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Special Issue "Sensor-based E-Healthcare System: Greenness and Security"

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

Deadline for manuscript submissions: 30 June 2018

Special Issue Editors

Guest Editor
Prof. Dr. Lei Shu

Nanjing Agricultural University, China / University of Lincoln, UK
Website | E-Mail
Interests: wireless sensor networks; multimedia communication; middleware; security
Guest Editor
Prof. Dr. Joel Rodrigues

National Institute of Telecommunications (Inatel), Av. João de Camargo, 510 - Centro, 37540-000 Santa Rita do Sapucaí-MG, Brazil;
Instituto de Telecomunicações, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
Website | E-Mail
Interests: vehicular delay tolerant networks; sensor networks; body sensor networks; e-health; high-speed networks; information and knowledge management; mobile and ubiquitous computing

Special Issue Information

Dear Colleagues,

Nowadays, sensor-based E-Healthcare systems are attracting increasing attention from both academic and industrial communities, with a number of benefits (e.g., easy access to diagnostic information, reduction of duplicated calls to doctors, fewer delays in treatment) in terms of traditional healthcare systems. As various information and communication technologies are incorporated in sensor-based E-Healthcare systems, the greenness and security, along with the utilization of these technologies, should be considered. For example, data sensing and transmission technologies should enable energy-efficient collection and delivery of patient information, while data storage and access technologies should enable secure storage and access of patient information.

Thus, for operating sensor-based E-Healthcare systems energy-efficiently and securely, this Special Issue calls for original technical papers, which focus on the greenness and security of sensor-based E-Healthcare systems. Tutorials or survey papers will also be considered. In addition, selected high quality papers from HealthCom 2017 (http://healthcom2017.ieee-healthcom.org/) will be invited for further consideration in this Special Issue for publication. Potential topics include, but are not limited to:

  • Green architecture for sensor-based E-Healthcare system

  • Secure architecture for sensor-based E-Healthcare system

  • Green sensing for sensor-based E-Healthcare system

  • Secure sensing for sensor-based E-Healthcare system

  • Green communication for sensor-based E-Healthcare system

  • Secure communication for sensor-based E-Healthcare system

  • Green computing for sensor-based E-Healthcare system

  • Secure computing for sensor-based E-Healthcare system

  • Green data for sensor-based E-Healthcare system

  • Secure data for sensor-based E-Healthcare system

  • Green network for sensor-based E-Healthcare system

  • Secure network for sensor-based E-Healthcare system

  • Green middleware for sensor-based E-Healthcare system

  • Secure middleware for sensor-based E-Healthcare system

Prof. Dr. Lei Shu
Prof. Dr. Joel J.P.C. Rodrigues
Guest Editors

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 monthly 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

  • Sensor

  • E-Healthcare

  • Greenness

  • Security

  • Architecture

  • Sensing

  • Communication

  • Computing

  • Data

  • Network

  • Middleware

Published Papers (4 papers)

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Research

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Open AccessArticle Mixed H2/H-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks
Sensors 2018, 18(1), 56; doi:10.3390/s18010056
Received: 21 September 2017 / Revised: 23 December 2017 / Accepted: 24 December 2017 / Published: 27 December 2017
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Abstract
In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC), the power of sensor node would run out rapidly. On the other hand, the data also needs a
[...] Read more.
In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC), the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H-based energy-efficient fusion estimation model (MHEEFE) for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance. Full article
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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Open AccessArticle A Component-Based Approach for Securing Indoor Home Care Applications
Sensors 2018, 18(1), 46; doi:10.3390/s18010046
Received: 31 October 2017 / Revised: 5 December 2017 / Accepted: 18 December 2017 / Published: 26 December 2017
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Abstract
eHealth systems have adopted recent advances on sensing technologies together with advances in information and communication technologies (ICT) in order to provide people-centered services that improve the quality of life of an increasingly elderly population. As these eHealth services are founded on the
[...] Read more.
eHealth systems have adopted recent advances on sensing technologies together with advances in information and communication technologies (ICT) in order to provide people-centered services that improve the quality of life of an increasingly elderly population. As these eHealth services are founded on the acquisition and processing of sensitive data (e.g., personal details, diagnosis, treatments and medical history), any security threat would damage the public’s confidence in them. This paper proposes a solution for the design and runtime management of indoor eHealth applications with security requirements. The proposal allows applications definition customized to patient particularities, including the early detection of health deterioration and suitable reaction (events) as well as security needs. At runtime, security support is twofold. A secured component-based platform supervises applications execution and provides events management, whilst the security of the communications among application components is also guaranteed. Additionally, the proposed event management scheme adopts the fog computing paradigm to enable local event related data storage and processing, thus saving communication bandwidth when communicating with the cloud. As a proof of concept, this proposal has been validated through the monitoring of the health status in diabetic patients at a nursing home. Full article
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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Open AccessArticle A Multi-Sensor Data Fusion Approach for Atrial Hypertrophy Disease Diagnosis Based on Characterized Support Vector Hyperspheres
Sensors 2017, 17(9), 2049; doi:10.3390/s17092049
Received: 25 July 2017 / Revised: 4 September 2017 / Accepted: 5 September 2017 / Published: 7 September 2017
PDF Full-text (1627 KB) | HTML Full-text | XML Full-text
Abstract
Disease diagnosis can be performed based on fusing the data acquired by multiple medical sensors from patients, and it is a crucial task in sensor-based e-healthcare systems. However, it is a challenging problem that there are few effective diagnosis methods based on sensor
[...] Read more.
Disease diagnosis can be performed based on fusing the data acquired by multiple medical sensors from patients, and it is a crucial task in sensor-based e-healthcare systems. However, it is a challenging problem that there are few effective diagnosis methods based on sensor data fusion for atrial hypertrophy disease. In this article, we propose a novel multi-sensor data fusion method for atrial hypertrophy diagnosis, namely, characterized support vector hyperspheres (CSVH). Instead of constructing a hyperplane, as a traditional support vector machine does, the proposed method generates “hyperspheres” to collect the discriminative medical information, since a hypersphere is more powerful for data description than a hyperplane. In detail, CSVH constructs two characterized hyperspheres for the classes of patient and healthy subject, respectively. The hypersphere for the patient class is developed in a weighted version so as to take the diversity of patient instances into consideration. The hypersphere for the class of healthy people keeps furthest away from the patient class in order to achieve maximum separation from the patient class. A query is labelled by membership functions defined based on the two hyperspheres. If the query is rejected by the two classes, the angle information of the query to outliers and overlapping-region data is investigated to provide the final decision. The experimental results illustrate that the proposed method achieves the highest diagnosis accuracy among the state-of-the-art methods. Full article
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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Review

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Open AccessReview Applications Based on Service-Oriented Architecture (SOA) in the Field of Home Healthcare
Sensors 2017, 17(8), 1703; doi:10.3390/s17081703
Received: 22 May 2017 / Revised: 17 July 2017 / Accepted: 18 July 2017 / Published: 25 July 2017
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Abstract
This article makes a literature review of applications developed in the health industry which are focused on patient care from home and implement a service-oriented (SOA) design in architecture. Throughout this work, the applicability of the concept of Internet of Things (IoT) in
[...] Read more.
This article makes a literature review of applications developed in the health industry which are focused on patient care from home and implement a service-oriented (SOA) design in architecture. Throughout this work, the applicability of the concept of Internet of Things (IoT) in the field of telemedicine and health care in general is evaluated. It also performs an introduction to the concept of SOA and its main features, making a small emphasis on safety aspects. As a central theme, the description of different solutions that can be found in the health industry is developed, especially those whose goal is health care at home; the main component of these solutions are body sensor networks. Finally, an analysis of the literature from the perspectives of functionalities, security implementation and semantic interoperability is made to have a better understanding of what has been done and which are probable research paths to be studied in the future. Full article
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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