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Flexible Electronics for Physiological Signal Monitoring

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A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 16636

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Special Issue Editors

Dr. Ningqi Luo

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Guest Editor

1. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong
2. Intelligent Sensing Limited, Hong Kong
Interests: flexible pressure sensors; physiological signal monitoring; vital signs analysis

Dr. Guodong Zhou

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Guest Editor

Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong
Interests: photodetectors; field-effect transistors; flexible electronics; biomedical sensors/systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

While the landscape of biomedical devices has been altered toward compactness and wearability, flexible electronics for physiological signal monitoring have been extensively researched in recent years. Multivariate sensing systems consisting of sensor modules, packaging and connections, and signal processing circuits have been developed to achieve high-quality acquisition of physiological signals such as electrocardiograms, photoplethysmograms, and epidermal blood pressure waves.

To provide an in-depth overview and facilitate the interdisciplinary research effort in this field, for this Special Issue, we encourage authors to submit research papers and review articles in the following topics:

Material or structure design that renders high-performance flexible sensors;
Sensing system design that provides solution or optimization for existing issues;
Algorithm development that improves signal quality and feature extraction accuracy;
Theoretical modeling of the sensor mechanism or physiological process.

Looking forward to your contribution!

Dr. Ningqi Luo
Dr. Guodong Zhou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Flexible electronics
Wearable devices
Physiological signal monitoring
Pressure sensors
Photoplethysmogram sensors
Electrocardiogram sensors
Heart rate measurement
Heart rate variability measurement
Pulse oximetry measurement
Respiration measurement
Blood pressure measurement

Published Papers (4 papers)

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Research

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15 pages, 812 KiB

Open AccessArticle

A Portable Sign Language Collection and Translation Platform with Smart Watches Using a BLSTM-Based Multi-Feature Framework

by Zhenxing Zhou, Vincent W. L. Tam and Edmund Y. Lam

Micromachines 2022, 13(2), 333; https://doi.org/10.3390/mi13020333 - 20 Feb 2022

Cited by 8 | Viewed by 1740

Abstract

Continuous sign language recognition (CSLR) using different types of sensors to precisely recognize sign language in real time is a very challenging but important research direction in sensor technology. Many previous methods are vision-based, with computationally intensive algorithms to process a large number of image/video frames possibly contaminated with noises, which can result in a large translation delay. On the other hand, gesture-based CSLR relying on hand movement data captured on wearable devices may require less computation resources and translation time. Thus, it is more efficient to provide instant translation during real-world communication. However, the insufficient amount of information provided by the wearable sensors often affect the overall performance of this system. To tackle this issue, we propose a bidirectional long short-term memory (BLSTM)-based multi-feature framework for conducting gesture-based CSLR precisely with two smart watches. In this framework, multiple sets of input features are extracted from the collected gesture data to provide a diverse spectrum of valuable information to the underlying BLSTM model for CSLR. To demonstrate the effectiveness of the proposed framework, we test it on an extremely challenging and radically new dataset of Hong Kong sign language (HKSL), in which hand movement data are collected from 6 individual signers for 50 different sentences. The experimental results reveal that the proposed framework attains a much lower word error rate compared with other existing machine learning or deep learning approaches for gesture-based CSLR. Based on this framework, we further propose a portable sign language collection and translation platform, which can simplify the procedure of collecting gesture-based sign language dataset and recognize sign language through smart watch data in real time, in order to break the communication barrier for the sign language users. Full article

(This article belongs to the Special Issue Flexible Electronics for Physiological Signal Monitoring)

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11 pages, 2458 KiB

Open AccessArticle

An Ultra-Stretchable Sensitive Hydrogel Sensor for Human Motion and Pulse Monitoring

by Bin Shen, Jiang Li, Yongtao Tang, Huihua Xu and Fengyu Li

Micromachines 2021, 12(7), 789; https://doi.org/10.3390/mi12070789 - 01 Jul 2021

Cited by 12 | Viewed by 3051

Abstract

Ionic hydrogels with intrinsic conductivity and stretchability show great potential in flexible electronics. However, it remains a great challenge to achieve hydrogels with mechanical stretchability, ionic conductivity, optical transparency, and a self-healing ability at the same time. In this paper, we developed a hydroxyethylidene diphosphonic acid (HEDP) assisted poly(vinyl alcohol) (PVA) composite hydrogel to achieve high-performance stretch-sensitive sensor. Through a facile freeze–thaw strategy, the hydrogel could achieve large stretchability (up to 950% strain), good conductivity (10.88 S/m), excellent linear sensitivity (GF = 2.72, within 100% strain), high transparency, and significant self-healing ability. The PVA-HEDP hydrogel-based strain sensor is capable of monitoring various human movements from small scale (e.g., laryngeal vibration while speaking) to large scale (e.g., knee joint movement). Moreover, the multisite sensor array is capable of detecting the subtle differences between the pulse wave features from Cun, Guan and Chi positions, mimicking the three-finger palpation in Traditional Chinese Medicine. This work demonstrates that the composite hydrogel-based flexible sensor provides a promising solution for multifunctional human activities and health monitoring. Full article

(This article belongs to the Special Issue Flexible Electronics for Physiological Signal Monitoring)

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Review

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29 pages, 1982 KiB

Open AccessReview

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

by Roberto De Fazio, Veronica Mattei, Bassam Al-Naami, Massimo De Vittorio and Paolo Visconti

Micromachines 2022, 13(8), 1335; https://doi.org/10.3390/mi13081335 - 17 Aug 2022

Cited by 15 | Viewed by 4564

Abstract

Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep’s functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG—electroencephalography, ECG—electrocardiography, EMG—electromyography, EOG—electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems. Full article

(This article belongs to the Special Issue Flexible Electronics for Physiological Signal Monitoring)

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14 pages, 2634 KiB

Open AccessReview

Applications of Graphene-Based Materials in Sensors: A Review

by Jihong Liu, Siyu Bao and Xinzhe Wang

Micromachines 2022, 13(2), 184; https://doi.org/10.3390/mi13020184 - 26 Jan 2022

Cited by 51 | Viewed by 5835

Abstract

With the research and the development of graphene-based materials, new sensors based on graphene compound materials are of great significance to scientific research and the consumer market. However, in the past ten years, due to the requirements of sensor accuracy, reliability, and durability, the development of new graphene sensors still faces many challenges in the future. Due to the special structure of graphene, the obtained characteristics can meet the requirements of high-performance sensors. Therefore, graphene materials have been applied in many innovative sensor materials in recent years. This paper introduces the important role and specific examples of sensors based on graphene and its base materials in biomedicine, photoelectrochemistry, flexible pressure, and other fields in recent years, and it puts forward the difficulties encountered in the application of graphene materials in sensors. Finally, the development direction of graphene sensors has been prospected. For the past two years of the COVID-19 epidemic, the detection of the virus sensor has been investigated. These new graphene sensors can complete signal detection based on accuracy and reliability, which provides a reference for researchers to select and manufacture sensor materials. Full article

(This article belongs to the Special Issue Flexible Electronics for Physiological Signal Monitoring)

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