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Special Issue "Smartphone-Based Biosensing"

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

Deadline for manuscript submissions: 31 July 2019

Special Issue Editor

Guest Editor
Prof. Dr. Elisa Michelini

Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum- University of Bologna, Bologna, Italy
Website | E-Mail
Interests: whole-cell biosensors; smartphone-based devices; bio-chemiluminescence; 3D-printed analytical devices; environmental monitoring; point-of-care diagnostics

Special Issue Information

Dear Colleagues,

This Special Issue aims at providing a collection of approaches and strategies that have been pursued in this direction, highlighting advantages, limitations, and current challenges. Authors are invited to submit both original research articles and reviews covering a broad range of technical solutions. A non-exhaustive list of topics includes facile 3D printing technology, microfluidics, nanomaterials and biohybrid biorecognition elements, lateral-flow assays, paper-based analytical devices, cell-based biosensors, and aptamer biosensors.

Prof. Dr. Elisa Michelini
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 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

  • Smartphones
  • Biosensor
  • Point-of-care
  • Optical detection
  • Personalized diagnostics
  • 3D-printing
  • Low-cost sensors
  • Mobile diagnostics
  • Paper-based devices

Published Papers (3 papers)

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Research

Open AccessArticle
Mass Surveilance of C. elegans—Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection
Sensors 2019, 19(6), 1468; https://doi.org/10.3390/s19061468
Received: 18 February 2019 / Revised: 17 March 2019 / Accepted: 20 March 2019 / Published: 26 March 2019
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Abstract
The nematode Caenorhabditis elegans (C. elegans) is often used as an alternative animal model due to several advantages such as morphological changes that can be seen directly under a microscope. Limitations of the model include the usage of expensive and cumbersome microscopes, and [...] Read more.
The nematode Caenorhabditis elegans (C. elegans) is often used as an alternative animal model due to several advantages such as morphological changes that can be seen directly under a microscope. Limitations of the model include the usage of expensive and cumbersome microscopes, and restrictions of the comprehensive use of C. elegans for toxicological trials. With the general applicability of the detection of C. elegans from microscope images via machine learning, as well as of smartphone-based microscopes, this article investigates the suitability of smartphone-based microscopy to detect C. elegans in a complete Petri dish. Thereby, the article introduces a smartphone-based microscope (including optics, lighting, and housing) for monitoring C. elegans and the corresponding classification via a trained Histogram of Oriented Gradients (HOG) feature-based Support Vector Machine for the automatic detection of C. elegans. Evaluation showed classification sensitivity of 0.90 and specificity of 0.85, and thereby confirms the general practicability of the chosen approach. Full article
(This article belongs to the Special Issue Smartphone-Based Biosensing)
Figures

Figure 1

Open AccessCommunication
Significant Sensitivity Improvement for Camera-Based Lateral Flow Immunoassay Readers
Sensors 2018, 18(11), 4026; https://doi.org/10.3390/s18114026
Received: 23 September 2018 / Revised: 16 November 2018 / Accepted: 16 November 2018 / Published: 19 November 2018
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Abstract
Recent developments in smartphone-based strip readers have further improved the performances of lateral flow test kits. Most smartphone cameras encode an unaltered and nonlinear power-law transfer function that maps the light intensity to a pixel value; this poses some limitations for camera-based strip [...] Read more.
Recent developments in smartphone-based strip readers have further improved the performances of lateral flow test kits. Most smartphone cameras encode an unaltered and nonlinear power-law transfer function that maps the light intensity to a pixel value; this poses some limitations for camera-based strip readers. For faint-color test lines which are almost as white such as with nitrocellulose pads, the slope of the transfer function is low. Therefore, it is difficult to differentiate between the faint test lines and the white background. We show that by manually setting the camera exposure time—instead of using the automatic settings—to the high-slope region of the transfer function, the reader’s sensitivity can be improved. We found that the sensitivity and the limit of detection of the Acidovorax avenae subsp. citrulli (Aac) test kit were enhanced up to 3-fold and 5-fold, respectively, when using the readers at the optimal camera settings, compared to the automatic mode settings. This simple technique can be readily applied to any existing camera-based colorimetric strip reader to significantly improve its performance. Full article
(This article belongs to the Special Issue Smartphone-Based Biosensing)
Figures

Graphical abstract

Open AccessArticle
Blood Coagulation Testing Smartphone Platform Using Quartz Crystal Microbalance Dissipation Method
Sensors 2018, 18(9), 3073; https://doi.org/10.3390/s18093073
Received: 13 August 2018 / Revised: 6 September 2018 / Accepted: 6 September 2018 / Published: 13 September 2018
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Abstract
Blood coagulation function monitoring is important for people who are receiving anticoagulation treatment and a portable device is needed by these patients for blood coagulation self-testing. In this paper, a novel smartphone based blood coagulation test platform was proposed. It was developed based [...] Read more.
Blood coagulation function monitoring is important for people who are receiving anticoagulation treatment and a portable device is needed by these patients for blood coagulation self-testing. In this paper, a novel smartphone based blood coagulation test platform was proposed. It was developed based on parylene-C coated quartz crystal microbalance (QCM) dissipation measuring and analysis. The parylene-C coating constructed a robust and adhesive surface for fibrin capturing. The dissipation factor was obtained by measuring the frequency response of the sensor. All measured data were sent to a smartphone via Bluetooth for dissipation calculation and blood coagulation results computation. Two major coagulation indexes, activated partial thromboplastin time (APTT) and prothrombin time (PT) were measured on this platform compared with results by a commercial hemostasis system in a clinical laboratory. The measurement results showed that the adjusted R-square (R2) value for APTT and PT measurements were 0.985 and 0.961 respectively. The QCM dissipation method for blood coagulation measurement was reliable and effective and the platform together with the QCM dissipation method was a promising solution for point of care blood coagulation testing. Full article
(This article belongs to the Special Issue Smartphone-Based Biosensing)
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Figure 1

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