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Special Issue "Multi-Sensor Fusion in Body Sensor Networks"

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

Deadline for manuscript submissions: 15 August 2019

Special Issue Editors

Guest Editor
Dr. Raffaele Gravina

Department of Informatics, Electronics, Modelling and Systems, University of Calabria, Via P. Bucci, 41C, 87036, Arcavacata di Rende (CS) Italy
Website | E-Mail
Interests: high-level programming methodologies and frameworks for body sensor networks; collaborative and cloud-assisted body sensor networks; pattern recognition and knowledge discovery algorithms on physiological signals; human activity recognition; ECG analysis; emotion recognition; interoperability on the Internet-of-Things
Guest Editor
Prof. Ye Li

Shenzhen Institutes of Advanced Technology, Chines Academy of Science, Nanshan, Shenzhen 518055, China
Website | E-Mail
Interests: body sensor networks, wearable sensing, data fusion, medical big data
Guest Editor
Prof. Hassan Ghasemzadeh

School of Electrical Engineering and Computer Science, Washington State University, 355 Spokane Street, Pullman, WA 99164-2752, USA
Website | E-Mail
Interests: pervasive computing, machine learning, algorithm design, Internet-of-Things, mobile health
Guest Editor
Dr. Andrea Mannini

The BioRobotics Institute, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56124 Pisa, Italy
Website | E-Mail
Interests: wearable sensors; machine learning; activity recognition; inertial sensors; movement analysis; gait parameters estimation; automatic early detection of gait alterations; sports bioengineering; mobile health

Special Issue Information

Dear Colleagues,

Multi-sensor data fusion comprises methodologies, algorithms and techniques to capture, from multiple sources, a unified picture of the observed phenomenon. In the context of body sensor networks (BSNs), the objective of sensor data fusion is the integration of multiple, heterogeneous, noisy and error-affected signals to obtain more accurate and comprehensive information on a subject’s health and psycho-physiological status.

Since their appearance, BSNs were considered a potentially disruptive shift of our health and social lifestyle. The key aspect of BSNs are wireless unobstructive wearable sensing units attached to the human body that allow, in mobility, continuous and real-time physiological monitoring to enable diverse applications such as (i) prevention, early detection, and monitoring of diseases and other medical conditions; (ii) elderly assistance at home; (iii) sport and training; (iv) physical activity and gesture detection; and (v) emotion recognition.

However, although the increasing diffusion of smart wearable sensing devices, the design and implementation of effective (and power-efficient) BSN applications remains challenging. Physiological signals are acquired, processed, and streamed by resource-constrained devices with limited processing capabilities, energy availability, and storage capacity that altogether hinder signal processing, pattern recognition, and machine learning performance. Multi-sensor data fusion applied to redundant or complementary signals is seen as an effective solution to infer accurate information from such corrupted, noisy, or error-affected signals. Nevertheless, the current evolution trend of BSNs to multi-device, multi-modal sensing systems makes data fusion a complex task that has only recently started to be approached with systematic and reusable methods and technical solutions.

This Special Issue aims to provide a report of recent research results related to methodologies, algorithms and techniques of “Multi-Sensor Fusion in Body Sensor Networks”.

Dr. Raffaele Gravina
Prof. Ye Li
Prof. Hassan Ghasemzadeh
Dr. Andrea Mannini
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 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 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

  • distributed multi-sensor fusion algorithms 
  • collaborative multi-sensor fusion
  • multi-level algorithms for multi-sensor fusion in BSNs
  • multi-modal fusion for cognitive services
  • power-efficient sensor fusion in BSNs
  • multi-sensor fusion for early diseases detection in BSNs
  • multi-sensor fusion for human activity recognition applications
  • multi-sensor fusion for emotion recognition applications

Published Papers

This special issue is now open for submission.
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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