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Microfluidic-Integrated Multimodal Wearable Hybrid Patch for Wireless and Continuous Physiological Monitoring.

Authors :
Zahed MA
Kim DK
Jeong SH
Selim Reza M
Sharifuzzaman M
Pradhan GB
Song H
Asaduzzaman M
Park JY
Source :
ACS sensors [ACS Sens] 2023 Aug 25; Vol. 8 (8), pp. 2960-2974. Date of Electronic Publication: 2023 Jul 27.
Publication Year :
2023

Abstract

Despite extensive advances in wearable monitoring systems, most designs focus on the detection of physical parameters or metabolites and do not consider the integration of microfluidic channels, miniaturization, and multimodality. In this study, a combination of multimodal (biochemical and electrophysiological) biosensing and microfluidic channel-integrated patch-based wireless systems is designed and fabricated using flexible materials for improved wearability, ease of operation, and real-time and continuous monitoring. The reduced graphene oxide-based microfluidic channel-integrated glucose biosensor exhibits a good sensitivity of 19.97 (44.56 without fluidic channels) μA mM <superscript>-1</superscript> cm <superscript>-2</superscript> within physiological levels (10 μM-0.4 mM) with good long-term and bending stability. All the sensors in the patch are initially validated using sauna gown sweat-based on-body and real-time tests with five separate individuals who perspired three times each. Multimodal glucose and electrocardiogram (ECG) sensing, along with their real-time adjustment based on sweat pH and temperature fluctuations, optimize sensing accuracy. Laser-burned hierarchical MXene-polyvinylidene fluoride-based conductive carbon nanofiber-based dry ECG electrodes exhibit low skin contact impedance (40.5 kΩ cm <superscript>2</superscript> ) and high-quality electrophysiological signals (signal-to-noise ratios = 23.4-32.8 dB). The developed system is utilized to accurately and wirelessly monitor the sweat glucose and ECG of a human subject engaged in physical exercise in real time.

Details

Language :
English
ISSN :
2379-3694
Volume :
8
Issue :
8
Database :
MEDLINE
Journal :
ACS sensors
Publication Type :
Academic Journal
Accession number :
37498214
Full Text :
https://doi.org/10.1021/acssensors.3c00148