Design and Application of a Novel Gesture-Sensing Skeleton Integrated With CNF/CB/Ecoflex Sensors

In recent years, flexible sensors have garnered substantial attention within the domain of gesture recognition and human-computer interaction. This study introduces the development of a gesture-sensing skeleton conductive composite elastic sensor (CCES) incorporating cellulose nanofiber (CNF)/CB/Ecoflex-30 sensors, achieved through a streamlined design approach. The sensor layer of a single finger ring within this skeleton employs Ecoflex-30 as its substrate and a blend of CNF/CB/Ecoflex-30 as the conductive filler. The incorporation of CNF notably augments the sensing stability of the sensor. A trigger layer embedded with six hemispherical protrusions is integrated within the finger ring mold, enhancing the sensor’s sensitivity significantly. An elastic steel bar positioned beneath the trigger layer of each finger ring allows for actuation through joint bending, thereby compressing the ring and altering the sensor resistance. This flexible and lightweight design strategy facilitates easy wearability on the hand, while the elastic steel bar serves as the skeletal framework, simplifying the system architecture. Experimental outcomes reveal that the skeleton exhibits rapid response/reply times (0.6/0.2 s), a broad dynamic range (1–16 N), and superior linearity (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}^{{2}} \gt 0.97$ </tex-math></inline-formula>). These attributes enable precise detection of hand movements and underscore its potential in pioneering next-generation human-computer interaction and artificial intelligence technologies.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-01-27
DOI
https://doi.org/10.1109/jsen.2025.3531387
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Design and Application of a Novel Gesture-Sensing Skeleton Integrated With CNF/CB/Ecoflex Sensors

Guanran Wang, Yonggeng Wei, Yong Shi, M.Y. Zhang et al.
IEEE Sensors Journal
Hand Gesture Recognition Systems
article

Design and Application of a Novel Gesture-Sensing Skeleton Integrated With CNF/CB/Ecoflex Sensors

Guanran Wang, Yonggeng Wei, Yong Shi, M.Y. Zhang, Hao Li, Xin Mao
article en

Abstract

In recent years, flexible sensors have garnered substantial attention within the domain of gesture recognition and human-computer interaction. This study introduces the development of a gesture-sensing skeleton conductive composite elastic sensor (CCES) incorporating cellulose nanofiber (CNF)/CB/Ecoflex-30 sensors, achieved through a streamlined design approach. The sensor layer of a single finger ring within this skeleton employs Ecoflex-30 as its substrate and a blend of CNF/CB/Ecoflex-30 as the conductive filler. The incorporation of CNF notably augments the sensing stability of the sensor. A trigger layer embedded with six hemispherical protrusions is integrated within the finger ring mold, enhancing the sensor’s sensitivity significantly. An elastic steel bar positioned beneath the trigger layer of each finger ring allows for actuation through joint bending, thereby compressing the ring and altering the sensor resistance. This flexible and lightweight design strategy facilitates easy wearability on the hand, while the elastic steel bar serves as the skeletal framework, simplifying the system architecture. Experimental outcomes reveal that the skeleton exhibits rapid response/reply times (0.6/0.2 s), a broad dynamic range (1–16 N), and superior linearity (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}^{{2}} \gt 0.97$ </tex-math></inline-formula>). These attributes enable precise detection of hand movements and underscore its potential in pioneering next-generation human-computer interaction and artificial intelligence technologies.

IEEE Sensors JournalVol. 25(5)
Harbin University of Science and Technology (CN), Heilongjiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 99%
Hand Gesture Recognition Systems
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