Flexible Non-contact Electrodes for Bioelectrical Signal Monitoring

Liu, Shuting; Liu, Xueyu; Jiang, Yanbing; Wang, Xin; Huang, Pingao; Wang, Hui; Zhu, Mingxing; Tan, Jingqian; Li, Peng; Chen, Lin; Zhang, Guanghe; Chen, Shixiong; Li, Guanglin

doi:10.1109/embc.2018.8513306

Cited by 12 publications

(10 citation statements)

References 17 publications

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“…To solve this problem, the team of Liu et al [ 14 ] made a flexible printed circuit (FPC) flexible circular electrode with a diameter of 2.5 cm, without components on both sides. The flexible non-contact electrode is connected with the main PCB board by using the soft shielded cable.…”

Section: Bioelectric Signal Monitoringmentioning

confidence: 99%

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

Liu

Bai

et al. 2020

Sensors

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With the development of flexible electronic materials, as well as the wide development and application of smartphones, the cloud, and wireless systems, flexible wearable sensor technology has a significant and far-reaching impact on the realization of personalized medical care and the reform of the consumer market in the future. However, due to the high requirements for accuracy, reliability, low power consumption, and less data error, the development of these potential areas is full of challenges. In order to solve these problems, this review mainly searches the literature from 2008 to May 2020, based on the PRISMA process. Based on them, this paper reviews the latest research progress of new flexible materials and different types of sensors for monitoring vital signs (including electrophysiological signals, body temperature, and respiratory frequency) in recent years. These materials and sensors can help realize accurate signal detection based on comfortable and sustainable observation, and may likely be applied to future daily clothing.

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Section: Bioelectric Signal Monitoringmentioning

confidence: 99%

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

Liu

Bai

et al. 2020

Sensors

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“…Zhang et al [23] confirmed that their polymer composite electrodes are as effective as Ag/AgCl electrodes in measuring ECG signals and have excellent scalability. In the direction of non-contact sensors and implantable sensors, flexible electrodes using composite materials have achieved new breakthroughs in signal quality [24,25]. Figure 3 shows the shape of the ECG sensor of different types of materials [26][27][28].…”

Section: Polymer Materials Sensormentioning

confidence: 99%

Research Progress of ECG Monitoring Equipment and Algorithms Based on Polymer Materials

Zhang

Liu

2021

Micromachines

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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.

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“…Input parameters: iteration number, code length, population size, Temperature profile t ' [1,1000], ⃗ a[−1.5, 1.5], social forces S() = [0, 1.5], movement limit m = 2, control parameters F [2,3], L[1. 5,2].…”

Section: Ta B L E 1 Proposed Algorithmmentioning

confidence: 99%

“…Electrocardiography (ECG) signals are broadly used in clinical uses and health checking, and they function as the target pointers firmly identified with human health . The electrical activities of the heart for certain time interval are represented by ECG, which have significant reference value to represent the fundamental function of the heart and its analytical examination.…”

Section: Introductionmentioning

confidence: 99%

EPOWT: A denoising technique of the electrocardiography signal transmission via 5G wireless communications

Bhuyar¹,

Kureshi

2019

Trans Emerging Tel Tech

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This article provides a thorough review of 5G wireless electrocardiography (ECG) communication for actual cardiac signal using both technical and clinical features for the purpose of recommending real‐time observation. Major issue regarding this frame work is the distortion and smoothness of ECG signal for the cardiologist advice also it needs correct diagnosis at the proper time. Extensive 5G wireless simulated scenarios are used to supervise the compressed ECG signal on reception. An efficient ECG transmission protocol is a modern and consistent ECG transmission protocol which is used to retransmit the noise signals. Thus, we are filtering the ECG signals to improve the quality which may directly affects the medical diagnosis. Because, time and frequency indicators can be obtained by the wavelet analysis but majority of the error functions cannot be flexible to various signals because of the static transition curve of threshold. Hence, we proposed a new emperor penguin optimization (EPO) together with wavelet thresholding (EPOWT) method. Here, the EPOWT is estimated through the means of real‐time ECG records. The outcomes of filtering process shows that the proposed EPOWT approach can achieve smooth threshold transition and soft thresholding bring the wavelet coefficient. EPOEPO algorithm is used to improve its flexibility to different signals. The EPOWT can generate an essential noise‐free signal by balancing the smoothness and signal distortion filtering for transmission. The proposed method can attains 2.9 seconds delay during simulation. Thus, the 5G wireless channel parameter's functioning zone is simple to acquire.

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Flexible Non-contact Electrodes for Bioelectrical Signal Monitoring

Cited by 12 publications

References 17 publications

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

Research Progress of ECG Monitoring Equipment and Algorithms Based on Polymer Materials

EPOWT: A denoising technique of the electrocardiography signal transmission via 5G wireless communications

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