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Chemical and Biological Sensors: Devices and Systems

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

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 4660

Special Issue Editor


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Guest Editor
Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, Crawley, WA 6019, Australia
Interests: electrical noise; GaN devices; biosensors; bioelectronics; GaN HEMTs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ability to measure changes in a large environment such as a water processing plant or an ecological system as well as in smaller scale environments such as the human body is increasing in importance because of economic, health and safety consequences. There have been many advances in recent years and it is timely to provide a Special Issue.

This call for papers invites technical contributions to a Special Issue of Sensors on "Chemical and Biological Sensors: Devices and Systems" The Special Issue is intended to describe novel or state-of-the-art devices and systems to measure chemical and biological environments, and provide insights into function, applications or methods of manufacture. Potential topics include, but are not limited to:

  • Electronic nose
  • Lab-on-a-chip
  • Nano-fluidic devices
  • Bio-medical sensors
  • DNA chips
  • Wearable biosensors
  • Interfaces and membrane technology
  • Instrumentation
  • AI enhancement of selectivity
Prof. Dr. Brett D. Nener
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

  • DNA recognition 
  • Enzyme 
  • Drug discovery 
  • Optical sensors
  • Piezoelectric transducers 
  • Electrochemical transduction
  • Membranes 
  • Surface attachment 
  • Surface properties 
  • Potentiometric 
  • Amperometric 
  • Contaminants

Published Papers (1 paper)

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Research

15 pages, 3786 KiB  
Article
A Hybrid System for Distinguishing between Brain Death and Coma Using Diverse EEG Features
by Li Zhu, Gaochao Cui, Jianting Cao, Andrzej Cichocki, Jianhai Zhang and Changle Zhou
Sensors 2019, 19(6), 1342; https://doi.org/10.3390/s19061342 - 18 Mar 2019
Cited by 6 | Viewed by 4261
Abstract
Electroencephalography (EEG) signals may provide abundant information reflecting the developmental changes in brain status. It usually takes a long time to finally judge whether a brain is dead, so an effective pre-test of brain states method is needed. In this paper, we present [...] Read more.
Electroencephalography (EEG) signals may provide abundant information reflecting the developmental changes in brain status. It usually takes a long time to finally judge whether a brain is dead, so an effective pre-test of brain states method is needed. In this paper, we present a hybrid processing pipeline to differentiate brain death and coma patients based on canonical correlation analysis (CCA) of power spectral density, complexity features, and feature fusion for group analysis. In addition, time-varying power spectrum and complexity were observed based on the analysis of individual patients, which can be used to monitor the change of brain status over time. Results showed three major differences between brain death and coma groups of EEG signal: slowing, increased complexity, and the improvement on classification accuracy with feature fusion. To the best of our knowledge, this is the first scheme for joint general analysis and time-varying state monitoring. Delta-band relative power spectrum density and permutation entropy could effectively be regarded as potential features of discrimination analysis on brain death and coma patients. Full article
(This article belongs to the Special Issue Chemical and Biological Sensors: Devices and Systems)
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