Wearable Self‐Powered Pressure Sensors Based on alk‐Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> Regulating Contact Barrier Difference for Noncontact Motion Object Recognition

Wearable self-powered pressure sensors present tremendous potential for object recognition. However, the fluctuated approach speed and distance may compromise the device output, thus affecting the recognition accuracy. Herein, a wearable self-powered pressure sensor with high sensitivity (1.48 V kPa<sup>-1</sup>), high output (130.5V), and high permeability (259.98 mm s<sup>-1</sup>) are developed where the contact barrier difference and triboelectric charge density of the triboelectric layer surface are dynamically regulated by modulating the surface groups resulting in a lower dielectric loss and higher output. The sensor leverages the polarity difference between the target object and the sensitive material to generate electrical signals at different speeds and distances through an electrostatic induction mechanism. With the assistance of the Transformer model with a self-attention mechanism, an average recognition accuracy of 94.3% is achieved by acquiring sensing signals at different speeds and distances. Simulating the ability of human vision, enables visually impaired people to acclimate to their surroundings more easily and independently and provides a critical advancement in the assistance of the blind with daily life.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2025-02-07
DOI
https://doi.org/10.1002/advs.202416504
Citations
8
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
5.39

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wearable Self‐Powered Pressure Sensors Based on alk‐Ti3C2Tx Regulating Contact Barrier Difference for Noncontact Motion Object Recognition

Quan Jin, Xiaoteng Jia, Shixiang Sun, Peng Sun et al.
8 citations
Advanced Science
Advanced Sensor and Energy Harvesting Materials
5.39
article

Wearable Self‐Powered Pressure Sensors Based on alk‐Ti3C2Tx Regulating Contact Barrier Difference for Noncontact Motion Object Recognition

Quan Jin, Xiaoteng Jia, Shixiang Sun, Peng Sun, Qi Pu, Geyu Lu, Yanan Xiao, Xiaolong Wang, Chenxing Wang, Bin Wang
article en
8 citations

Abstract

Wearable self-powered pressure sensors present tremendous potential for object recognition. However, the fluctuated approach speed and distance may compromise the device output, thus affecting the recognition accuracy. Herein, a wearable self-powered pressure sensor with high sensitivity (1.48 V kPa<sup>-1</sup>), high output (130.5V), and high permeability (259.98 mm s<sup>-1</sup>) are developed where the contact barrier difference and triboelectric charge density of the triboelectric layer surface are dynamically regulated by modulating the surface groups resulting in a lower dielectric loss and higher output. The sensor leverages the polarity difference between the target object and the sensitive material to generate electrical signals at different speeds and distances through an electrostatic induction mechanism. With the assistance of the Transformer model with a self-attention mechanism, an average recognition accuracy of 94.3% is achieved by acquiring sensing signals at different speeds and distances. Simulating the ability of human vision, enables visually impaired people to acclimate to their surroundings more easily and independently and provides a critical advancement in the assistance of the blind with daily life.

Advanced ScienceVol. 12(13)
Jilin University (CN), State Key Laboratory on Integrated Optoelectronics (CN), Jilin International Studies University (CN)
National Natural Science Foundation of China, People's Government of Jilin Province, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 5%
Advanced Sensor and Energy Harvesting Materials
5.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.