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Special Issue "Point of Care Sensors"

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

Deadline for manuscript submissions: closed (20 October 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Spyridon E. Kintzios

School of Food, Biotechnology and Development (TBA), Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
Website | E-Mail
Phone: +302105294292
Interests: biosensors; cell-based diagnostic systems; cell and tissue culture; cell differentiation; neuronal development; cell factories
Guest Editor
Dr. Georgia Moschopoulou

School of Food, Biotechnology and Development (TBA), Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
E-Mail
Interests: cell-based biosensors; cell and neuronal differentiation; real-time monitoring systems; high-throughput screening or diagnostics systems
Guest Editor
Dr. Sofia Mavrikou

School of Food, Biotechnology and Development (TBA), Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
E-Mail
Interests: biosensors; cell-based diagnostic systems; cell and tissue culture; cell differentiation

Special Issue Information

Dear Colleagues,

Novel technologies in mobile-based diagnoses are the next wave of innovations in portable, Point-of-Care/Point-of-Test (POCT) analytical and diagnostic science. Current and emerging biosensor designs represent a bold transition beyond the established laboratory- and home-based applications, including blood glucose testing and ecotoxicology screening. Indeed, developments in the new era of biosensing are focused on the end-user as the core element of a multi-purpose screening and information acquisition platform. This trend is facilitated both by progress in data processing with the aid of Artificial Intelligence, for example, Artificial Neural Networks, as well as the integration of sensors into everyday portable appliances, such as smartphones, tablets and wearables, the continuous miniaturization of which allows for remarkable processing capacity on a very small scale. Last, but not least, the majority of these novel designs and devices are compatible with an “Internet-of-Things” set up, allowing for their implementation in a global dimension. This Special Issue is intended to be a timely and comprehensive issue on very recent and emerging concepts and technologies in the fascinating field of ultra-portable biosensors and other analytical devices and approaches. Topics include, but are not restricted to, smartphone/tablet-based electrochemical and/or optical biosensors, lateral flow assays, microfluidic paper-based tests, wearable diagnostic systems (for example smart lenses, bandages and watches), technologies for non-invasive testing, micromotors or nanomotors with embedded biorecognition elements (e.g., digital immunoassays - DIA), biosensors for use in limited resource testing and portable surveillance systems (e.g., drone-based), micro‐electrophoresis assays. The challenges, applications and future of POCT can also be discussed. Research papers, short communications and reviews are all welcome. If the author is interested in submitting a review, it would be helpful to discuss this with the Guest Editor before your submission.

Prof. Dr. Spyridon E. Kintzios
Dr. Georgia Moschopoulou
Dr. Sofia Mavrikou
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 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 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 1800 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

  • Point-of-Care
  • Point-of-Test
  • Smartphone
  • Internet of Things
  • Wearables
  • Drones
  • Lab-on-a-Chip
  • Limited resources

Published Papers (6 papers)

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Research

Open AccessArticle An Ultra-Rapid Biosensory Point-of-Care (POC) Assay for Prostate-Specific Antigen (PSA) Detection in Human Serum
Sensors 2018, 18(11), 3834; https://doi.org/10.3390/s18113834
Received: 10 October 2018 / Revised: 2 November 2018 / Accepted: 6 November 2018 / Published: 8 November 2018
PDF Full-text (1888 KB) | HTML Full-text | XML Full-text
Abstract
Prostate-specific antigen (PSA) is the established routine screening tool for the detection of early-stage prostate cancer. Given the laboratory-centric nature of the process, the development of a portable, ultra rapid high-throughput system for PSA screening is highly desirable. In this study, an advancedpoint-of-care
[...] Read more.
Prostate-specific antigen (PSA) is the established routine screening tool for the detection of early-stage prostate cancer. Given the laboratory-centric nature of the process, the development of a portable, ultra rapid high-throughput system for PSA screening is highly desirable. In this study, an advancedpoint-of-care system for PSA detection in human serum was developed based on a cellular biosensor where the cell membrane was modified by electroinserting a specific antibody against PSA. Thirty nine human serum samples were used for validation of this biosensory system for PSA detection. Samples were analyzed in parallel with a standard immunoradiometric assay (IRMA) and an established electrochemical immunoassay was used for comparison purposes. They were classified in three different PSA concentration ranges (0, <4 and ≥4 ng/mL). Cells membrane-engineered with 0.25 μg/mL anti-PSA antibody demonstrated a statistically lower response against the upper (≥4 ng/mL) PSA concentration range. In addition, the cell-based biosensor performed better than the immunosensor in terms of sensitivity and resolution against positive samples containing <4 ng/mL PSA. In spite of its preliminary, proof-of-concept stage of development, the cell-based biosensor could be used as aninitiative for the development of a fast, low-cost, and high-throughput POC screening system for PSA. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Graphical abstract

Open AccessArticle Earable POCER: Development of a Point-of-Care Ear Sensor for Respiratory Rate Measurement
Sensors 2018, 18(9), 3020; https://doi.org/10.3390/s18093020
Received: 23 July 2018 / Revised: 30 August 2018 / Accepted: 8 September 2018 / Published: 10 September 2018
PDF Full-text (2020 KB) | HTML Full-text | XML Full-text
Abstract
We have carried out research and development on an earphone-type respiratory rate measuring device, earable POCER. The name earable POCER is a combination of “earable”, which is a word coined from “wearable” and “ear”, and “POCER”, which is an acronym for “point-of-care ear
[...] Read more.
We have carried out research and development on an earphone-type respiratory rate measuring device, earable POCER. The name earable POCER is a combination of “earable”, which is a word coined from “wearable” and “ear”, and “POCER”, which is an acronym for “point-of-care ear sensor for respiratory rate measurement”. The earable POCER calculates respiratory frequency, based on the measurement values over one minute, through the simple attachment of an ear sensor to one ear of the measured subject and displays these on a tablet terminal. The earable POCER irradiates infrared light using a light-emitting diode (LED) loaded on an ear sensor to the epidermis within the ear canal and, by receiving that reflected light with a phototransistor, it measures movement of the ear canal based on respiration. In an evaluation experiment, eight healthy subjects first breathed through the nose 12 times per minute, then 16 times per minute, and finally 20 times per minute, in accordance with the flashing of a timing instruction LED. The results of these evaluation tests showed that the accuracy of the respiratory frequency was 100% for nose breathing 12 times per minute, 93.8% at 16 times, and 93.8% at 20 times. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Open AccessArticle Nonlinear Flow Sensor Calibration with an Accurate Syringe
Sensors 2018, 18(7), 2163; https://doi.org/10.3390/s18072163
Received: 30 May 2018 / Accepted: 7 June 2018 / Published: 5 July 2018
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Abstract
Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The
[...] Read more.
Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The objective of the present work was to develop an algorithm to allow the calibration of nonlinear flow sensors using an accurate syringe. We first noticed that a power law equation could properly fit the pressure-flow relationship of nonlinear flow sensors. We then developed a software code to estimate the parameters for this equation using a 3 L syringe (calibration syringe). Finally, we tested the performance of a calibrated flow sensor using a different 3 L syringe (testing syringe) and a commercially available spirometer. After calibration, the sensor had a bias ranging from −1.7% to 3.0% and precision from 0.012 L to 0.039 L for volumes measured with the 3 L testing syringe. Calibrated sensor performance was at least as good as the commercial sensor. This calibration procedure can be done at the bedside for both clinical and research purposes, therefore improving the accuracy of nonlinear flow sensors. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Open AccessArticle Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis
Sensors 2018, 18(4), 1275; https://doi.org/10.3390/s18041275
Received: 5 March 2018 / Revised: 12 April 2018 / Accepted: 18 April 2018 / Published: 21 April 2018
Cited by 1 | PDF Full-text (1113 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Wearable sensors could facilitate point of care, clinically feasible assessments of dynamic stability and associated fall risk through an assessment of single-task (ST) and dual-task (DT) walking. This study investigated gait changes between ST and DT walking and between older adult prospective fallers
[...] Read more.
Wearable sensors could facilitate point of care, clinically feasible assessments of dynamic stability and associated fall risk through an assessment of single-task (ST) and dual-task (DT) walking. This study investigated gait changes between ST and DT walking and between older adult prospective fallers and non-fallers. The results were compared to a study based on retrospective fall occurrence. Seventy-five individuals (75.2 ± 6.6 years; 47 non-fallers, 28 fallers; 6 month prospective fall occurrence) walked 7.62 m under ST and DT conditions while wearing pressure-sensing insoles and accelerometers at the head, pelvis, and on both shanks. DT-induced gait changes included changes in temporal measures, centre of pressure (CoP) path stance deviations and coefficient of variation, acceleration descriptive statistics, Fast Fourier Transform (FFT) first quartile, ratio of even to odd harmonics, and maximum Lyapunov exponent. Compared to non-fallers, prospective fallers had significantly lower DT anterior–posterior CoP path stance coefficient of variation, DT head anterior–posterior FFT first quartile, ST left shank medial–lateral FFT first quartile, and ST right shank superior maximum acceleration. DT-induced gait changes were consistent regardless of faller status or when the fall occurred (retrospective or prospective). Gait differences between fallers and non-fallers were dependent on retrospective or prospective faller identification. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Open AccessArticle Statistical Platform for Individualized Behavioral Analyses Using Biophysical Micro-Movement Spikes
Sensors 2018, 18(4), 1025; https://doi.org/10.3390/s18041025
Received: 23 February 2018 / Revised: 23 March 2018 / Accepted: 27 March 2018 / Published: 29 March 2018
Cited by 1 | PDF Full-text (68690 KB) | HTML Full-text | XML Full-text
Abstract
Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on
[...] Read more.
Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on human heuristics, the analyses become computationally expensive and rather subjective. Further, there is no standardized scale or set of tasks amenable to take advantage of such technology in ways that permit broad dissemination and reproducibility of results. Indeed, there is a critical need for fully objective automated analytical methods that easily handle the deluge of data these sensors output, while providing standardized scales amenable to apply across large sections of the population, to help promote personalized-mobile medicine. Here we use an open-access data set from Kaggle.com to illustrate the use of a new statistical platform and standardized data types applied to smart phone accelerometer and gyroscope data from 30 participants, performing six different activities. We report full distinction without confusion of the activities from the Kaggle set using a single parameter (linear acceleration or angular speed). We further extend the use of our platform to characterize data from commercially available smart shoes, using gait patterns within a set of experiments that probe nervous systems functioning and levels of motor control. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Graphical abstract

Open AccessArticle A Field-Portable Cell Analyzer without a Microscope and Reagents
Sensors 2018, 18(1), 85; https://doi.org/10.3390/s18010085
Received: 29 November 2017 / Revised: 26 December 2017 / Accepted: 28 December 2017 / Published: 29 December 2017
Cited by 2 | PDF Full-text (3400 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper demonstrates a commercial-level field-portable lens-free cell analyzer called the NaviCell (No-stain and Automated Versatile Innovative cell analyzer) capable of automatically analyzing cell count and viability without employing an optical microscope and reagents. Based on the lens-free shadow imaging technique, the NaviCell
[...] Read more.
This paper demonstrates a commercial-level field-portable lens-free cell analyzer called the NaviCell (No-stain and Automated Versatile Innovative cell analyzer) capable of automatically analyzing cell count and viability without employing an optical microscope and reagents. Based on the lens-free shadow imaging technique, the NaviCell (162 × 135 × 138 mm3 and 1.02 kg) has the advantage of providing analysis results with improved standard deviation between measurement results, owing to its large field of view. Importantly, the cell counting and viability testing can be analyzed without the use of any reagent, thereby simplifying the measurement procedure and reducing potential errors during sample preparation. In this study, the performance of the NaviCell for cell counting and viability testing was demonstrated using 13 and six cell lines, respectively. Based on the results of the hemocytometer (de facto standard), the error rate (ER) and coefficient of variation (CV) of the NaviCell are approximately 3.27 and 2.16 times better than the commercial cell counter, respectively. The cell viability testing of the NaviCell also showed an ER and CV performance improvement of 5.09 and 1.8 times, respectively, demonstrating sufficient potential in the field of cell analysis. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Graphical abstract

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