Back to Search Start Over

Oriented Alginate-Poly(vinyl alcohol) Electrospun Nanofibers for Multimodal Sensing and Gesture Language Recognition.

Authors :
Fu Y
Yang C
Tian Y
Zhang B
Wan Z
Zhang K
Wang S
Jiang G
Liu W
Wei R
Source :
ACS applied materials & interfaces [ACS Appl Mater Interfaces] 2024 Nov 06; Vol. 16 (44), pp. 61381-61394. Date of Electronic Publication: 2024 Oct 28.
Publication Year :
2024

Abstract

Flexible nanofiber sensors have gained substantial attention in extending application scenarios owing to their desirable lightweight, comfort, and breathability. Nevertheless, disorder and uneven dimension issues of nanofibers are the leading concerns in their multifunctional response, which often leads to erratic response signals as well as poor linearity. In this work, a high-performance oriented nanofiber film with a three-dimensional network consisting of alginate sodium, poly(vinyl alcohol), and poly(ethylene oxide) was successfully fabricated by a controllable directional electrospinning technique. The main properties of the nanofibers are capable of being regulated intentionally by varying the electrospinning temperature, collector rotation speed, and polymer concentrations. Based on the favorable structure orientation, the nanofiber film displays satisfied biodegradability and high mechanical strength (575.1 MPa). Being integrated with modified magnetic particles, the sensors not only display a fast response speed, high magnetic sensitivity, and exceptional recoverability in response to magnetic fields but also show favorable sensitivities and reliable long-term durability under mechanical excitations. As a wearable sensor, it can accurately perceive the physiological signals generated by the human body in real-time. Furthermore, with the assistance of a convolutional neural network model, a gesture language recognition system is developed by integrating multiple sensors to realize a high recognition accuracy (∼99.08%). This study provides a feasible strategy to manufacture high-performance multimodal sensors for wearable human-machine interaction applications.

Details

Language :
English
ISSN :
1944-8252
Volume :
16
Issue :
44
Database :
MEDLINE
Journal :
ACS applied materials & interfaces
Publication Type :
Academic Journal
Accession number :
39468763
Full Text :
https://doi.org/10.1021/acsami.4c16421