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Special Issue "Wearable Sensors and Systems in the IOT"

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

Deadline for manuscript submissions: closed (15 December 2019).

Special Issue Editors

Prof. Dr. Subhas Mukhopadhyay
Website
Guest Editor
School of Engineering, Macquarie University, NSW, 2109, Australia
Interests: sensors and sensing technology; instrumentation; wireless sensor networks; Internet of Things; mechatronics and robotics
Special Issues and Collections in MDPI journals
Prof. Dr. Nagender Kumar Suryadevara
Website
Guest Editor
Associate Professor, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, India
Interests: wireless sensor networks; Internet of Things; real-time data mining
Dr. Anindya Nag
Website
Guest Editor
School of Engineering, Macquarie University, NSW 2109, Australia
Interests: fabrication and implementation of printed sensors, manoparticle-based flexible sensors, biosensors; sensors for different applications, smart sensors and sensing technology, sensor applications; strain sensing

Special Issue Information

Dear Colleagues,

Wearable smart devices are now widely used to determine various physical parameters at any point in time. The proliferation of such devices has been driven by the acceptance of enhanced technology by the general public. Despite the exponential growth in wearable sensors, they have limitations, especially regarding the broader aspects of their commercialized use, that need to be rectified to further enhance the field of wearable electronics.

Consideration of the Internet of Things (IoT), which connects smart objects around the world, has increased predominantly over the last two decades. By 2020, it is estimated that there will be over 50 billion IoT-connected devices, thus provoking questions regarding security and big data handling. This Special Issue aims at presenting the issues and challenges faced by the currently-proposed IoT-based systems along with state-of-the-art research on the commercialisation of current systems.

The topics of interest for this issue include:

  1. Wearable sensors
  2. Flexible sensing systems
  3. Flexible devices
  4. Sensing technologies
  5. Measurement of physiological parameters
  6. Autonomous wearable sensors
  7. Textile-based wearable sensors
  8. Printed electronics
  9. Wearable IoT based systems
  10. Energy harvesting
  11. Energy efficient wearable systems
  12. Health care wearable sensing
  13. Integrated wearable sensors
  14. Multifunctional wearable sensing systems
  15. IoT-based systems
  16. Security in IoT-based systems
  17. Heterogenous IoT-based systems
  18. Big data handling in IoT-based systems
  19. Smart homes and cities
  20. Visualisation techniques
  21. Artificial Intelligence algorithms
  22. Hardware Architecture for IoT-based systems
  23. Data processing in IoT
  24. Wireless energy harvesting
  25. Cloud computing in IoT-based systems

Prof. Dr. Subhas Mukhopadhyay
Dr. Nagender K. Suryadevara
Dr. Anindya Nag
Guest Edtiors

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 2200 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.

Published Papers (15 papers)

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Research

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Open AccessArticle
Medication Adherence and Liquid Level Tracking System for Healthcare Provider Feedback
Sensors 2020, 20(8), 2435; https://doi.org/10.3390/s20082435 - 24 Apr 2020
Abstract
A common problem for healthcare providers is accurately tracking patients’ adherence to medication and providing real-time feedback on the management of their medication regimen. This is a particular problem for eye drop medications, as the current commercially available monitors focus on measuring adherence [...] Read more.
A common problem for healthcare providers is accurately tracking patients’ adherence to medication and providing real-time feedback on the management of their medication regimen. This is a particular problem for eye drop medications, as the current commercially available monitors focus on measuring adherence to pills, and not to eye drops. This work presents an intelligent bottle sleeve that slides onto a prescription eye drop medication bottle. The intelligent sleeve is capable of detecting eye drop use, measuring fluid level, and sending use information to a healthcare team to facilitate intervention. The electronics embedded into the sleeve measure fluid level, dropper orientation, the state of the dropper top (on/off), and rates of angular motion during an application. The sleeve was tested with ten patients (age ≥65) and successfully identified and timestamped 94% of use events. On-board processing enabled event detection and the measurement of fluid levels at a 0.4 mL resolution. These data were communicated to the healthcare team using Bluetooth and Wi-Fi in real-time, enabling rapid feedback to the subject. The healthcare team can therefore monitor a log of medication use behavior to make informed decisions on treatment or support for the patient. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
A Wristwatch-Based Wireless Sensor Platform for IoT Health Monitoring Applications
Sensors 2020, 20(6), 1675; https://doi.org/10.3390/s20061675 - 17 Mar 2020
Cited by 3
Abstract
A wristwatch-based wireless sensor platform for IoT wearable health monitoring applications is presented. The paper describes the platform in detail, with a particular focus given to the design of a novel and compact wireless sub-system for 868 MHz wristwatch applications. An example application [...] Read more.
A wristwatch-based wireless sensor platform for IoT wearable health monitoring applications is presented. The paper describes the platform in detail, with a particular focus given to the design of a novel and compact wireless sub-system for 868 MHz wristwatch applications. An example application using the developed platform is discussed for arterial oxygen saturation (SpO2) and heart rate measurement using optical photoplethysmography (PPG). A comparison of the wireless performance in the 868 MHz and the 2.45 GHz bands is performed. Another contribution of this work is the development of a highly integrated 868 MHz antenna. The antenna structure is printed on the surface of a wristwatch enclosure using laser direct structuring (LDS) technology. At 868 MHz, a low specific absorption rate (SAR) of less than 0.1% of the maximum permissible limit in the simulation is demonstrated. The measured on-body prototype antenna exhibits a −10 dB impedance bandwidth of 36 MHz, a peak realized gain of −4.86 dBi and a radiation efficiency of 14.53% at 868 MHz. To evaluate the performance of the developed 868 MHz sensor platform, the wireless communication range measurements are performed in an indoor environment and compared with a commercial Bluetooth wristwatch device. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
A Flexible Strain Sensor Based on the Porous Structure of a Carbon Black/Carbon Nanotube Conducting Network for Human Motion Detection
Sensors 2020, 20(4), 1154; https://doi.org/10.3390/s20041154 - 20 Feb 2020
Cited by 8Correction
Abstract
High-performance flexible strain sensors are playing an increasingly important role in wearable electronics, such as human motion detection and health monitoring, with broad application prospects. This study developed a flexible resistance strain sensor with a porous structure composed of carbon black and multi-walled [...] Read more.
High-performance flexible strain sensors are playing an increasingly important role in wearable electronics, such as human motion detection and health monitoring, with broad application prospects. This study developed a flexible resistance strain sensor with a porous structure composed of carbon black and multi-walled carbon nanotubes. A simple and low-cost spraying method for the surface of a porous polydimethylsiloxane substrate was used to form a layer of synergized conductive networks built by carbon black and multi-walled carbon nanotubes. By combining the advantages of the synergetic effects of mixed carbon black and carbon nanotubes and their porous polydimethylsiloxane structure, the performance of the sensor was improved. The results show that the sensor has a high sensitivity (GF) (up to 61.82), a wide strain range (0%–130%), a good linearity, and a high stability. Based on the excellent performance of the sensor, the flexible strain designed sensor was installed successfully on different joints of the human body, allowing for the monitoring of human movement and human respiratory changes. These results indicate that the sensor has promising potential for applications in human motion monitoring and physiological activity monitoring. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Automatic Classification of Squat Posture Using Inertial Sensors: Deep Learning Approach
Sensors 2020, 20(2), 361; https://doi.org/10.3390/s20020361 - 08 Jan 2020
Cited by 3
Abstract
Without expert coaching, inexperienced exercisers performing core exercises, such as squats, are subject to an increased risk of spinal or knee injuries. Although it is theoretically possible to measure the kinematics of body segments and classify exercise forms with wearable sensors and algorithms, [...] Read more.
Without expert coaching, inexperienced exercisers performing core exercises, such as squats, are subject to an increased risk of spinal or knee injuries. Although it is theoretically possible to measure the kinematics of body segments and classify exercise forms with wearable sensors and algorithms, the current implementations are not sufficiently accurate. In this study, the squat posture classification performance of deep learning was compared to that of conventional machine learning. Additionally, the location for the optimal placement of sensors was determined. Accelerometer and gyroscope data were collected from 39 healthy participants using five inertial measurement units (IMUs) attached to the left thigh, right thigh, left calf, right calf, and lumbar region. Each participant performed six repetitions of an acceptable squat and five incorrect forms of squats that are typically observed in inexperienced exercisers. The accuracies of squat posture classification obtained using conventional machine learning and deep learning were compared. Each result was obtained using one IMU or a combination of two or five IMUs. When employing five IMUs, the accuracy of squat posture classification using conventional machine learning was 75.4%, whereas the accuracy using deep learning was 91.7%. When employing two IMUs, the highest accuracy (88.7%) was obtained using deep learning for a combination of IMUs on the right thigh and right calf. The single IMU yielded the best results on the right thigh, with an accuracy of 58.7% for conventional machine learning and 80.9% for deep learning. Overall, the results obtained using deep learning were superior to those obtained using conventional machine learning for both single and multiple IMUs. With regard to the convenience of use in self-fitness, the most feasible strategy was to utilize a single IMU on the right thigh. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU
Sensors 2020, 20(2), 344; https://doi.org/10.3390/s20020344 - 07 Jan 2020
Cited by 7
Abstract
Wearable indoor localization can now find applications in a wide spectrum of fields, including the care of children and the elderly, sports motion analysis, rehabilitation medicine, robotics navigation, etc. Conventional inertial measurement unit (IMU)-based position estimation and radio signal indoor localization methods based [...] Read more.
Wearable indoor localization can now find applications in a wide spectrum of fields, including the care of children and the elderly, sports motion analysis, rehabilitation medicine, robotics navigation, etc. Conventional inertial measurement unit (IMU)-based position estimation and radio signal indoor localization methods based on WiFi, Bluetooth, ultra-wide band (UWB), and radio frequency identification (RFID) all have their limitations regarding cost, accuracy, or usability, and a combination of the techniques has been considered a promising way to improve the accuracy. This investigation aims to provide a cost-effective wearable sensing solution with data fusion algorithms for indoor localization and real-time motion analysis. The main contributions of this investigation are: (1) the design of a wireless, battery-powered, and light-weight wearable sensing device integrating a low-cost UWB module-DWM1000 and micro-electromechanical system (MEMS) IMU-MPU9250 for synchronized measurement; (2) the implementation of a Mahony complementary filter for noise cancellation and attitude calculation, and quaternions for frame rotation to obtain the continuous attitude for displacement estimation; (3) the development of a data fusion model integrating the IMU and UWB data to enhance the measurement accuracy using Kalman-filter-based time-domain iterative compensations; and (4) evaluation of the developed sensor module by comparing it with UWB- and IMU-only solutions. The test results demonstrate that the average error of the integrated module reached 7.58 cm for an arbitrary walking path, which outperformed the IMU- and UWB-only localization solutions. The module could recognize lateral roll rotations during normal walking, which could be potentially used for abnormal gait recognition. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Hydrophobic Paper-Based SERS Sensor Using Gold Nanoparticles Arranged on Graphene Oxide Flakes
Sensors 2019, 19(24), 5471; https://doi.org/10.3390/s19245471 - 11 Dec 2019
Cited by 5
Abstract
Paper-based surface-enhanced Raman scattering (SERS) sensors have garnered much attention in the past decade owing to their ubiquity, ease of fabrication, and environmentally friendly substrate. The main drawbacks of a paper substrate for a SERS sensor are its high porosity, inherent hygroscopic nature, [...] Read more.
Paper-based surface-enhanced Raman scattering (SERS) sensors have garnered much attention in the past decade owing to their ubiquity, ease of fabrication, and environmentally friendly substrate. The main drawbacks of a paper substrate for a SERS sensor are its high porosity, inherent hygroscopic nature, and hydrophilic surface property, which reduce the sensitivity and reproducibility of the SERS sensor. Here, we propose a simple, quick, convenient, and economical method for hydrophilic to hydrophobic surface modification of paper, while enhancing its mechanical and moisture-resistant properties. The hydrophobic paper (h-paper) was obtained by spin-coating diluted polydimethylsiloxane (PDMS) solution onto the filter paper, resulting in h-paper with an increased contact angle of up to ≈130°. To complete the h-paper-based SERS substrate, gold nanoparticles arranged on graphene oxide ([email protected]) were synthesized using UV photoreduction, followed by drop-casting of [email protected] solution on the h-paper substrate. The enhancement of the SERS signal was then assessed by attaching a rhodamine 6G (R6G) molecule as a Raman probe material to the h-paper-based SERS substrate. The limit of detection was 10 nM with an R2 of 0.966. The presented SERS sensor was also tested to detect a thiram at the micromolar level. We expect that our proposed [email protected]/h-paper-based SERS sensor could be applied to point-of-care diagnostics applications in daily life and in spacecraft. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
WaistonBelt X: A Belt-Type Wearable Device with Sensing and Intervention Toward Health Behavior Change
Sensors 2019, 19(20), 4600; https://doi.org/10.3390/s19204600 - 22 Oct 2019
Cited by 2
Abstract
Changing behavior related to improper lifestyle habits has attracted attention as a solution to prevent lifestyle diseases, such as diabetes, heart disease, arteriosclerosis, and stroke. To drive health behavior changes, wearable devices are needed, and they must not only provide accurate sensing and [...] Read more.
Changing behavior related to improper lifestyle habits has attracted attention as a solution to prevent lifestyle diseases, such as diabetes, heart disease, arteriosclerosis, and stroke. To drive health behavior changes, wearable devices are needed, and they must not only provide accurate sensing and visualization functions but also effective intervention functions. In this paper, we propose a health support system, WaistonBelt X, that consists of a belt-type wearable device with sensing and intervention functions and a smartphone application. WaistonBelt X can automatically measure a waistline with a magnetometer that detects the movements of a blade installed in the buckle, and monitor the basic activities of daily living with inertial sensors. Furthermore, WaistonBelt X intervenes with the user to correct lifestyle habits by using a built-in vibrator. Through evaluation experiments, we confirmed that our proposed device achieves measurement of the circumference on the belt position (mean absolute error of 0.93 cm) and basic activity recognition (F1 score of 0.95) with high accuracy. In addition, we confirmed that the intervention via belt vibration effectively improves the sitting posture of the user. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Wellness Assessment of Alzheimer’s Patients in an Instrumented Health-Care Facility
Sensors 2019, 19(17), 3658; https://doi.org/10.3390/s19173658 - 22 Aug 2019
Cited by 1
Abstract
Wellness assessment refers to the evaluation of physical, mental, and social well-being. This work explores the possibility of applying technological tools to assist clinicians and professionals to improve the quality of life of people through continuous monitoring of their wellness. The contribution of [...] Read more.
Wellness assessment refers to the evaluation of physical, mental, and social well-being. This work explores the possibility of applying technological tools to assist clinicians and professionals to improve the quality of life of people through continuous monitoring of their wellness. The contribution of this paper is manifold: a coarse-grained localization system is responsible for monitoring and collecting data related to patients, while a novel wellness assessment methodology is proposed to extract quantitative indicators related to the well-being of patients from the collected data. The proposed system has been installed at “Il Paese Ritrovato", an innovative health-care facility for Alzheimer’s in Monza, Italy; first satisfactory results have been obtained, and the dataset shows great potential for several applications. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
A Wide-Range, Wireless Wearable Inertial Motion Sensing System for Capturing Fast Athletic Biomechanics in Overhead Pitching
Sensors 2019, 19(17), 3637; https://doi.org/10.3390/s19173637 - 21 Aug 2019
Cited by 10
Abstract
The standard technology used to capture motion for biomechanical analysis in sports has employed marker-based optical systems. While these systems are excellent at providing positional information, they suffer from a limited ability to accurately provide fundamental quantities such as velocity and acceleration (hence [...] Read more.
The standard technology used to capture motion for biomechanical analysis in sports has employed marker-based optical systems. While these systems are excellent at providing positional information, they suffer from a limited ability to accurately provide fundamental quantities such as velocity and acceleration (hence forces and torques) during high-speed motion typical of many sports. Conventional optical systems require considerable setup time, can exhibit sensitivity to extraneous light, and generally sample too slowly to accurately capture extreme bursts of athletic activity. In recent years, wireless wearable sensors have begun to penetrate devices used in sports performance assessment, offering potential solutions to these limitations. This article, after determining pressing problems in sports that such sensors could solve and surveying the state-of-the-art in wearable motion capture for sports, presents a wearable dual-range inertial and magnetic sensor platform that we developed to enable an end-to-end investigation of high-level, very wide dynamic-range biomechanical parameters. We tested our system on collegiate and elite baseball pitchers, and have derived and measured metrics to glean insight into performance-relevant motion. As this was, we believe, the first ultra-wide-range wireless multipoint and multimodal inertial and magnetic sensor array to be used on elite baseball pitchers, we trace its development, present some of our results, and discuss limitations in accuracy from factors such as soft-tissue artifacts encountered with extreme motion. In addition, we discuss new metric opportunities brought by our systems that may be relevant for the assessment of micro-trauma in baseball. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Multifunctional Flexible Sensor Based on Laser-Induced Graphene
Sensors 2019, 19(16), 3477; https://doi.org/10.3390/s19163477 - 09 Aug 2019
Cited by 8
Abstract
The paper presents the design and fabrication of a low-cost and easy-to-fabricate laser-induced graphene sensor together with its implementation for multi-sensing applications. Laser-irradiation of commercial polymer film was applied for photo-thermal generation of graphene. The graphene patterned in an interdigitated shape was transferred [...] Read more.
The paper presents the design and fabrication of a low-cost and easy-to-fabricate laser-induced graphene sensor together with its implementation for multi-sensing applications. Laser-irradiation of commercial polymer film was applied for photo-thermal generation of graphene. The graphene patterned in an interdigitated shape was transferred onto Kapton sticky tape to form the electrodes of a capacitive sensor. The functionality of the sensor was validated by employing them in electrochemical and strain-sensing scenarios. Impedance spectroscopy was applied to investigate the response of the sensor. For the electrochemical sensing, different concentrations of sodium sulfate were prepared, and the fabricated sensor was used to detect the concentration differences. For the strain sensing, the sensor was deployed for monitoring of human joint movements and tactile sensing. The promising sensing results validating the applicability of the fabricated sensor for multiple sensing purposes are presented. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Zirconia-Based Ultra-Thin Compact Flexible CPW-Fed Slot Antenna for IoT
Sensors 2019, 19(14), 3134; https://doi.org/10.3390/s19143134 - 16 Jul 2019
Cited by 4
Abstract
An ultra-thin compact flexible CPW-fed slot monopole antenna suitable for the Internet of Things (IoT) applications was achieved as a result of exploring the use of Zirconia-based ENrG’s Thin E-Strate® for the antenna’s design. The electromagnetic characterization of the novel material at [...] Read more.
An ultra-thin compact flexible CPW-fed slot monopole antenna suitable for the Internet of Things (IoT) applications was achieved as a result of exploring the use of Zirconia-based ENrG’s Thin E-Strate® for the antenna’s design. The electromagnetic characterization of the novel material at the frequency range of interest was analyzed. A comparison was made concerning the required dimensions and the simulation results regarding impedance matching and radiation properties, for three different dielectric substrates: Novel flexible ceramic (ENrG’s Thin E-Strate), rigid Arlon 25N, and flexible Polypropylene (PP). Two different metallization techniques—electrotextile-based and inkjet printing—were used in the fabrication of prototypes based on ENrG’s Thin E-Strate. Return losses measured results for the fabricated prototypes with both procedures was compared, as well as with simulation. The best prototype on the ENrG’s Thin E-Strate was compared with one on Arlon 25N, in terms of radiation properties in an anechoic chamber, and conclusions were drawn. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things
Sensors 2019, 19(13), 2985; https://doi.org/10.3390/s19132985 - 06 Jul 2019
Cited by 5
Abstract
Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data [...] Read more.
Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique—steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Open AccessArticle
Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
Sensors 2019, 19(7), 1528; https://doi.org/10.3390/s19071528 - 29 Mar 2019
Abstract
We can benefit from various services with context recognition using wearable sensors. In this study, we focus on the contexts acquired from sensor data in the nostrils. Nostrils can provide various contexts on breathing, nasal congestion, and higher level contexts including psychological and [...] Read more.
We can benefit from various services with context recognition using wearable sensors. In this study, we focus on the contexts acquired from sensor data in the nostrils. Nostrils can provide various contexts on breathing, nasal congestion, and higher level contexts including psychological and health states. In this paper, we propose a context recognition method using the information in the nostril. We develop a system to acquire the temperature in the nostrils using small temperature sensors connected to glasses. As a result of the evaluations, the proposed system can detect breathing correctly, workload at an accuracy of 96.4%, six behaviors at an accuracy of 54%, and eight behaviors in daily life at an accuracy of 86%. Moreover, the proposed system can detect nasal congestion, therefore, it can log nasal cycles that are considered to have a relationship with the autonomic nerves and/or biological states. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Review

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Open AccessReview
Recent Advances in Fabrication Methods for Flexible Antennas in Wearable Devices: State of the Art
Sensors 2019, 19(10), 2312; https://doi.org/10.3390/s19102312 - 19 May 2019
Cited by 24
Abstract
Antennas are a vital component of the wireless body sensor networks devices. A wearable antenna in this system can be used as a communication component or energy harvester. This paper presents a detailed review to recent advances fabrication methods for flexible antennas. Such [...] Read more.
Antennas are a vital component of the wireless body sensor networks devices. A wearable antenna in this system can be used as a communication component or energy harvester. This paper presents a detailed review to recent advances fabrication methods for flexible antennas. Such antennas, for any applications in wireless body sensor networks, have specific considerations such as flexibility, conformability, robustness, and ease of integration, as opposed to conventional antennas. In recent years, intriguing approaches have demonstrated antennas embroidered on fabrics, encapsulated in polymer composites, printed using inkjets on flexible laminates and a 3-D printer and, more interestingly, by injecting liquid metal in microchannels. This article presents an operational perspective of such advanced approaches and beyond, while analyzing the strengths and limitations of each in the microwave as well as millimeter-wave regions. Navigating through recent developments in each area, mechanical and electrical constitutive parameters are reviewed, and finally, some open challenges are presented as well for future research directions. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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Other

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Open AccessCorrection
Correction: Zhang, P., et al. A Flexible Strain Sensor Based on the Porous Structure of a Carbon Black/Carbon Nanotube Conducting Network for Human Motion Detection. Sensors 2020, 20, 1154
Sensors 2020, 20(10), 2901; https://doi.org/10.3390/s20102901 - 20 May 2020
Abstract
The authors wish to make the following corrections to this paper [...] Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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