Silicone Reinforced Fabric Sensor with Dual‐Measurement Method: For Human Physiological Signal Detection and Robot Motion Detection
Year: 2025
Type: article
Abstract: Fabric‐based sensors exhibit remarkable potential for human physiological signal detection due to their excellent wearability and flexibility. However, the sensing range and sensitivity of conventional fabric‐based sensors are inherently constrained by the textile substrate. Furthermore, deformation of textile materials during cyclic stretching processes significantly compromises sensor accuracy and stability. Enhancing the performance of textile materials has emerged as a critical research direction for fabric‐based stretchable sensors. In this work, by introducing silicone resin, it develops a sensor with enhanced load‐bearing capacity and sensitivity and devised dual measurement method. Performance evaluation reveals that the silicone‐reinforced fabric sensor achieves an 18.3‐fold enhancement in the maximum bearable stress (from 0.083 to 1.52 MPa), signifying a vastly extended tensile strength, while maintaining excellent stability. A high gauge factor (GF) of 181.5 is achieved within a tensile strain range of 0%–5%. Furthermore, precise discrimination between directional and nondirectional bending is accomplished through the implementation of dual measurement methodologies. Experimental results demonstrate that the sensor satisfies monitoring requirements across various human body locations, including respiratory monitoring and kinematic state detection. Grasping experiments based on soft fingertip operations validate the superior performance of silicone‐reinforced sensors in motion analysis for soft robotic systems.
Source: Advanced Engineering Materials
Authors: Jiantao Yao, Xiangyu Fei, Xianhe Yu, Bingheng Che, Haoqian Gao, Bo Han
Institutions: Yanshan University, Shijiazhuang Tiedao University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Awards: G2763061020, G5520932293, G7566156869
OpenAlex ID: W4416559657