TY - JOUR
T1 - Bioinspired Monopolar Controlled Ionic Hydrogels for Flexible Non-Contact Human–Machine Interfaces
AU - Wu, Wenlong
AU - Jiang, Tianyi
AU - Wang, Min
AU - Li, Tong
AU - Song, Yuxin
AU - Liu, Jun
AU - Wang, Zuankai
AU - Jiang, Hongyuan
PY - 2024/11/26
Y1 - 2024/11/26
N2 - Most flexible human–machine interfaces emulate the tactile system of the skin, which has the risk of contact damage. Additionally, contact deformation often leads to a hysteresis response. Non-contact interaction can address these problems. Inspired by the electroreception capabilities of the elephantnose fish, this study introduces a non-contact sensing model employing monopolar controlled ionic hydrogel. Compared to most existing mutual capacitive non-contact sensing models, this model not only boosts responsivity by over 3.5 times but also streamlines the sensing architecture. Utilizing this sensing model, a flexible non-contact human–machine interface is developed by organizing three differently shaped hydrogels into an asymmetric configuration. This device reliably discerns six non-contact gestures using machine learning algorithms and supports at least eleven interactive functions by detecting the duration of gestures, enabling continuous real-time control over external devices. This advancement heralds a more liberated paradigm of human–machine interaction with promising implications for the Internet of Things. © 2024 Wiley-VCH GmbH.
AB - Most flexible human–machine interfaces emulate the tactile system of the skin, which has the risk of contact damage. Additionally, contact deformation often leads to a hysteresis response. Non-contact interaction can address these problems. Inspired by the electroreception capabilities of the elephantnose fish, this study introduces a non-contact sensing model employing monopolar controlled ionic hydrogel. Compared to most existing mutual capacitive non-contact sensing models, this model not only boosts responsivity by over 3.5 times but also streamlines the sensing architecture. Utilizing this sensing model, a flexible non-contact human–machine interface is developed by organizing three differently shaped hydrogels into an asymmetric configuration. This device reliably discerns six non-contact gestures using machine learning algorithms and supports at least eleven interactive functions by detecting the duration of gestures, enabling continuous real-time control over external devices. This advancement heralds a more liberated paradigm of human–machine interaction with promising implications for the Internet of Things. © 2024 Wiley-VCH GmbH.
KW - flexible sensor
KW - human–machine interface
KW - ionic hydrogel
KW - nature inspired engineering
KW - non-contact gesture recognition
UR - http://www.scopus.com/inward/record.url?scp=85201148094&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85201148094&origin=recordpage
U2 - 10.1002/adfm.202408338
DO - 10.1002/adfm.202408338
M3 - RGC 21 - Publication in refereed journal
SN - 1616-301X
VL - 34
JO - Advanced Functional Materials
JF - Advanced Functional Materials
IS - 48
M1 - 2408338
ER -