Special Issue "Smart Health"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (31 March 2016) | Viewed by 11594

Special Issue Editors

Center for Outcomes Research and Evaluation, Yale School of Medicine; Department of Statistics, Yale University
Interests: wearable sensors; activity recognition; medical risk prediction and stratification; patient-centered outcomes research; medical data analysis
School of Electrical Engineering and Computer Science, Washington State University, Pullman, Washington, USA
Interests: embedded systems; pervasive computing; smart health; cyber physical systems
Special Issues, Collections and Topics in MDPI journals
Dr. Sunghoon Ivan Lee
E-Mail Website
Guest Editor
Department of Physical Medicine and Rehabilitation, Harvard Medical School
Interests: wearable sensors; remote monitoring; smart health; medical data analysis
1 Department of Preventive Medicine, Northwestern University
2 Department of Electrical Engineering and Computer Science, Northwestern University
Interests: wireless health; data analytics; preventive medicine; activity recognition; food intake recognition; embedded systems; wearable sensors; remote health monitoring; human-computer interaction

Special Issue Information

Dear Colleagues,

This Special Issue focuses on smart health, which inherently integrates ideas, tools, and expertise from a variety of disciplines, including computer science and engineering, electrical engineering, biomedical engineering, nursing, medicine, and public health. We solicit papers on theoretical and experimental research, prototyping efforts, case studies, and advances in technology related to smart health technologies and systems. Special topics of interest include, but are not limited to:

Devices, Systems and Infrastructures for Smart Health

  • Medical device prototypes for diagnosis/prevention
  • Wearable and implantable sensors
  • Disposable and cost-effective electronics
  • Systems for health promotion and disease prevention
  • Body sensor networks
  • Smart environments for health
  • Remote patient monitoring
  • Mobile health technologies
  • Data management
  • Interface with health information systems such as electronic health records

Algorithms and Software for Smart Health

  • Signal processing and pattern recognition
  • Machine learning and clinical decision support
  • Health informatics
  • Algorithms for security and safety
  • Communication protocols and algorithms
  • Context-Aware Sensing
  • Algorithms for anomaly detection
  • Human-computer interaction
  • Computational models for predicting and understanding behaviour

Scalable Smart Health

  • Reliability, security, and data uncertainty challenges
  • Data collection in the wild
  • Collecting ground truth data in unstructured environments
  • Approaches for deployment and validation of smart health systems in the wild
  • Models for benchmarking and validation
  • Patient-centered design approaches
  • Interoperability of smart health technologies and existing medical data systems
  • Techniques to enhance compliance
  • Models to assess impact of the technology on healthcare cost
  • Novel applications of smart health in chronic diseases management
  • Clinical studies and field validation techniques
  • Novel experimental testbeds
  • Algorithms and frameworks for seamless sensing

Assistant Professor Dr. Hassan Ghasemzadeh
Assistant Professor Dr. Nabil Alshurafa
Dr. Sunghoon Ivan Lee
Dr. Jack Bobak Mortazavi
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 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. 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 1600 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.


  • Smart Health
  • Algorithm
  • Sensors
  • Machine learning
  • Signal processing
  • Clinical studies
  • Context-aware

Published Papers (1 paper)

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An mHealth Tool Suite for Mobility Assessment
Information 2016, 7(3), 47; https://doi.org/10.3390/info7030047 - 18 Jul 2016
Cited by 14 | Viewed by 10971
The assessment of mobility and functional impairments in the elderly is important for early detection and prevention of fall conditions. Falls create serious threats to health by causing disabling fractures that reduce independence in the elderly. Moreover, they exert heavy economic burdens on [...] Read more.
The assessment of mobility and functional impairments in the elderly is important for early detection and prevention of fall conditions. Falls create serious threats to health by causing disabling fractures that reduce independence in the elderly. Moreover, they exert heavy economic burdens on society due to high treatment costs. Modern smartphones enable the development of innovative mobile health (mHealth) applications by integrating a growing number of inertial and environmental sensors along with the ever-increasing data processing and communication capabilities. Mobility assessment is one of the promising mHealth application domains. In this paper, we introduce a suite of smartphone applications for assessing mobility in the elderly population. The suite currently includes smartphone applications that automate and quantify the following standardized medical tests for assessing mobility: Timed Up and Go (TUG), 30-Second Chair Stand Test (30SCS), and 4-Stage Balance Test (4SBT). For each application, we describe its functionality and a list of parameters extracted by processing signals from smartphone’s inertial sensors. The paper shows the results from studies conducted on geriatric patients for TUG tests and from experiments conducted in the laboratory on healthy subjects for 30SCS and 4SBT tests. Full article
(This article belongs to the Special Issue Smart Health)
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