A broad range triboelectric stiffness sensor for variable inclusions recognition
With the development of artificial intelligence, stiffness sensors are extensively utilized in various fields, and their integration with robots for automated palpation has gained significant attention. This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator (Stiff-TENG) for variable inclusions in soft objects detection. The Stiff-TENG employs a stacked structure comprising an indium tin oxide film, an elastic sponge, a fluorinated ethylene propylene film with a conductive ink electrode, and two acrylic pieces with a shielding layer. Through the decoupling method, the Stiff-TENG achieves stiffness detection of objects within 1.0 s. The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed. The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures, enabling effective recognition of variable inclusions in soft object, reaching a recognition accuracy of 99.7%. Furthermore, its adaptability makes it well-suited for the detection of pathological conditions within the human body, as pathological tissues often exhibit changes in the stiffness of internal organs. This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
Nano-Micro LettersVolume
15Issue
1Publisher
SpringerVersion
- VoR (Version of Record)
Rights holder
© The Author(s)Publisher statement
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Acceptance date
2023-08-28Publication date
2023-10-20Copyright date
2023ISSN
2311-6706eISSN
2150-5551Publisher version
Language
- en