Augmented Reality Interfaces Using Virtual Customization of Microstructured Electronic Skin Sensor Sensitivity Performances. (4th February 2021) - Yao, Haicheng; Sun, Tao; Chiam, John Solomon; Tan, Melissa; Ho, Khek Yu; Liu, Zhuangjian; Tee, Benjamin Chee Keong
Abstract: Electronic skins equip robots and biomedical devices with intuitive skin‐like sensitivity. Performance‐driven design of electronic skins is a critical need for electronic or biomedical applications. Prior research primarily focuses on investigating effects of microstructures on sensor performance at low pressure ranges. However, having predictive and tunable electro–mechanical responses across an extensive pressure range (>100 kPa) is paramount. Here, the authors propose a system that virtually customizes micropyramids for e‐skin sensors. The associations between geometry parameters, material properties, and single‐pyramid performance are systematically explored via numerical simulations, empirical characterizations, and analytical solutions. These experimentally validated models allow for the determination of the sensor parameters for the desired performance. An augmented reality interface system for surgery skills training by optimizing sensitivities that match varying tissue stiffnesses is further demonstrated. The platform enables greater effectiveness in rapidly iterating and designing micropyramidal e‐skin for applications in augmented reality interfaces, robotics, and telehealthcare. Abstract : An augmented reality surgical interface system can aid in surgical training of hand stability. Piezo‐capacitive sensors made using pyramidal microstructures transduce tactile feedbacks and the data are used for conducting virtual excisions. Sensor performance is tuned with the new predictive mechanical models developed through single‐pyramid level microstructure indentation measurements.