Soft strain sensors pose great potential for emerging human–machine interfaces.However,their real-world applications have been limited due to challenges such as low reproducibility,susceptibility to environmental noi...Soft strain sensors pose great potential for emerging human–machine interfaces.However,their real-world applications have been limited due to challenges such as low reproducibility,susceptibility to environmental noise,and short lifetimes,which are attributed to nanotechnologies,including microfabrication techniques.In this study,we present a computer vision-based optical strain(CVOS)sensor system that integrates computer vision with streamlined microfabrication techniques to overcome these challenges and facilitate real-time multiaxial strain mapping.The proposed CVOS sensor consists of an easily fabricated soft silicone substrate with micro-markers and a tiny camera for highly sensitive marker detection.Real-time multiaxial strain mapping allows for measuring and distinguishing complex multi-directional strain patterns,providing the proposed CVOS sensor with higher scalability.Our results indicate that the proposed CVOS sensor is a promising approach for the development of highly sensitive and versatile human–machine interfaces that can operate long-term under real-world conditions.展开更多
基金supported by the Pioneer Research Center Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science,ICT&Future Planning(2022M3C1A3081294)NRF of Korea funded by the Korean government and Ministry of Science and ICT(MSIT)(2020R1A2C2005385)+3 种基金Basic Science Research Program through the NRF of Korea funded by the Ministry of Education(2020R1A6A1A03047902)National R&D Program through the NRF of Korea funded by the Ministry of Science and ICT(2020M3H4A1A02084830)the MSIT under the ICAN(ICT Challenge and Advanced Network of HRD)program(IITP-2022-2020-0-01822)supervised by the IITP(Institute of Information&Communications Technology Planning&Evaluation).
文摘Soft strain sensors pose great potential for emerging human–machine interfaces.However,their real-world applications have been limited due to challenges such as low reproducibility,susceptibility to environmental noise,and short lifetimes,which are attributed to nanotechnologies,including microfabrication techniques.In this study,we present a computer vision-based optical strain(CVOS)sensor system that integrates computer vision with streamlined microfabrication techniques to overcome these challenges and facilitate real-time multiaxial strain mapping.The proposed CVOS sensor consists of an easily fabricated soft silicone substrate with micro-markers and a tiny camera for highly sensitive marker detection.Real-time multiaxial strain mapping allows for measuring and distinguishing complex multi-directional strain patterns,providing the proposed CVOS sensor with higher scalability.Our results indicate that the proposed CVOS sensor is a promising approach for the development of highly sensitive and versatile human–machine interfaces that can operate long-term under real-world conditions.
