Satellite-Based Sensor for Environmental Heat-Stress Sweat Creatinine Monitoring: The Remote Artificial Intelligence-Assisted Epidermal Wearable Sensing for Health Evaluation
Abstract
Wearable human sweat sensors have offered a great prospect in epidermal detection for self-monitoring and health evaluation. These on-body epidermal sensors can be integrated with the Internet of Things (IoT) as augmented diagnostics tools for telehealth applications, especially for noninvasive health monitoring without using blood contents. One of many great benefits in utilizing sweat as biofluid is the capability of instantaneously continuous diagnosis during normal day-to-day activities. Here, we revealed a textile-based sweat sensor selective for perspired creatinine that is prepared by coating poly(vinyl alcohol) (PVA)-Cu 2+ -poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) and cuprous oxide nanoparticles on stretchable nylon, is equipped with heart rate monitoring and a satellite-communication device to locate wearers, and incorporates machine learning to predict the levels of environmental heat stress. Electrochemical impedance spectroscopy (EIS) was used to investigate different charge-transfer resistances of PVA and PEDOT:PSS with cuprous and cuprite ions induced by single-chain and ionic cross-linking. Furthermore, density function theory (DFT) studies predicted the catalytic binding of sweat creatinine with the sensing materials that occurred at thiophene rings. The hybrid sensor successfully achieved 96.3% selectivity efficacy toward the determination of creatinine contents from 0.4 to 960 μM in the presence of interfering species of glucose, urea, uric acid, and NaCl as well as retained 92.1% selectivity efficacy in the existence of unspecified human sweat interference. Ultimately, the hand-grip portable device can offer the great benefit of continuous health monitoring and provide the location of any wearer. This augmented telemedicine sensor may represent the first remote low-cost and artificial-intelligence-based sensing device selective for heat-stress sweat creatinine.
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Sweat stress biomarkers, such as creatinine, could be correlated with human heat stress using a neural network algorithm in which a multimodal sensor could monitor the stress creatinine in sweat and the heart rate and predict the stress intensity occupied by mental states.
“However, it was shown recently that sweat stress biomarkers, such as creatinine, could be correlated with human heat stress using a neural network algorithm in which a multimodal sensor could monitor the stress creatinine in sweat and the heart rate and predict the stress intensity occupied by mental states [235].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [235]
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The emergence of AI-based wearable sensors for digital health technology: a review
Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works
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- Authors
- Kalasin, S., Sangnuang, P., & Surareungchai, W.
- Affiliations
- King Mongkut's University of Technology Thonburi (TH)
- Corresponding author
- Kalasin, Surachate
- Venue
- ACS Biomaterials Science & Engineering
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-12-23
- Volume
- 7
- Issue
- 1
- Pages
- 322-334
- ISSN
- 2373-9878 (ISSN-L)
- OpenAlex
- W3116534048
- Cited by
- 57
- References
- 58
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 9 · 2023: 19 · 2022: 7 · 2021: 5
- FWCI
- 2.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- ACS Biomaterials Science & Engineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science and Technology Development Agency
- Ministry of Science and Technology of Thailand
- Asahi Glass Foundation
- Thailand Research Fund (MRG 6280176)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- wearable sensors, epidermal sensors, environmental heat stress, copper oxide nanoparticles, PEDOT:PSS, polyvinyl alcohol, electrochemical impedance spectroscopy, density functional theory, machine learning, telemedicine, heart rate monitoring, satellite communication, continuous health monitoring, non-invasive diagnosis
- MeSH terms
- Wearable Electronic Devices, Artificial Intelligence, Creatinine, Humans, Sweat, Heat-Shock Response
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