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Hierarchical conducting networks constructed as resistive strain sensors for personal healthcare monitoring and robotic arm control.

Authors :
Lin, Huijuan
Wang, Jia
Cao, Wei
Wang, Huinan
Rui, Kun
Yan, Yan
Zhu, Jixin
Source :
Chemical Engineering Journal. Jun2024, Vol. 490, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

[Display omitted] • CB/CNT hybrids and elastic TPU are combined to assemble resistive strain sensor. • The hierarchical conductive network endows the sensor with desirable sensing capabilities. • CB/CNT@TPU strain sensor shows great application in personalized health monitoring. • Multiple sensors are integrated for robotic arm control by capturing human motions. Flexible strain sensors are strongly demanded in fields of personal healthcare monitoring and human–machine interface, as they can accurately perceive external action to produce electrical output signals. Aiming at the existing problems, such as the balanced sensitivity and sensing range, durability as well as expanded application, this paper proposes a flexible strain sensor prepared based on electrospun thermoplastic polyurethane (TPU) membrane, followed by anchoring mixed conductive materials (carbon black (CB)/carbon nanotubes (CNT)) on its surface via an effective ultrasonic-assisted method. The resulting CB/CNT@TPU strain sensor delivers a desirable integration of sensing performances: good sensitivity, wide work range, fast response speed (<150 ms) and reliable cyclic stability (5000 cycles). Ascribed to the sensing behavior and additional breathability, strain sensor can be applied well to monitor human health, including human joints movements (fingers and wrists) and physiological signals (pulse and laryngeal vibration recognition). Finally, a multiaxial robotic arm control system is constructed, which provides a feasible strategy for intelligent robotic arms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13858947
Volume :
490
Database :
Academic Search Index
Journal :
Chemical Engineering Journal
Publication Type :
Academic Journal
Accession number :
177419931
Full Text :
https://doi.org/10.1016/j.cej.2024.151840