TY - JOUR
T1 - MXene-based pressure sensor with ultrahigh sensitivity in a small pressure range for voiceless speaking and abnormal writing recognition
AU - Du, Yuzhang
AU - Lu, Wenxuan
AU - Liu, Yichen
AU - Yu, Rui
AU - Wu, Panzhen
AU - Kong, Jie
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
PY - 2024/2
Y1 - 2024/2
N2 - Language and characters contain rich information and play an important role in daily communication. Although flexible pressure sensors have aroused extensive attention in information interaction, the application in the special groups who characterized with “voiceless” and/or “dysgraphia” cannot normally speak and/or write is usually ignored. Herein, a high-performance flexible pressure sensor was proposed to learn the expression content from special groups through recognizing the voiceless speaking and abnormal writing. Thanks for the enhanced interfacial interactions and air gaps constructed in device, the as-prepared sensor possesses ultrahigh sensitivity in a small pressure range (S = 45.95 kPa−1, P < 1 kPa) and exhibits an outstanding sensitivity to the slight pressure resulted from voice and writing. In addition, high stability, good flexibility, short response time of 123 ms, and excellent durability over 2000 cycles are also achieved. As the voice and writing detector, it can accurately recognize different voice signals and character stroke order. Importantly, by comparing with the electrical signals obtained under normal speaking and writing conditions, the real expression content from the special groups can be well acquired. This high-performance pressure sensor, along with its unique structure designing, is expected to be widely used in human − computer interaction, health monitoring, and soft robotics.
AB - Language and characters contain rich information and play an important role in daily communication. Although flexible pressure sensors have aroused extensive attention in information interaction, the application in the special groups who characterized with “voiceless” and/or “dysgraphia” cannot normally speak and/or write is usually ignored. Herein, a high-performance flexible pressure sensor was proposed to learn the expression content from special groups through recognizing the voiceless speaking and abnormal writing. Thanks for the enhanced interfacial interactions and air gaps constructed in device, the as-prepared sensor possesses ultrahigh sensitivity in a small pressure range (S = 45.95 kPa−1, P < 1 kPa) and exhibits an outstanding sensitivity to the slight pressure resulted from voice and writing. In addition, high stability, good flexibility, short response time of 123 ms, and excellent durability over 2000 cycles are also achieved. As the voice and writing detector, it can accurately recognize different voice signals and character stroke order. Importantly, by comparing with the electrical signals obtained under normal speaking and writing conditions, the real expression content from the special groups can be well acquired. This high-performance pressure sensor, along with its unique structure designing, is expected to be widely used in human − computer interaction, health monitoring, and soft robotics.
KW - Dysgraphia
KW - MXene
KW - Pressure sensors
KW - Voice recognition
KW - Voiceless
KW - Writing recognition
UR - http://www.scopus.com/inward/record.url?scp=85183331069&partnerID=8YFLogxK
U2 - 10.1007/s42114-024-00838-1
DO - 10.1007/s42114-024-00838-1
M3 - 文章
AN - SCOPUS:85183331069
SN - 2522-0128
VL - 7
JO - Advanced Composites and Hybrid Materials
JF - Advanced Composites and Hybrid Materials
IS - 1
M1 - 24
ER -