Near-hysteresis-free soft tactile electronic skins for wearables and reliable machine learning

被引:148
作者
Yao, Haicheng [1 ]
Yang, Weidong [1 ,6 ]
Cheng, Wen [1 ]
Tan, Yu Jun [1 ,2 ]
See, Hian Hian [1 ]
Li, Si [1 ,2 ]
Ali, Hashina Parveen Anwar [1 ]
Lim, Brian Z. H. [1 ]
Liu, Zhuangjian [3 ]
Tee, Benjamin C. K. [1 ,2 ,4 ,5 ]
机构
[1] Natl Univ Singapore, Mat Sci & Engn, Singapore 117575, Singapore
[2] Natl Univ Singapore, Inst Hlth Innovat & Technol iHealthtech, Singapore 117599, Singapore
[3] A STAR Res Ent, Inst High Performance Comp, Singapore 138632, Singapore
[4] Natl Univ Singapore, N1 Inst Hlth Natl, Singapore 117456, Singapore
[5] Natl Univ Singapore, Elect & Comp Engn, Singapore 117583, Singapore
[6] Tongji Univ, Sch Aerosp Engn & Appl Mech, Shanghai 200092, Peoples R China
关键词
sensor; electronic skin; machine learning; robotics; wearable; PULSE-WAVE VELOCITY; PRESSURE SENSORS; ARTERIAL STIFFNESS;
D O I
10.1073/pnas.2010989117
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Electronic skins are essential for real-time health monitoring and tactile perception in robots. Although the use of soft elastomers and microstructures have improved the sensitivity and pressuresensing range of tactile sensors, the intrinsic viscoelasticity of soft polymeric materials remains a long-standing challenge resulting in cyclic hysteresis. This causes sensor data variations between contact events that negatively impact the accuracy and reliability. Here, we introduce the Tactile Resistive Annularly Cracked E-Skin (TRACE) sensor to address the inherent trade-off between sensitivity and hysteresis in tactile sensors when using soft materials. We discovered that piezoresistive sensors made using an array of three-dimensional (3D) metallic annular cracks on polymeric microstructures possess high sensitivities (> 10(7) Omega . kPa(-1)), low hysteresis (2.99 +/- 1.37%) over a wide pressure range (0-20 kPa), and fast response (400 Hz). We demonstrate that TRACE sensors can accurately detect and measure the pulse wave velocity (PWV) when skin mounted. Moreover, we show that these tactile sensors when arrayed enabled fast reliable one-touch surface texture classification with neuromorphic encoding and deep learning algorithms.
引用
收藏
页码:25352 / 25359
页数:8
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