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Special Issue "Sensors, Signal and Image Processing in Biomedicine and Assisted Living"

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

Deadline for manuscript submissions: 31 August 2019

Special Issue Editor

Guest Editor
Prof. Dr. Dimitris Iakovidis

Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, 35131 Lamia, Greece
Website | E-Mail
Interests: Signal/image processing and analysis; Pattern recognition, data mining & machine learning; Software engineering; Bio-inspired algorithms & fuzzy systems; Decision support & cognitive systems; Challenging applications including but not limited to clinical informatics and biomedical engineering

Special Issue Information

Dear Colleagues,

Sensor technologies are crucial in biomedicine, as the biomedical devices used for screening and/or diagnosis rely on their efficiency and effectiveness. Further enhancement of the sensor signals acquired, such as the noise reduction in the one-dimensional electroencephalographic (EEG) signals or the color correction in the endoscopic images, and their analysis by computer-based medical systems, has been enabled by artificial intelligence, which promises enhanced diagnostic yield and productivity for sustainable health systems. Furthermore, today, smart sensor systems incorporating advanced signal processing and analysis techniques are entering our life through smartphones and other wearable devices to monitor our health status and help us maintain a healthy lifestyle. The impact of such technologies can be even more significant for the elderly or people with disabilities, such as the visually impaired.

In this context, this Special Issue welcomes original contributions that focus on novel sensor technologies, signal, image, and video processing/analysis methodologies. It also welcomes review articles on challenging topics and emerging technologies.

This Special Issue is organized in the context of the project ENORASI (Intelligent Audiovisual System Enhancing Cultural Experience and Accessibility), co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1EDK-02070).

Prof. Dr. Dimitris Iakovidis
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


  • Biomedical systems
  • Assistive systems
  • Multisensor systems
  • Biomedical sensors
  • Sensor networks
  • Internet of Things (IoT)
  • Machine learning
  • Decision making
  • Uncertainty-aware systems
  • Segmentation
  • Detection
  • Classification
  • Modeling and simulation
  • Video analysis
  • Multimodal signal fusion
  • Coding and compression
  • Summarization
  • Transmission
  • Quality enhancement
  • Quality assessment

Published Papers (1 paper)

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Research

Open AccessArticle Low-Complexity and Hardware-Friendly H.265/HEVC Encoder for Vehicular Ad-Hoc Networks
Sensors 2019, 19(8), 1927; https://doi.org/10.3390/s19081927
Received: 19 March 2019 / Revised: 16 April 2019 / Accepted: 22 April 2019 / Published: 24 April 2019
PDF Full-text (1653 KB) | HTML Full-text | XML Full-text
Abstract
Real-time video streaming over vehicular ad-hoc networks (VANETs) has been considered as a critical challenge for road safety applications. The purpose of this paper is to reduce the computation complexity of high efficiency video coding (HEVC) encoder for VANETs. Based on a novel [...] Read more.
Real-time video streaming over vehicular ad-hoc networks (VANETs) has been considered as a critical challenge for road safety applications. The purpose of this paper is to reduce the computation complexity of high efficiency video coding (HEVC) encoder for VANETs. Based on a novel spatiotemporal neighborhood set, firstly the coding tree unit depth decision algorithm is presented by controlling the depth search range. Secondly, a Bayesian classifier is used for the prediction unit decision for inter-prediction, and prior probability value is calculated by Gibbs Random Field model. Simulation results show that the overall algorithm can significantly reduce encoding time with a reasonably low loss in encoding efficiency. Compared to HEVC reference software HM16.0, the encoding time is reduced by up to 63.96%, while the Bjontegaard delta bit-rate is increased by only 0.76–0.80% on average. Moreover, the proposed HEVC encoder is low-complexity and hardware-friendly for video codecs that reside on mobile vehicles for VANETs. Full article
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