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Sensors
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CMOS Integrated Sensors for Healthcare and Biomedical Applications
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CMOS Integrated Sensors for Healthcare and Biomedical Applications

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

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 3579

Special Issue Editor

Prof. Dr. Kiichi Niitsu

E-Mail Website
Guest Editor
Nagoya University, Nagoya, Japan
Interests: biosensor; healthcare IoT; integrated biosensors; energy-efficient circuits and systems

Special Issue Information

Dear Colleagues,

Recently, the developments of healthcare and biomedical IoTs associated with AI have attracted more and more attention.

For accelerating these IoTs developments, the CMOS integrated sensor is one of the most important fundamental technologies.

The purpose of this Special Issue is to gather original contributions or review papers from researchers that are actively doing R&D for developing new ideas in this field. The interest is in integrated sensors based on CMOS technology, such as integrated biosensor technology, building block circuits and systems for healthcare and biomedical IoTs, and so on.

Prof. Dr. Kiichi Niitsu
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 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

  • CMOS
  • healthcare IoT
  • biomedical IoT
  • integrated biosensor

Published Papers (1 paper)

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12 pages, 3029 KiB  
Letter
Development of a Smartphone-Based Fluorescent Immunochromatographic Assay Strip Reader
by Qi Zheng, Huihuang Wu, Haiyan Jiang, Jiejie Yang and Yueming Gao
Sensors 2020, 20(16), 4521; https://doi.org/10.3390/s20164521 - 13 Aug 2020
Cited by 7 | Viewed by 3150
Abstract
Fluorescence immunochromatographic assay (FICA) is a rapid immunoassay technique that has the characteristics of high precision and sensitivity. Although image FICA strip readers have the advantages of high portability and easy operation, the use of high-precision complementary metal oxide semiconductor (CMOS) image sensors [...] Read more.
Fluorescence immunochromatographic assay (FICA) is a rapid immunoassay technique that has the characteristics of high precision and sensitivity. Although image FICA strip readers have the advantages of high portability and easy operation, the use of high-precision complementary metal oxide semiconductor (CMOS) image sensors leads to an increase in overall cost. Considering the popularity of CMOS image sensors in smartphones and their powerful processing functions, this work developed a smartphone-based FICA strip reader. An optical module suitable for the test strips with different fluorescent markers was designed by replacing the excitation light source and the light filter. An android smartphone was used for image acquisition and image denoising. Then, the test and control lines of the test strip image were recognized by the sliding window algorithm. Finally, the characteristic value of the strip image was calculated. A linear detection range from 10 to 5000 mIU/mL (R2 = 0.95) was obtained for human chorionic gonadotrophin with the maximum relative error less than 9.41%, and a linear detection range from 5 to 4000 pg/mL (R2 = 0.99) was obtained for aflatoxin B1, with the maximum relative error less than 12.71%. Therefore, the smartphone-based FICA strip reader had high portability, versatility, and accuracy. Full article
(This article belongs to the Special Issue CMOS Integrated Sensors for Healthcare and Biomedical Applications)
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