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Special Issue "Selected Papers from 7th EAI International Conference on Wireless Mobile Communication and Healthcare"

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

Deadline for manuscript submissions: closed (6 March 2018)

Special Issue Editors

Guest Editor
Dr. Amir Rahmani

TU Wien (Austria) and University of California Irvine (USA), Bren Hall 3062, Donald Bren School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA
Website | E-Mail
Interests: energy-efficient computing for the dark silicon era; self-aware computing; 3D stack architecture; networks-on-chip and system-on-chip; reliability, thermal, and power management; runtime resource allocation and scheduling; test and fault tolerance; healthcare Internet of things (IoT); medical cyber-physical systems; fog computing
Guest Editor
Dr. Paolo Perego

Politecnico di Milano (Italy), via Durando 38/A, CAP 20158, Milan, Italy
Website | E-Mail
Interests: biomedical, wearble devices; Internet of medical things (IOmT); ambient assisted living; home automation; brain computer interface; user centered design; human computer interaction
Guest Editor
Dr. Nima TaheriNejad

TU Wien (Austria), Gußhausstraße 27-29, 1040 Vienna, Austria
Website | E-Mail
Interests: self-awareness; embedded systems; system on chip; robotics and cyber-physicals; intelligence and learning; memristors

Special Issue Information

Dear Colleagues,

This Special Issue seeks selected manuscripts with major extensions for a Special Issue on the 7th EAI International Conference on Wireless Mobile Communication and Healthcare (MobiHealth), held from 14–17 November 2017, in Vienna, Austria. The 7th edition of MobiHealth proposed to continue and extend the focus areas of the first six editions with a focus on specific research and scientific challenges in the Healthcare Technology domain, faced in Europe and globally, and, hence, with a more interactive input from industry. The essence of the conference lies in its interdisciplinary nature, with original contributions cutting across boundaries, but all within the area of the application of mobile communications (technologies, standards, solutions, methodologies, etc.) to the improvement of human health. The Special Issue seeks quality manuscripts from MobiHealth’17, with major extensions, scheduled to appear in the July issue of 2018. All aspects of novel mobile and wireless technologies for smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and Big Data analytics that are aimed at providing tele-health interventions to individuals for healthier lifestyles, are of interest.

MobiHealth 2017: http://mobihealth.name/

Manuscript submission deadline: 20 February 2018
Notification of acceptance: 20 May 2018
Submission of final revised paper: 20 June 2018
Publication of special issue (tentative): 31 July 2018

Dr. Paolo Perego
Dr. Amir M. Rahmani
Dr. Nima TaheriNejad
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

  • Mobile and e-Health Sensing
  • Wearable, outdoor and home-based sensors
  • Healthcare Internet of Things (IoT)
  • Fog Computing in Healthcare
  • Printable Electronics
  • Body Area Sensor Networks
  • Harvesting Management and Optimization
  • Self-systems for Healthcare
  • Data collection and management at hubs, mobile devices and gateways
  • Healthcare telemetry and telemedicine
  • Intra-body communication issues (propagation and transmission)
  • Sensor Devices for Biomedical Monitoring
  • Data Collection and Data Mining in e-Health Applications
  • Implantable Sensors
  • Energy in Biomedical Devices

Published Papers (2 papers)

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Research

Open AccessArticle Geriatric Helper: An mHealth Application to Support Comprehensive Geriatric Assessment
Sensors 2018, 18(4), 1285; https://doi.org/10.3390/s18041285
Received: 20 February 2018 / Revised: 8 April 2018 / Accepted: 19 April 2018 / Published: 22 April 2018
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Abstract
The Comprehensive Geriatric Assessment (CGA) is a multidisciplinary diagnosis approach that considers several dimensions of fragility in older adults to develop an individualized plan to improve their overall health. Despite the evidence of its positive impact, CGA is still applied by a reduced
[...] Read more.
The Comprehensive Geriatric Assessment (CGA) is a multidisciplinary diagnosis approach that considers several dimensions of fragility in older adults to develop an individualized plan to improve their overall health. Despite the evidence of its positive impact, CGA is still applied by a reduced number of professionals in geriatric care in many countries, mostly using a paper-based approach. In this context, we collaborate with clinicians to bring CGA to the attention of more healthcare professionals and to enable its easier application in clinical settings by proposing a mobile application, Geriatric Helper, to act as a pocket guide that is easy to update remotely with up-to-date information, and that acts as a tool for conducting CGA. This approach reduces the time spent on retrieving the scales documentation, the overhead of calculating the results, and works as a source of information for non-specialists. Geriatric Helper is a tool for the health professionals developed considering an iterative, User-Centred Design approach, with extensive contributions from a broad set of users including domain experts, resulting in a highly usable and accepted system. Geriatric Helper is currently being tested in Portuguese healthcare units allowing for any clinician to apply the otherwise experts-limited geriatric assessment. Full article
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Open AccessArticle QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform
Sensors 2018, 18(4), 1097; https://doi.org/10.3390/s18041097
Received: 20 February 2018 / Revised: 25 March 2018 / Accepted: 2 April 2018 / Published: 5 April 2018
PDF Full-text (1298 KB) | HTML Full-text | XML Full-text
Abstract
Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific
[...] Read more.
Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub), which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study (N = 13) to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing. Full article
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