Wearable Flexible Triboelectric Sensor Array for a Self-Powered Infant Care System

Infant falls during critical developmental stages present severe injury risks due to immature motor control and undetectable trauma hazards. Existing monitoring solutions face limitations in detection accuracy, real-time response, and wearability, necessitating reliable monitoring solutions. This study introduces a wearable triboelectric sensor array (WTSA) for infant collision detection. The device integrates a flexible 3 × 3 array of polydimethylsiloxane (PDMS) hemispherical protrusions mounted on an Ecoflex substrate with copper electrodes. Structural deformation during impact generates triboelectric signals through contact electrification and electrostatic induction. The WTSA demonstrated high sensitivity, with voltage output scaling from -2 V at 0.5 g to -17 V at 3 g and exceptional stability during extended operation exceeding 48 h. It serves dual functions as an accelerometer and self-powered sensor, achieving approximately 42.5 nW peak power output and successfully charging capacitors to 2.8 V. Crucially, impact location identification exceeded 93.6% accuracy using a convolutional neural network (CNN) trained on voltage waveforms from all nine sensor units. Its flexible design ensures comfortable, nondisruptive wear during infant activities. By enabling real-time, precise assessment of collision dynamics and injury risk through machine learning, the WTSA provides a robust, self-powered solution for enhancing infant safety during critical developmental stages.

Authors

Institutions

Publication Details

Journal
ACS Omega
Published
2025-12-04
DOI
https://doi.org/10.1021/acsomega.5c08776
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wearable Flexible Triboelectric Sensor Array for a Self-Powered Infant Care System

L.L. Chen, Jiahui Shi, L. Ruan, Yong Wang et al.
ACS Omega
Advanced Sensor and Energy Harvesting Materials
article

Wearable Flexible Triboelectric Sensor Array for a Self-Powered Infant Care System

L.L. Chen, Jiahui Shi, L. Ruan, Yong Wang, Minzhu Zheng
article en

Abstract

Infant falls during critical developmental stages present severe injury risks due to immature motor control and undetectable trauma hazards. Existing monitoring solutions face limitations in detection accuracy, real-time response, and wearability, necessitating reliable monitoring solutions. This study introduces a wearable triboelectric sensor array (WTSA) for infant collision detection. The device integrates a flexible 3 × 3 array of polydimethylsiloxane (PDMS) hemispherical protrusions mounted on an Ecoflex substrate with copper electrodes. Structural deformation during impact generates triboelectric signals through contact electrification and electrostatic induction. The WTSA demonstrated high sensitivity, with voltage output scaling from -2 V at 0.5 g to -17 V at 3 g and exceptional stability during extended operation exceeding 48 h. It serves dual functions as an accelerometer and self-powered sensor, achieving approximately 42.5 nW peak power output and successfully charging capacitors to 2.8 V. Crucially, impact location identification exceeded 93.6% accuracy using a convolutional neural network (CNN) trained on voltage waveforms from all nine sensor units. Its flexible design ensures comfortable, nondisruptive wear during infant activities. By enabling real-time, precise assessment of collision dynamics and injury risk through machine learning, the WTSA provides a robust, self-powered solution for enhancing infant safety during critical developmental stages.

ACS OmegaVol. 10(49)
City University (BD), Hangzhou Women’s Hospital (CN), Kindeva Drug Delivery (United States) (US), Hangzhou City University
Openalex Percentile: Top 62%
Advanced Sensor and Energy Harvesting Materials
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.