are sensitive to these three mechanical factors at varying levels. Experimental results suggest that reducing sensor error requires calibration of each sensor in an environment as close to its intended use as possible and if multiple FSRs are used in a system, they must be calibrated independently.