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Special Issue "Wearable Electronic Sensors"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: 15 January 2021.

Special Issue Editor

Dr. Jaehong Lee
Website
Guest Editor
Affilication: Soft Biomedical Devices Lab, Department of Robotics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 42988 Daegu, Korea
Interests: stretchable electronics; fiber electronics; wearable sensors; implantable electronics; biomedical engineering; bioelectronics; biosensors

Special Issue Information

Dear Colleagues,

Wearable electronics, where electronic components or systems are integrated into wearable objects or directly used on the body, has been intensively explored for the last few decades. In particular, wearable sensors is one of the main parts of wearable electronics based on a variety of applications such as healthcare, activity tracking, sport, virtual reality, and environmental monitoring.

The present Special Issue reports recent advances in the multidisciplinary research of wearable sensors, including textile-based sensors, electronic skin, fiber electronic sensors, and various forms of wearable sensors. We look forward to and welcome your participation in this Special Issue. 

Dr. Jaehong Lee
Guest Editor

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 papers will be 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. Sensors is an international peer-reviewed open access semimonthly 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 2000 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

  • Wearable sensors;
  • Textile-based sensors;
  • Electronic skin;
  • Fiber electronic sensors;
  • Stretchable electronic sensors;
  • Wearable healthcare sensing;
  • Flexible wearable sensors.

Published Papers (4 papers)

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Research

Open AccessArticle
A Bluetooth-Low-Energy-Based Detection and Warning System for Vulnerable Road Users in the Blind Spot of Vehicles
Sensors 2020, 20(9), 2727; https://doi.org/10.3390/s20092727 - 11 May 2020
Abstract
Blind spot road accidents are a frequently occurring problem. Every year, several deaths are caused by this phenomenon, even though a lot of money is invested in raising awareness and in the development of prevention systems. In this paper, a blind spot detection [...] Read more.
Blind spot road accidents are a frequently occurring problem. Every year, several deaths are caused by this phenomenon, even though a lot of money is invested in raising awareness and in the development of prevention systems. In this paper, a blind spot detection and warning system is proposed, relying on Received Signal Strength Indicator (RSSI) measurements and Bluetooth Low Energy (BLE) wireless communication. The received RSSI samples are threshold-filtered, after which a weighted average is computed with a sliding window filter. The technique is validated by simulations and measurements. Finally, the strength of the proposed system is demonstrated with real-life measurements. Full article
(This article belongs to the Special Issue Wearable Electronic Sensors)
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Open AccessArticle
Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance
Sensors 2020, 20(5), 1530; https://doi.org/10.3390/s20051530 - 10 Mar 2020
Abstract
In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system [...] Read more.
In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system based on micro-inertial measurement units (MIMUs) installed on feet cannot effectively realize its positioning function when the body movement is too drastic to be measured correctly by commercial grade inertial sensors, a pedestrian navigation method based on construction of a virtual inertial measurement unit (VIMU) and gait feature assistance is proposed. The inertial data from different positions of pedestrians’ lower limbs are collected synchronously via actual IMUs as training samples. The nonlinear mapping relationship between inertial information from the human foot and leg is established by a visual geometry group-long short term memory (VGG-LSTM) neural network model, based on which the foot VIMU and virtual inertial navigation system (VINS) are constructed. The VINS experimental results show that, combined with zero-velocity update (ZUPT), the integrated method of error modification proposed in this paper can effectively reduce the accumulation of positioning errors in situations where the gait type exceeds the measurement range of the inertial sensors. The positioning performance of the proposed method is more accurate and stable in complex gait types than that merely using ZUPT. Full article
(This article belongs to the Special Issue Wearable Electronic Sensors)
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Open AccessArticle
Evaluation of Joint Motion Sensing Efficiency According to the Implementation Method of SWCNT-Coated Fabric Motion Sensor
Sensors 2020, 20(1), 284; https://doi.org/10.3390/s20010284 - 03 Jan 2020
Cited by 1
Abstract
The purpose of this study was to investigate the effects of the shape and attachment position of stretchable textile piezoresistive sensors coated with single-walled carbon nanotubes on their performance in measuring the joint movements of children. The requirements for fabric motion sensors suitable [...] Read more.
The purpose of this study was to investigate the effects of the shape and attachment position of stretchable textile piezoresistive sensors coated with single-walled carbon nanotubes on their performance in measuring the joint movements of children. The requirements for fabric motion sensors suitable for children are also identified. The child subjects were instructed to wear integrated clothing with sensors of different shapes (rectangular and boat-shaped), attachment positions (at the knee and elbow joints or 4 cm below the joints). The change in voltage caused by the elongation and contraction of the fabric sensors was measured for the flexion-extension motions of the arms and legs at 60°/s (three measurements of 10 repetitions each for the 60° and 90° angles, for a total of 60 repetitions). Their reliability was verified by analyzing the agreement between the fabric motion sensors and attached acceleration sensors. The experimental results showed that the fabric motion sensor that can measure children’s arm and leg motions most effectively is the rectangular-shaped sensor attached 4 cm below the joint. In this study, we developed a textile piezoresistive sensor suitable for measuring the joint motion of children, and analyzed the shape and attachment position of the sensor on clothing suitable for motion sensing. We showed that it is possible to sense joint motions of the human body by using flexible fabric sensors integrated into clothing. Full article
(This article belongs to the Special Issue Wearable Electronic Sensors)
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Open AccessArticle
Ultra-Low Power Wearable Infant Sleep Position Sensor
Sensors 2020, 20(1), 61; https://doi.org/10.3390/s20010061 - 20 Dec 2019
Abstract
Numerous wearable sensors have been developed for a variety of needs in medical/healthcare/wellness/sports applications, but there are still doubts about their usefulness due to uncomfortable fit or frequent battery charging. Because the size or capacity of battery is the major factor affecting the [...] Read more.
Numerous wearable sensors have been developed for a variety of needs in medical/healthcare/wellness/sports applications, but there are still doubts about their usefulness due to uncomfortable fit or frequent battery charging. Because the size or capacity of battery is the major factor affecting the convenience of wearable sensors, power consumption must be reduced. We developed a method that can significantly reduce the power consumption by introducing a signal repeater and a special switch that provides power only when needed. Antenna radiation characteristics are an important factor in wireless wearable sensors, but soft material encapsulation for comfortable fit results in poor wireless performance. We improved the antenna radiation characteristics by a local encapsulation patterning. In particular, ultra-low power operation enables the use of paper battery to achieve a very thin and flexible form factor. Also, we verified the human body safety through specific absorption rate simulations. With these methods, we demonstrated a wearable infant sleep position sensor. Infants are unable to call for help in unsafe situations, and it is not easy for caregivers to observe them all the time. Our wearable sensor detects infants’ sleep positions in real time and automatically alerts the caregivers when needed. Full article
(This article belongs to the Special Issue Wearable Electronic Sensors)
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