Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.0
Journals
Micromachines
Special Issues
Flexible Electronics for Physiological Signal Monitoring
share announcement

Flexible Electronics for Physiological Signal Monitoring

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 22134

Special Issue Editors

Dr. Ningqi Luo

E-Mail Website
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

E-Mail Website
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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

15 pages, 812 KiB  
Article
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 9 | Viewed by 2271
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 [...] Read more.
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)
►▼ Show Figures

Figure 1

11 pages, 2458 KiB  
Article
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 - 1 Jul 2021
Cited by 15 | Viewed by 3746
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 [...] Read more.
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)
►▼ Show Figures

Figure 1

Review

Jump to: Research

29 pages, 1982 KiB  
Review
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 25 | Viewed by 6666
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 [...] Read more.
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)
►▼ Show Figures

Figure 1

14 pages, 2634 KiB  
Review
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 86 | Viewed by 7872
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, [...] Read more.
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)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop