Special Issue "e-Health Pervasive Wireless Applications and Services (e-HPWAS'19)"
A special issue of Information (ISSN 2078-2489).
Deadline for manuscript submissions: 30 May 2020
Dr. Yevgeniya Kovalchuk
School of Computing and Digital Technology, Birmingham City University, Birmingham B5 5JU, UK
Website | E-Mail
Interests: artificial intelligence; machine learning; software engineering; embedded systems; software–hardware integration; sensors and wearables; cyber security; mutli-agent systems; healthcare informatics; movement science and movement and art therapy
e-HPWAS'19 aims at providing optimal, secure, and context-aware e-health systems with the best quality of services (QoS) and user experience (QoE). Applications and services are implemented in wireless environments and architecture with the use of IoT (Internet of Things), big data analysis, and a strong heterogeneity of access technologies, sensors, terminals, users’ needs analyzers, and services (data, content, live streams, or complex network services).
Emerging e-health services and applications can involve the use of “heavy” content, such as multimedia content and streams (e.g., 3D-TV, media conferencing, remote live diagnostics) using conventional e-health devices, or terminals like smart TV sets, home boxes, smartphones, tablets, and new Things. The main topics of e-HPWAS are related to e-health care and safety services provided for patients, the elderly, and dependent persons. These services are generally built using different communication technologies, for different profiles of people in different contexts and places (e.g., in health institutions, at home, in cities). The provided services should ideally be accessible anytime, anywhere, and using any kind of device or platform.
Authors of the IEEE eHPWAS 2019 are encouraged to submit an extended version of their work to this Special Issue of the journal Information with a minimum of 50% of new content and input. Papers describing advanced prototypes, platforms, techniques, and general surveys for discussing future perspectives and directions are particularly encouraged. Each manuscript will be blind-reviewed by academic editors.
Dr. Tayeb Lemlouma
Dr. Abderrezak Rachedi
Dr. Sébastien Laborie
Dr. Yevgeniya Kovalchuk
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. Information 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 1000 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.
- Internet of Things (IoT)
- Big data analysis, summarization, prediction
- Sensor networks (e.g., BAN, WPAN, etc.)
- Network interoperability
- Security and privacy
- User acceptance
- Norms for e-Health (e.g., HL7 norms, electronic health information exchange-HIE, Health Record-HER)
- Web norms for e-health (e.g., WebRTC)
- Context models
- E-Health, artificial intelligence, and machine learning techniques