Self-Powered Dual-Mode Hydrogel Sensors for Respiratory Monitoring via Humidity Sensing and Strain Detection

Reliance on external power sources remains a significant constraint for the practical deployment of flexible sensors. Herein, we develop a multifunctional hydrogel-based sensor that operates in two distinct modes: a self-powered mode for humidity sensing and a resistance mode for strain detection. The sensor is built around a conductive poly(vinyl alcohol)-graphene oxide/lithium bromide (PVA-GO/LiBr) hydrogel, fabricated via a straightforward one-step process. This core material exhibits a high ionic conductivity of 0.33 S·cm–1. In its self-powered humidity-sensing mode, the device leverages a metal–air redox reaction, where moisture-triggered ion mobility generates a current output with a sensitivity of 0.299 nA/s per % RH in the 70% to 90% RH range. Simultaneously, the intrinsic resistance of the very same hydrogel structure serves as a highly responsive strain gauge, capable of achieving a 6-fold increase in resistance at 400% tensile strain. Demonstrating robust performance even at −15 °C, the sensor is integrated into a respiratory monitoring platform. It successfully enables the real-time detection of abnormal breathing patterns, such as sleep apnea hypopnea syndrome (SAHS), showcasing its potential as a scalable and power-efficient solution for advanced wearable health diagnostics and telemedicine.

Authors

Institutions

Publication Details

Journal
ACS Applied Electronic Materials
Published
2025-12-23
DOI
https://doi.org/10.1021/acsaelm.5c02209
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

Self-Powered Dual-Mode Hydrogel Sensors for Respiratory Monitoring via Humidity Sensing and Strain Detection

esmaeil heydari, Lihui Huang, Yongjie Yu, Gongxun Bai et al.
ACS Applied Electronic Materials
Advanced Sensor and Energy Harvesting Materials
article

Self-Powered Dual-Mode Hydrogel Sensors for Respiratory Monitoring via Humidity Sensing and Strain Detection

esmaeil heydari, Lihui Huang, Yongjie Yu, Gongxun Bai, Xinna Zhang, Yueyang Xu, Nan Lin
article en

Abstract

Reliance on external power sources remains a significant constraint for the practical deployment of flexible sensors. Herein, we develop a multifunctional hydrogel-based sensor that operates in two distinct modes: a self-powered mode for humidity sensing and a resistance mode for strain detection. The sensor is built around a conductive poly(vinyl alcohol)-graphene oxide/lithium bromide (PVA-GO/LiBr) hydrogel, fabricated via a straightforward one-step process. This core material exhibits a high ionic conductivity of 0.33 S·cm–1. In its self-powered humidity-sensing mode, the device leverages a metal–air redox reaction, where moisture-triggered ion mobility generates a current output with a sensitivity of 0.299 nA/s per % RH in the 70% to 90% RH range. Simultaneously, the intrinsic resistance of the very same hydrogel structure serves as a highly responsive strain gauge, capable of achieving a 6-fold increase in resistance at 400% tensile strain. Demonstrating robust performance even at −15 °C, the sensor is integrated into a respiratory monitoring platform. It successfully enables the real-time detection of abnormal breathing patterns, such as sleep apnea hypopnea syndrome (SAHS), showcasing its potential as a scalable and power-efficient solution for advanced wearable health diagnostics and telemedicine.

ACS Applied Electronic MaterialsVol. 8(1)
Kharazmi University (IR), College of Medical Sciences (NP), NeoPhotonics (United States) (US), Modern College of Business and Science (OM), China Jiliang University (CN), Optica (US)
Affordable and clean energy
Openalex Percentile: Top 43%
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.