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Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm
Sensor technologies have been core features for various wearable electronic products for decades. Their functions are expected to continue to play an essential role in future generations of wearable products. For example, trends in industrial, military, and security applications include smartwatches...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537244/ https://www.ncbi.nlm.nih.gov/pubmed/37763889 http://dx.doi.org/10.3390/mi14091726 |
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author | Vu, Chi Cuong Kim, Jooyong Nguyen, Thanh-Hai |
author_facet | Vu, Chi Cuong Kim, Jooyong Nguyen, Thanh-Hai |
author_sort | Vu, Chi Cuong |
collection | PubMed |
description | Sensor technologies have been core features for various wearable electronic products for decades. Their functions are expected to continue to play an essential role in future generations of wearable products. For example, trends in industrial, military, and security applications include smartwatches used for monitoring medical indicators, hearing devices with integrated sensor options, and electronic skins. However, many studies have focused on a specific area of the system, such as manufacturing processes, data analysis, or actual testing. This has led to challenges regarding the reliability, accuracy, or connectivity of components in the same wearable system. There is an urgent need for studies that consider the whole system to maximize the efficiency of soft sensors. This study proposes a method to fabricate a resistive pressure sensor with high sensitivity, resilience, and good strain tolerance for recognizing human motion or body signals. Herein, the sensor electrodes are shaped on a thin Pyralux film. A layer of microfiber polyesters, coated with carbon nanotubes, is used as the bearing and pressure sensing layer. Our sensor shows superior capabilities in respiratory monitoring. More specifically, the sensor can work in high-humidity environments, even when immersed in water—this is always a big challenge for conventional sensors. In addition, the embedded random forest model, built for the application to recognize restoration signals with high accuracy (up to 92%), helps to provide a better overview when placing flexible sensors in a practical system. |
format | Online Article Text |
id | pubmed-10537244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105372442023-09-29 Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm Vu, Chi Cuong Kim, Jooyong Nguyen, Thanh-Hai Micromachines (Basel) Article Sensor technologies have been core features for various wearable electronic products for decades. Their functions are expected to continue to play an essential role in future generations of wearable products. For example, trends in industrial, military, and security applications include smartwatches used for monitoring medical indicators, hearing devices with integrated sensor options, and electronic skins. However, many studies have focused on a specific area of the system, such as manufacturing processes, data analysis, or actual testing. This has led to challenges regarding the reliability, accuracy, or connectivity of components in the same wearable system. There is an urgent need for studies that consider the whole system to maximize the efficiency of soft sensors. This study proposes a method to fabricate a resistive pressure sensor with high sensitivity, resilience, and good strain tolerance for recognizing human motion or body signals. Herein, the sensor electrodes are shaped on a thin Pyralux film. A layer of microfiber polyesters, coated with carbon nanotubes, is used as the bearing and pressure sensing layer. Our sensor shows superior capabilities in respiratory monitoring. More specifically, the sensor can work in high-humidity environments, even when immersed in water—this is always a big challenge for conventional sensors. In addition, the embedded random forest model, built for the application to recognize restoration signals with high accuracy (up to 92%), helps to provide a better overview when placing flexible sensors in a practical system. MDPI 2023-09-01 /pmc/articles/PMC10537244/ /pubmed/37763889 http://dx.doi.org/10.3390/mi14091726 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vu, Chi Cuong Kim, Jooyong Nguyen, Thanh-Hai Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title | Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title_full | Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title_fullStr | Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title_full_unstemmed | Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title_short | Health Monitoring System from Pyralux Copper-Clad Laminate Film and Random Forest Algorithm |
title_sort | health monitoring system from pyralux copper-clad laminate film and random forest algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537244/ https://www.ncbi.nlm.nih.gov/pubmed/37763889 http://dx.doi.org/10.3390/mi14091726 |
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