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Smart Sensors for Wearable Applications
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Smart Sensors for Wearable Applications

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 33611

Special Issue Editors

Dr. Andrea Pilotto

E-Mail Website
Guest Editor
Dipartimento di Scienze Cliniche e Sperimentali, University of Brescia, 25121 Brescia, Italy
Interests: digital markers of neurological disease; gait and movement mobile health technologies; optic sensors; cognitive digital assessment; interfaces between sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Joanna Nassar

E-Mail Website
Guest Editor
Bao Group, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
Interests: flexible electronics; wearable devices; electronic skin; CMOS devices; Sensors; Internet of Things; biomedical devices

Special Issue Information

Dear Colleagues,

The evolution of the Internet of Things (IoT) has enabled the emergence of compact and conformal devices that could be embedded in individual bodies, revolutionizing the way we interact with the world and augmenting our quality of life. These devices are known as smart wearable or mobile health technology devices. They come in different form factors of body-worn objects, such as watches, glasses, clothing, and even tattoo-like patches using advanced developments in the area of flexible/stretchable electronics. The diversity and innovation of new materials, form factor, and design as well as the integration of information coming from different smart sensors is key to expanding the potential of the application of mobile health technology. Applications are limitless and span the fields of environmental monitoring, prosthetics & robotics, healthcare and wellness, biomedical systems, ocean health study, fitness tracking, sports and wellness, mobile gaming, etc.

This Special Issue is intended to report recent advances in the multidisciplinary field of wearable sensing technologies. Articles will address topics that include smart sensors, wearable sensing technologies, smart textiles, smart materials, implantable sensors, flexible and stretchable sensors, energy harvesting in wearables, as well as low-power data acquisition and data transmission in support of smart sensors in Internet of Things applications. A discussion on the challenges and gaps that still remain to achieve desired characteristics and performance from wearable sensors is desired. We aim to report innovation in research but also help clarify necessary steps still needed for practical translation to the hands of the consumer.

Dr. Andrea Pilotto
Dr. Joanna Nassar
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. 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 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

  • Mobile health technology
  • Wearable technology
  • Smart sensors
  • Flexible and stretchable sensors
  • Optic sensors
  • Integrative mobile technology
  • Clinical and imaging correlation of digital data
  • E-skin
  • Healthcare and wellness
  • Internet of Things (IoT)
  • Environmental Monitoring
  • Robotics
  • Mobile gaming
  • Brain mapping

Published Papers (6 papers)

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Research

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14 pages, 5299 KiB  
Article
Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
by Surya A. Singaraju, Dennis D. Weller, Thurid S. Gspann, Jasmin Aghassi-Hagmann and Mehdi B. Tahoori
Sensors 2022, 22(11), 4000; https://doi.org/10.3390/s22114000 - 25 May 2022
Cited by 3 | Viewed by 2160
Abstract
Printed electronic devices have demonstrated their applicability in complex electronic circuits. There is recent progress in the realization of neuromorphic computing systems (NCSs) to implement basic synaptic functions using solution-processed materials. However, a fully printed neuron is yet to be realised. We demonstrate [...] Read more.
Printed electronic devices have demonstrated their applicability in complex electronic circuits. There is recent progress in the realization of neuromorphic computing systems (NCSs) to implement basic synaptic functions using solution-processed materials. However, a fully printed neuron is yet to be realised. We demonstrate a fully printed artificial neuromorphic circuit on flexible polyimide (PI) substrate. Characteristic features of individual components of the printed system were guided by the software training of the NCS. The printing process employs graphene ink for passive structures and In2O3 as active material to print a two-input artificial neuron on PI. To ensure a small area footprint, the thickness of graphene film is tuned to target a resistance and to obtain conductors or resistors. The sheet resistance of the graphene film annealed at 300 °C can be adjusted between 200 Ω and 500 kΩ depending on the number of printed layers. The fully printed devices withstand a minimum of 2% tensile strain for at least 200 cycles of applied stress without any crack formation. The area usage of the printed two-input neuron is 16.25 mm2, with a power consumption of 37.7 mW, a propagation delay of 1 s, and a voltage supply of 2 V, which renders the device a promising candidate for future applications in smart wearable sensors. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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15 pages, 4065 KiB  
Article
Applying Noncontact Sensing Technology in the Customized Product Design of Smart Clothes Based on Anthropometry
by I-Jan Wang, Wei-Ting Chang, Wen-Hao Wu and Bor-Shyh Lin
Sensors 2021, 21(23), 7978; https://doi.org/10.3390/s21237978 - 29 Nov 2021
Cited by 5 | Viewed by 2305
Abstract
Electrocardiograms (ECGs) provide important information for diagnosing cardiovascular diseases. In clinical practice, the conventional Ag/AgCl electrode is generally used; however, it is not suitable for long-term ECG measurement because of the risk of allergic reactions on the skin and the dying issue of [...] Read more.
Electrocardiograms (ECGs) provide important information for diagnosing cardiovascular diseases. In clinical practice, the conventional Ag/AgCl electrode is generally used; however, it is not suitable for long-term ECG measurement because of the risk of allergic reactions on the skin and the dying issue of electrolytic gels. In previous studies, several dry electrodes have been proposed to address these issues. However, most dry electrodes, which are the mode of conductive materials, have to contact the skin well and are easily affected by motion artifacts in daily life. In the smart clothes developed in this study, a noncontact electrode was used to assess the biopotential across the clothes to prevent skin irritation and discomfort. Moreover, a three-dimensional parametric model based on anthropometric data was built, and the technique of customized product design was introduced into the smart clothes development process to reduce the influence of motion artifacts. The experimental results show that the proposed smart clothes can maintain a good ECG signal quality stably under motion from different activities. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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13 pages, 1686 KiB  
Article
Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol
by Elke Warmerdam, Robbin Romijnders, Johanna Geritz, Morad Elshehabi, Corina Maetzler, Jan Carl Otto, Maren Reimer, Klarissa Stuerner, Ralf Baron, Steffen Paschen, Thorben Beyer, Denise Dopcke, Tobias Eiken, Hendrik Ortmann, Falko Peters, Felix von der Recke, Moritz Riesen, Gothia Rohwedder, Anna Schaade, Maike Schumacher, Anton Sondermann, Walter Maetzler and Clint Hansenadd Show full author list remove Hide full author list
Sensors 2021, 21(17), 5833; https://doi.org/10.3390/s21175833 - 30 Aug 2021
Cited by 14 | Viewed by 3918
Abstract
Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial [...] Read more.
Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18–60 years), healthy older adults (>60 years), and patients with Parkinson’s disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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9 pages, 4445 KiB  
Communication
The Ultraviolet Index Is Well Estimated by the Terrestrial Irradiance at 310 nm
by Peter D. Kaplan and Emmanuel L. P. Dumont
Sensors 2021, 21(16), 5528; https://doi.org/10.3390/s21165528 - 17 Aug 2021
Cited by 1 | Viewed by 2159
Abstract
Ultraviolet (UV) exposure significantly contributes to non-melanoma skin cancer. In the context of health, UV exposure is the product of time and the UV Index (UVI), a weighted sum of the irradiance I(λ) over all wavelengths from λ = 250 to 400 nm. [...] Read more.
Ultraviolet (UV) exposure significantly contributes to non-melanoma skin cancer. In the context of health, UV exposure is the product of time and the UV Index (UVI), a weighted sum of the irradiance I(λ) over all wavelengths from λ = 250 to 400 nm. In our analysis of the United States Environmental Protection Agency’s UV-Net database of over 400,000 spectral irradiance measurements taken over several years, we found that the UVI is well estimated by 77 I310. To further understand this result, we applied an optical atmospheric model to generate terrestrial irradiance spectra and found that it applies across a wide range of conditions. An accurate UVI radiometer can be built from a photodiode covered by a bandpass filter centered at 310 nm. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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13 pages, 3011 KiB  
Article
Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition
by Hwiwon Lee and Sekyoung Youm
Sensors 2021, 21(11), 3594; https://doi.org/10.3390/s21113594 - 21 May 2021
Cited by 8 | Viewed by 3043
Abstract
As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic conditions, such as diabetes or hypertension. Limited opportunity for medication monitoring is a major problem from the perspective of health professionals. The availability of prompt medication [...] Read more.
As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic conditions, such as diabetes or hypertension. Limited opportunity for medication monitoring is a major problem from the perspective of health professionals. The availability of prompt medication error reports can enable health professionals to provide immediate interventions for patients. Furthermore, it can enable clinical researchers to modify experiments easily and predict health levels based on medication compliance. This study proposes a method in which videos of patients taking medications are recorded using a camera image sensor integrated into a wearable device. The collected data are used as a training dataset based on applying the latest convolutional neural network (CNN) technique. As for an artificial intelligence (AI) algorithm to analyze the medication behavior, we constructed an object detection model (Model 1) using the faster region-based CNN technique and a second model that uses the combined feature values to perform action recognition (Model 2). Moreover, 50,000 image data were collected from 89 participants, and labeling was performed on different data categories to train the algorithm. The experimental combination of the object detection model (Model 1) and action recognition model (Model 2) was newly developed, and the accuracy was 92.7%, which is significantly high for medication behavior recognition. This study is expected to enable rapid intervention for providers seeking to treat patients through rapid reporting of drug errors. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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Review

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35 pages, 17742 KiB  
Review
Comprehensive Review on Wearable Sweat-Glucose Sensors for Continuous Glucose Monitoring
by Hima Zafar, Asma Channa, Varun Jeoti and Goran M. Stojanović
Sensors 2022, 22(2), 638; https://doi.org/10.3390/s22020638 - 14 Jan 2022
Cited by 94 | Viewed by 18599
Abstract
The incidence of diabetes is increasing at an alarming rate, and regular glucose monitoring is critical in order to manage diabetes. Currently, glucose in the body is measured by an invasive method of blood sugar testing. Blood glucose (BG) monitoring devices measure the [...] Read more.
The incidence of diabetes is increasing at an alarming rate, and regular glucose monitoring is critical in order to manage diabetes. Currently, glucose in the body is measured by an invasive method of blood sugar testing. Blood glucose (BG) monitoring devices measure the amount of sugar in a small sample of blood, usually drawn from pricking the fingertip, and placed on a disposable test strip. Therefore, there is a need for non-invasive continuous glucose monitoring, which is possible using a sweat sensor-based approach. As sweat sensors have garnered much interest in recent years, this study attempts to summarize recent developments in non-invasive continuous glucose monitoring using sweat sensors based on different approaches with an emphasis on the devices that can potentially be integrated into a wearable platform. Numerous research entities have been developing wearable sensors for continuous blood glucose monitoring, however, there are no commercially viable, non-invasive glucose monitors on the market at the moment. This review article provides the state-of-the-art in sweat glucose monitoring, particularly keeping in sight the prospect of its commercialization. The challenges relating to sweat collection, sweat sample degradation, person to person sweat amount variation, various detection methods, and their glucose detection sensitivity, and also the commercial viability are thoroughly covered. Full article
(This article belongs to the Special Issue Smart Sensors for Wearable Applications)
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