Advanced Polymer Materials for Stretchable Electronics

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D:Materials and Processing".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 2947

Special Issue Editor


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Guest Editor
Department of Chemical and Materials Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan
Interests: stretchable electronics; organic materials; nano materials; carbon nanotube transistor

Special Issue Information

Dear colleagues,

Electronic skins are emerging technologies that based on stretchable electronics and related integrated circuits. They have great potential in a broad range of applications such as prosthetics, artificial intelligence, soft robotics and health monitoring. In the development of stretchable electronics, polymeric materials have played important roles due to their intrinsic flexibility, which can help devices to dissipate externally applied strain, and maintain the performance during deformation. Moreover, their electrical and mechanical properties, which are critical to stretchable electronics, could be further improved through chemical modification or physical blend. The advancement of polymers can promote the fields, evolve the stretchable devices, make electronic skin more like human skin. Accordingly, this Special Issue seeks to showcase research papers, communications, and review articles that focus on polymeric materials used in stretchable electronics. The scope covers all the relevant topics, including:

  • Advanced polymers for the applications of stretchable transistors, memories, and smart displays.
  • Advanced polymers for stretchable energy storage applications, deformable solar cells, supercapacitors, and batteries.
  • Advanced polymers for stretchable sensor developments, pressure sensors, temperature sensors, photo sensors, and chemical sensors.
  • Advanced polymers for stretchable bioelectronics, human–machine interface, implantable devices, and health care systems.

Dr. Chien-Chung Shih
Guest Editor

Manuscript Submission Information

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Keywords

  • stretchable polymers
  • stretchable transistors
  • stretchable memories
  • smart displays
  • stretchable energy storage devices
  • stretchable sensors

Published Papers (1 paper)

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Review

17 pages, 3248 KiB  
Review
Research Progress of ECG Monitoring Equipment and Algorithms Based on Polymer Materials
by Lvheng Zhang and Jihong Liu
Micromachines 2021, 12(11), 1282; https://doi.org/10.3390/mi12111282 - 20 Oct 2021
Cited by 3 | Viewed by 2210
Abstract
Heart diseases such as myocardial ischemia (MI) are the main causes of human death. The prediction of MI and arrhythmia is an effective method for the early detection, diagnosis, and treatment of heart disease. For the rapid detection of arrhythmia and myocardial ischemia, [...] Read more.
Heart diseases such as myocardial ischemia (MI) are the main causes of human death. The prediction of MI and arrhythmia is an effective method for the early detection, diagnosis, and treatment of heart disease. For the rapid detection of arrhythmia and myocardial ischemia, the electrocardiogram (ECG) is widely used in clinical diagnosis, and its detection equipment and algorithm are constantly optimized. This paper introduces the current progress of portable ECG monitoring equipment, including the use of polymer material sensors and the use of deep learning algorithms. First, it introduces the latest portable ECG monitoring equipment and the polymer material sensor it uses and then focuses on reviewing the progress of detection algorithms. We mainly introduce the basic structure of existing deep learning methods and enumerate the internationally recognized ECG datasets. This paper outlines the deep learning algorithms used for ECG diagnosis, compares the prediction results of different classifiers, and summarizes two existing problems of ECG detection technology: imbalance of categories and high computational overhead. Finally, we put forward the development direction of using generative adversarial networks (GAN) to improve the quality of the ECG database and lightweight ECG diagnosis algorithm to adapt to portable ECG monitoring equipment. Full article
(This article belongs to the Special Issue Advanced Polymer Materials for Stretchable Electronics)
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