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Stretchable Graphene Pressure Sensors with Shar-Pei-like Hierarchical Wrinkles for Collision-Aware Surgical Robotics.

Ting-Hsiang ChangYuan TianChangsheng LiXiaoyi GuKerui LiHaitao YangParita SanghaniChwee Ming LimHongliang RenPo-Yen Chou
Published in: ACS applied materials & interfaces (2019)
Stretchable skin-like pressure sensing with minimized and distinguishable strain-induced interference is essential for the development of collision-aware surgical robotics to improve the safety and efficiency of minimally invasive surgery in a confined space. Inspired by the multidimensional wrinkles of Shar-Pei dog's skin for tactile sensing, we developed a stretchable pressure sensor consisting of reduced graphene oxide (rGO) electrodes with biomimetic topographies to improve the robot-tissue collision detections. A facile fabrication route for stretchable rGO electrodes was first demonstrated by harnessing the surface instability during the sequential deformation processes. The wrinkle-crumple rGO electrodes exhibited high stretchability (∼100%) and strain-insensitive resistance profiles [a gauge factor (GF) < 0.05], which were next utilized to fabricate piezoresistive pressure sensors. The rGO pressure sensors were highly stretchable and exhibited high sensitivity under uniaxial strains (1.37, 1.30, and 0.98 kPa-1 at 0, 30, and 50% stretching states, respectively) along with distinguishable and reduced stretching responsiveness (a small GF ∼0.2 under 40% strains). The stretchable pressure sensors were next integrated with two surgical robots for the transoral robotic surgery procedure. During the cadaveric testing, the rGO sensors can detect the robot-tissue contacts under joint stretches in real time to enhance the surgeon's awareness for collision avoidance. The stretchable rGO pressure sensor that is highly sensitive under large strains provides great potential in the fields of wearable sensing and collision-aware humanoid robots to improve the human-machine interactions.
Keyphrases
  • reduced graphene oxide
  • gold nanoparticles
  • low cost
  • escherichia coli
  • endothelial cells
  • minimally invasive
  • soft tissue
  • blood pressure
  • risk assessment
  • deep learning
  • wound healing
  • metal organic framework