Special Issue "Intelligent Health Services Based on Biomedical Smart Sensors"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 June 2019

Special Issue Editors

Guest Editor
Prof. Dr. Ricardo Colomo-Palacios

Department of Computer Science, Østfold University College, Halden, Norway
Website | E-Mail
Interests: information systems, human factors in computing, project management in information-systems development, global and distributed software-engineering, systems, services, and software process improvement and innovation, management information systems, business software, innovation in IT
Guest Editor
Prof. Dr. Juan A. Gómez-Pulido

Escuela Politécnica, Universidad de Extremadura, Cáceres, Spain
Website | E-Mail
Fax: (+34)927257187
Interests: optimization and computational intelligence; machine learning; reconfigurable computing and FPGAs; wireless communications; bioinformatics
Guest Editor
Dr. Alfredo J. Pérez

TSYS School of Computer Science, Columbus State University, Columbus, GA 31907, USA
Website | E-Mail
Interests: privacy; mobile/ubiquitous computing and sensing; human-activity recognition; multiobjective optimization and its application to computer networks and scheduling; CS education

Special Issue Information

Dear Colleagues,

Advances in computer technologies are driving significant changes in medical care by shifting the hospital-centered paradigm to a patient-centered one. The focus on disease is replaced with the orientation to wellness. Monitoring and analyzing biomedical variables are key activities required for diagnosis and health care. The automation of these activities by means of computing systems allows processing massive volumes of data collected from biomedical sensors, leading to useful field applications to health personnel. This is particularly interesting to predict the diagnosis of certain diseases suffered by the most vulnerable groups, like the elderly. New systems, applications, developments, models, and research that make use of monitored medical data are envisaged to bring differentiated services to the society.

Big Data and Machine Learning provide significant potential for this purpose, leading to new applications, more effective operations, and more human approaches. These methodologies enable digging massive databases, enhancing the knowledge base and producing new data model-based applications and services for society. The most significant requirement for these technologies is the availability of databases to mine them or to train and test the models. However, medical information is hard to obtain for administrative issues, so other efficient alternatives to collect data are required. The use of smart sensors requires strategies to minimize interference with the work of health personnel and have a minimal impact on monitored patients. The implementation of health-care services with these technologies will probably save costs, but the benefits will be better perceived as an increment of the satisfaction of patients and personnel. Moreover, these technological implementations will expand accessibility to new areas.

This Special Issue provides a collection of papers of original advances in health applications and services propelled by artificial intelligence, big data, and machine learning, supported by the design of biosensor systems for the construction of trustable medical databases. Papers about advancements in pattern recognition techniques, intelligent algorithms, automated data analysis, sensor-fusion techniques, and smart sensing, which focus on existing issues in biomedical sensing and diagnostics, are welcomed.

Prof. Dr. Ricardo Colomo-Palacios
Prof. Dr. Juan A. Gómez-Pulido
Dr. Alfredo J. Pérez
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. Applied Sciences 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 1500 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.


  • extraction information from biomedical sensors
  • Internet of Things
  • biomedical data
  • cloud computing in health
  • data mining and big data analysis
  • intelligent systems for health
  • machine and deep learning
  • diagnostic and predictive analytics
  • health systems, healthcare, and wellness
  • activity recognition in health care
  • data authentication and security
  • privacy-preserving systems for healthcare

Published Papers (1 paper)

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Open AccessArticle An Agile Approach to Improve the Usability of a Physical Telerehabilitation Platform
Appl. Sci. 2019, 9(3), 480; https://doi.org/10.3390/app9030480
Received: 29 November 2018 / Revised: 28 December 2018 / Accepted: 2 January 2019 / Published: 30 January 2019
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The goal of a telerehabilitation platform is to safely and securely facilitate the rehabilitation of patients through the use of telecommunication technologies complemented with the use of biomedical smart sensors. The purpose of this study was to perform a usability evaluation of a [...] Read more.
The goal of a telerehabilitation platform is to safely and securely facilitate the rehabilitation of patients through the use of telecommunication technologies complemented with the use of biomedical smart sensors. The purpose of this study was to perform a usability evaluation of a telerehabilitation platform. To improve the level of usability, the researchers developed and proposed an iterative process. The platform uses a digital representation of the patient which duplicates the therapeutic exercise being executed by the patient; this is detected by a Kinect camera and sensors in real time. This study used inspection methods to perform a usability evaluation of an exploratory prototype of a telerehabilitation platform. In addition, a cognitive workload assessment was performed to complement the usability evaluation. Users were involved through all the stages of the iterative refinement process. Usability issues were progressively reduced from the first iteration to the fourth iteration according to improvements which were developed and applied by the experts. Usability issues originally cataloged as catastrophic were reduced to zero, major usability problems were reduced to ten (2.75%) and minor usability problems were decreased to 141 (38.74%). This study also intends to serve as a guide to improve the usability of e-Health systems in alignment with the software development cycle. Full article
(This article belongs to the Special Issue Intelligent Health Services Based on Biomedical Smart Sensors)

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