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Capacitive Fingerprint Sensors and Applications

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

Deadline for manuscript submissions: closed (1 April 2022) | Viewed by 2362

Special Issue Editor


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Guest Editor
School of Engineering, London South Bank University, London SE1 0AA, UK
Interests: infrared sensing technologies; lasers and detectors; capacitive imaging; skin hydration; embedded systems; Internet of Things; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the increase in consumer electronic products such as smart phones and tablets, the demands for biometric sensing capabilities are also increasing. Among a variety of biometric sensing systems, capacitive fingerprint sensors are one of the most popular biometric sensing techniques in the current market, with smartphones commonly adopting capacitive fingerprint sensors for a biometric identification method. 

The Internet of Things is another fast-growing area that has increasing demands for authentication techniques. Capacitive fingerprint sensors are again a popular choice due to the compact size and low power consumption of the hardware.

Apart from biometric applications, capacitive fingerprint sensors have also been used for skin measurements, such as water content and solvent penetration measurements, as well as skin texture and skin micro-relief measurements, and so on. Machine learning and deep learning have also been used for analysing capacitive skin images.

I am excited to be the Guest Editor of this Special Issue. This Special Issue targets researchers working in the field of capacitive fingerprint sensors, as well as the end-users who utilise the sensors for their own applications. We hereby invite the international community with expert knowledge of capacitive fingerprint sensors to participate in this high impact journal, aiming at the proper dissemination of our research.

Prof. Perry Xiao
Guest Editor

Manuscript Submission Information

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Keywords

  • Capacitive fingerprint sensors
  • Biometric sensing
  • Internet of Things
  • Machine learning
  • Deep learning
  • Skin hydration
  • Skin texture

Published Papers (1 paper)

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Research

10 pages, 5849 KiB  
Communication
The Effect of Sun Tan Lotion on Skin by Using Skin TEWL and Skin Water Content Measurements
by Perry Xiao and Daqing Chen
Sensors 2022, 22(9), 3595; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093595 - 09 May 2022
Cited by 5 | Viewed by 1907
Abstract
Stratum corneum (SC) is the outermost skin layer. SC hydration is important for its cosmetic properties and barrier function. SC trans-epidermal water loss (TEWL) measurements and skin water content measurements are two key indexes used for SC characterisation. The instrument stability and accuracy [...] Read more.
Stratum corneum (SC) is the outermost skin layer. SC hydration is important for its cosmetic properties and barrier function. SC trans-epidermal water loss (TEWL) measurements and skin water content measurements are two key indexes used for SC characterisation. The instrument stability and accuracy are vitally important when measuring small changes. In this paper, we present our latest study on the effect of sun tan lotion on skin by using skin TEWL and skin water content measurements. We developed techniques to improve the measurement stability and to visualise small changes, as well as developed machine learning algorithms for processing the skin capacitive images. The overall results show that TEWL and skin water content measurements are capable of measuring the subtle changes of skin conditions due to the application of sun tan lotions. The results show that the TEWL values decreased after the sun tan lotion application. The sun tan lotion with SPF 20 had the lowest decrease, whilst the sun tan lotion with SPF 50+ had the highest decrease. The results also show that the skin water content increased after the sun tan lotion application, with SPF 20 having the highest increase, whilst SPF 50+ had the lowest increase. Full article
(This article belongs to the Special Issue Capacitive Fingerprint Sensors and Applications)
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