Journal
ACS BIOMATERIALS SCIENCE & ENGINEERING
Volume 7, Issue 1, Pages 322-334Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsbiomaterials.0c01459
Keywords
telemedicine sensor; wearable sensor; sweat creatinine; machine learning; heat stress
Categories
Funding
- Thailand Research Fund (TRF), Research Network of Nanotec (RNN) program of the National Nanotechnology Center (NANOTEC), NSTDA [MRG 6280176]
- Ministry of Science and Technology, Thailand
- Asahi Glass Foundation 2019 grant, Japan
Ask authors/readers for more resources
The research developed a textile-based sweat sensor for detecting perspired creatinine, integrated with heart rate monitoring, satellite communication, and machine learning. The sensor exhibited high selectivity and efficacy in continuous monitoring, suitable for health diagnostics and environmental heat stress prediction.
Wearable human sweat sensors have offered a great prospect in epidermal detection for self-monitoring and health evaluation. These onbody 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)-Cu2+-poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) and cuprous oxide nanoparticles on stretchable nylon, is equipped with heart rate monitoring and a satellitecommunication 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 mu M 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available