Design of 3D Controller Using Nanocracking Structure-Based Stretchable Strain Sensor

Seongjin Yang, Minjae Kim, Seong Kyung Hong, Suhyeon Kim, Wan Kyun Chung, Geunbae Lim, Hyungkook Jeon

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we introduce a novel design for a three-dimensional (3D) controller, which incorporates the omni-purpose stretchable strain sensor (OPSS sensor). This sensor exhibits both remarkable sensitivity, with a gauge factor of approximately 30, and an extensive working range, accommodating strain up to 150%, thereby enabling accurate 3D motion sensing. The 3D controller is structured such that its triaxial motion can be discerned independently along the X, Y, and Z axes by quantifying the deformation of the controller through multiple OPSS sensors affixed to its surface. To ensure precise and real-time 3D motion sensing, a machine learning-based data analysis technique was implemented for the effective interpretation of the multiple sensor signals. The outcomes reveal that the resistance-based sensors successfully and accurately track the 3D controller’s motion. We believe that this innovative design holds the potential to augment the performance of 3D motion sensing devices across a diverse range of applications, encompassing gaming, virtual reality, and robotics.

Original languageEnglish
Article number4941
JournalSensors
Volume23
Issue number10
DOIs
StatePublished - May 2023

Keywords

  • human-machine interface
  • machine learning
  • motion analysis
  • strain sensor
  • stretchable materials

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