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Noncontact and Unobtrusive Biomedical Sensors 2018
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Noncontact and Unobtrusive Biomedical Sensors 2018

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

Deadline for manuscript submissions: closed (20 May 2018) | Viewed by 21601

Special Issue Editors

Prof. Steffen Leonhardt

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Guest Editor
Philips Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, D-52074 Aachen, Germany
Interests: physiological measurement techniques; personal health care systems and feedback control systems in medicine
Special Issues, Collections and Topics in MDPI journals
Dr. Daniel Teichmann

E-Mail Website
Guest Editor
Philips Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, D-52074 Aachen, Germany
Interests: biomedical monitoring; signal processing and data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to cordially invite you to participate in a Special Issue on “Noncontact and Unobtrusive Biomedical Sensors”. This Special Issue shall concentrate on noncontact and unobtrusive biomedical sensors for the monitoring of vital signs. Such biomedical sensor devices offer a variety of benefits. They, not only prevent the risk of infection, but are also easy to apply and suitable for long-term monitoring.

While previous Special Issues have focused on wearable or noninvasive sensor techniques, contributions to this Special Issue may include, but are not limited to:

  1. Sensor technology: Presentation, analysis, and evaluation of noncontact and unobtrusive sensors that are able to take measurements in an imperceptible way.
  2. Measurement set-ups: Special set-ups and arrangements can make measurements more accurate or robust; they may also allow promising utilization of noncontact and unobtrusive sensors in new fields and areas, such as automotive environments, beds, bathrooms, or medical treatment units.
  3. Signal processing: Smart signal processing plays a major role in noncontact and unobtrusive sensing. This addresses algorithmic approaches for proper vital parameter extraction, as well as signal fusion algorithms that are able to fuse signals in order to gain higher coverage rate, higher accuracy, or new diagnostic information.
Prof. Dr. Steffen Leonhardt
Dr. Daniel Teichmann
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

  • noncontact
  • unobtrusive
  • vital signs
  • physiological signals
  • signal fusion
  • signal processing

Published Papers (3 papers)

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Research

38 pages, 20867 KiB  
Article
Unobtrusive Vital Sign Monitoring in Automotive Environments—A Review
by Steffen Leonhardt, Lennart Leicht and Daniel Teichmann
Sensors 2018, 18(9), 3080; https://doi.org/10.3390/s18093080 - 13 Sep 2018
Cited by 86 | Viewed by 12761
Abstract
This review provides an overview of unobtrusive monitoring techniques that could be used to monitor some of the human vital signs (i.e., heart activity, breathing activity, temperature and potentially oxygen saturation) in a car seat. It will be shown that many techniques actually [...] Read more.
This review provides an overview of unobtrusive monitoring techniques that could be used to monitor some of the human vital signs (i.e., heart activity, breathing activity, temperature and potentially oxygen saturation) in a car seat. It will be shown that many techniques actually measure mechanical displacement, either on the body surface and/or inside the body. However, there are also techniques like capacitive electrocardiogram or bioimpedance that reflect electrical activity or passive electrical properties or thermal properties (infrared thermography). In addition, photopleythysmographic methods depend on optical properties (like scattering and absorption) of biological tissues and—mainly—blood. As all unobtrusive sensing modalities are always fragile and at risk of being contaminated by disturbances (like motion, rapidly changing environmental conditions, triboelectricity), the scope of the paper includes a survey on redundant sensor arrangements. Finally, this review also provides an overview of automotive demonstrators for vital sign monitoring. Full article
(This article belongs to the Special Issue Noncontact and Unobtrusive Biomedical Sensors 2018)
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20 pages, 6525 KiB  
Article
Noncontact Strain Monitoring of Osseointegrated Prostheses
by Sumit Gupta, Han-Joo Lee, Kenneth J. Loh, Michael D. Todd, Joseph Reed and A. Drew Barnett
Sensors 2018, 18(9), 3015; https://doi.org/10.3390/s18093015 - 09 Sep 2018
Cited by 15 | Viewed by 3655
Abstract
The objective of this study was to develop a noncontact, noninvasive, imaging system for monitoring the strain and deformation states of osseointegrated prostheses. The proposed sensing methodology comprised of two parts. First, a passive thin film was designed such that its electrical permittivity [...] Read more.
The objective of this study was to develop a noncontact, noninvasive, imaging system for monitoring the strain and deformation states of osseointegrated prostheses. The proposed sensing methodology comprised of two parts. First, a passive thin film was designed such that its electrical permittivity increases in tandem with applied tensile loading and decreases while unloading. It was found that patterning the thin films could enhance their dielectric property’s sensitivity to strain. The film can be deposited onto prosthesis surfaces as an external coating prior to implant. Second, an electrical capacitance tomography (ECT) measurement technique and reconstruction algorithm were implemented to capture strain-induced changes in the dielectric property of nanocomposite-coated prosthesis phantoms when subjected to different loading scenarios. The preliminary results showed that ECT, when coupled with strain-sensitive nanocomposites, could quantify the strain-induced changes in the dielectric property of thin film-coated prosthesis phantoms. The results suggested that ECT coupled with embedded thin films could serve as a new noncontact strain sensing method for scenarios when tethered strain sensors cannot be used or instrumented, especially in the case of osseointegrated prostheses. Full article
(This article belongs to the Special Issue Noncontact and Unobtrusive Biomedical Sensors 2018)
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14 pages, 4864 KiB  
Article
Free-Form Deformation Approach for Registration of Visible and Infrared Facial Images in Fever Screening
by Yedukondala Narendra Dwith Chenna, Pejhman Ghassemi, T. Joshua Pfefer, Jon Casamento and Quanzeng Wang
Sensors 2018, 18(1), 125; https://doi.org/10.3390/s18010125 - 04 Jan 2018
Cited by 28 | Viewed by 4517
Abstract
Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate [...] Read more.
Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate estimates of core body temperature and are preferred sites for fever screening. Therefore, rapid, automated identification of the canthi regions within facial IR images may greatly facilitate rapid fever screening of asymptomatic travelers. However, it is more difficult to accurately identify the canthi regions from IR images than from visible images that are rich with exploitable features. In this study, we developed and evaluated techniques for multi-modality image registration (MMIR) of simultaneously captured visible and IR facial images for fever screening. We used free form deformation (FFD) models based on edge maps to improve registration accuracy after an affine transformation. Two widely used FFD models in medical image registration based on the Demons and cubic B-spline algorithms were qualitatively compared. The results showed that the Demons algorithm outperformed the cubic B-spline algorithm, likely due to overfitting of outliers by the latter method. The quantitative measure of registration accuracy, obtained through selected control point correspondence, was within 2.8 ± 1.2 mm, which enables accurate and automatic localization of canthi regions in the IR images for temperature measurement. Full article
(This article belongs to the Special Issue Noncontact and Unobtrusive Biomedical Sensors 2018)
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