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Body Sensor Networks (BSN) and Innovative Approaches for Data Fusion and Analytics in Internet of Medical Things (IoMT)

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 867

Special Issue Editors

E-Mail Website
Guest Editor
Department of Information and Electrical Engineering and Applied Mathematics, Università di Salerno, Salerno, Italy
Interests: wearable sensors; IoT; semantic web; edge and cloud computing
Università di Salerno, Department of Information and Electrical Engineering and Applied Mathematics, Salerno, Italy
Interests: Information Retrieval; Affective Computing; Semantic Web

E-Mail Website
Guest Editor
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

Special Issue Information

Dear Colleagues,

MDPI Sensors invites manuscript submissions in the area of Internet of Medical Things (IoMT).

In recent decades, the world has been facing major challenges to manage the rapid aging of the population, the increase of individuals with chronic illnesses, infant mortality, high-frequency outbreaks of epidemics, poor health, and increased pollution. The continued growth in the demand for medical services requires a transition from the traditional model of hospital care (in which the citizen turns to the medical facility when symptoms of a pathological state appear) towards a more sustainable model in the long term, where continuous monitoring of the health status as well as remote treatment (where possible) of the diseases will be feasible. In this context, information technologies and in particular the Internet of Things (IoT) are finding a privileged position thanks to technological advances in the world of wearable sensor networks (body sensor networks—BSN), machine learning, and the wide diffusion of low-cost microcontrollers and single board computers. With the IoT becoming a context for data analysis in the medical field, a general Internet of Medical Things (IoMT) scenario can be exploited at different layers: A sensing layer (physical or virtual sensors); an edge/fog computing layer (e.g., microcontrollers or single board low-power computers meant for pre-processing), or a cloud layer (for high complexity processing and/or storage).

In this context, the research challenges concern several aspects: Body sensor networks (BSN) and innovative approaches for data fusion; fog and edge computing for pre-processing, filtering and compression of data produced by sensors; stream processing and parallel architectures; cloud computing for intensive processing and data storage; machine learning algorithms and deep networks for the detection of anomalies and prevention (risk reduction); and real-time monitoring and analysis for predictive and/or evaluative purposes on the effect of physiatric and pharmacological therapies in relation to chronic diseases.

The primary goal of this Special Section in MDPI Sensors is to provide an overview of the current state-of-the-art advances in the domain of IoMT.

Topics of interest include but are not limited to:

  • Body sensors networks (BSN) in IoMT;
  • Nano and bio sensors for health monitoring, disease prevention, diagnostic and drug delivery;
  • Data fusion from BSN for IoMT;
  • IoMT architecture for healthcare;
  • IoMT infrastructure and applications for home patient care;
  • Innovative machine learning algorithms or applications in IoMT;
  • Medical data security and privacy techniques for healthcare;
  • Fog and edge computing in IoMT;
  • Parallel architectures for medical big data in IoMT;
  • Low-power medical devices for IoMT;
  • Reinforcement learning in IoMT;
  • Smart medical systems based on cloud-assisted body area networks;
  • Flexible and wearable sensors in the IoMT paradigm;
  • Healthcare informatics to analyze patient health records, for enabling better clinical decision making and improved healthcare outcomes.

We also highly encourage the submission of multimedia with each article, as this significantly increases the visibility, downloads, and citations of articles.

Prof. Dr. Pierluigi Ritrovato
Dr. Luca Greco
Prof. Dr. Giancarlo Fortino
Dr. Kelvin Wong
Dr. Hassan Ghasemzadeh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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. 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 2600 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.


  • Body sensors networks (BSN)
  • IoMT
  • Nano sensors
  • biosensors
  • health monitoring
  • healthcare
  • smart medical systems
  • wearable sensors

Published Papers

There is no accepted submissions to this special issue at this moment.
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