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Intelligent IoT-Based E-health Systems for a Higher Inclusion of Vulnerable People

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 14605

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Special Issue Editors

Prof. Dr. Oresti Banos

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Guest Editor

Research Center for Information and Communication Technologies, University of Granada, 18014 Granada, Spain
Interests: wearable, ubiquitous, and mobile computing; artificial intelligence; data mining; digital health
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Prof. Dr. Jesús Peral

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Guest Editor

Department of Software and Computing Systems, University of Alicante, Spain
Interests: multidimensional databases, business intelligence, data mining and information integration; natural language processing (NLP), specifically in syntactic analysis and solving linguistic phenomena (i.e., ellipsis and anaphora)
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Prof. Dr. David Gil

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Guest Editor

Department of Computing Technology and Data Processing, University of Alicante, Spain
Interests: artificial intelligence applications (such as artificial neural networks, support vector machines, decision trees, and so on); data mining applications; Big Data; Internet of things; diagnosis and decision support system in medical and cognitive sciences
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Prof. Dr. Javi Medina Quero

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Guest Editor

Department of Computer Science, University of Jaén, 23071 Jaén, Spain
Interests: intelligent systems for Internet of Things, which encompasses knowledge base systems with fuzzy logic, deep learning for temporal processing and fusion of sensor data and advanced architectures for ubiquitous computing and ambient intelligence in e-Health
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Special Issue Information

Dear Colleagues,

As guest editors, we are most pleased to present our Special Issue on Intelligent IoT-based e-Health Systems for a Greater Inclusion of Disabled People. At present, new trends in intelligent systems and IoT devices are changing traditional health systems by facilitating the development of services that help in assisting a greater number of patients. The current challenge is, however, to develop personalized health services improving the precision and quality of generalized treatments for specific sectors of the population. The objective of this Special Issue is to contribute to the development of a new generation of inclusive health systems focused on people with disabilities (PWD), whose conditions of vulnerability require personalized and specialized services. For this reason, this issue seeks to explore the capabilities of IoT while monitoring the daily activities of PWD at home, within hospital or other facilities. Specifically, the new generation of non-invasive devices, such as textile, mobile, and ambient devices in smart environments and health infrastructures, is regarded as the main data source to be processed by machine learning models in order to:

prevent risk conditions of patients in the environment;
ensure the adherence of rehabilitation and prevention treatments;
iincrease the capacity of autonomy within smart environments;
increase knowledge and learning about the disease and treatments of caregivers and patients.

Potential users of such technologies are people with any type of disability, people with visual or hearing disabilities, people with mental disorders or cognitive limitations (e.g., autistic spectrum disorders), elderly people with dementia, Alzheimer’s or Parkinson’s, people with partially or totally reduced mobility, and people with other cognitive deficits.

In this Special Issue, we call for high-quality research papers as well as review articles that address the development of intelligent health systems based on IoT technology for PWD under the following topics (see keywords).

Prof. Dr. Oresti Banos
Prof. Dr. Jesús Peral
Prof. Dr. David Gil
Prof. Dr. Javi Medina Quero
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. International Journal of Environmental Research and Public Health 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 2500 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

Wearable, mobile, and ubiquitous health sensing systems for PWD
IoT platforms for health monitoring of PWD
IoT-based decision support systems for caregivers and specialists for PWD
IoT for improving autonomy of PWD
IoT-based remote rehabilitation systems for PWD
Benchmarking, datasets, and simulation tools for PWD

Published Papers (4 papers)

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Research

25 pages, 19693 KiB

Open AccessArticle

MoSIoT: Modeling and Simulating IoT Healthcare-Monitoring Systems for People with Disabilities

by Santiago Meliá, Shahabadin Nasabeh, Sergio Luján-Mora and Cristina Cachero

Int. J. Environ. Res. Public Health 2021, 18(12), 6357; https://doi.org/10.3390/ijerph18126357 - 11 Jun 2021

Cited by 12 | Viewed by 3738

Abstract

The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer’s disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central. Full article

(This article belongs to the Special Issue Intelligent IoT-Based E-health Systems for a Higher Inclusion of Vulnerable People)

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22 pages, 3545 KiB

Open AccessArticle

An Agile Digital Platform to Support Population Health—A Case Study of a Digital Platform to Support Patients with Delirium Using IoT, NLP, and AI

by Mohan R. Tanniru, Nimit Agarwal, Amanda Sokan and Salim Hariri

Int. J. Environ. Res. Public Health 2021, 18(11), 5686; https://doi.org/10.3390/ijerph18115686 - 26 May 2021

Cited by 6 | Viewed by 3700

Abstract

For an organization to be customer centric and service oriented requires that it use each encounter with a customer to create value, leverage advanced technologies to design digital services to fulfill the value, and assess perceived value-in-use to continue to revise the value as customer expectations evolve. The adaptation of value cycles to address the rapid changes in customer expectations requires agile digital platforms with dynamic software ecosystems interacting with multiple actors. For public health agencies focused on population health, these agile digital platforms should provide tailored care to address the distinct needs of select population groups. Using prior research on aging and dynamic software ecosystems, this paper develops a template for the design of an agile digital platform to support value cycle activities among clinical and non-clinical actors, including population groups. It illustrates the design of an agile digital platform to support clients that suffer from delirium, using digital services that leverage Internet of Things, natural language processing, and AI that uses real-time data for learning and care adaption. We conclude the paper with directions for future research. Full article

(This article belongs to the Special Issue Intelligent IoT-Based E-health Systems for a Higher Inclusion of Vulnerable People)

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12 pages, 806 KiB

Open AccessArticle

Movement Patterns in Students Diagnosed with ADHD, Objective Measurement in a Natural Learning Environment

by Mireia Sempere-Tortosa, Francisco Fernández-Carrasco, Ignasi Navarro-Soria and Carlos Rizo-Maestre

Int. J. Environ. Res. Public Health 2021, 18(8), 3870; https://doi.org/10.3390/ijerph18083870 - 07 Apr 2021

Cited by 9 | Viewed by 3086

Abstract

Attention deficit hyperactivity disorder is the most common neuropsychological disorder in childhood and adolescence, affecting the basic psychological processes involved in learning, social adaptation and affective adjustment. From previous research, the disorder is linked to problems in different areas of development, with deficiencies in psychological processes leading to the development of the most common characteristics of the disorder such as inattention, excess of activity and lack of inhibitory control. As for the diagnosis, in spite of being a very frequent disorder, there are multiple controversies about which tools are the most suitable for evaluation. One of the most widespread tools in the professional field is behavior inventories such as the Strengths and Difficulties Questionnaires for Parents and Teachers or the ADHD Rating Scale-V. The main disadvantage of these assessment tools is that they do not provide an objective observation. For this reason, there are different studies focused on recording objective measures of the subjects’ movement, since hyperkinesia is one of the most characteristic symptoms of this disorder. In this sense, we have developed an application that, using a Kinect device, is capable of measuring the movement of the different parts of the body of up to six subjects in the classroom, being a natural context for the student. The main objective of this work is twofold, on the one hand, to investigate whether there are correlations between excessive movement and high scores in the inventories for the diagnosis of ADHD, Rating Scale-V and Strengths and Difficulties Questionnaire (SDQ) and, on the other hand, to determine which sections of the body present the most significant mobility in subjects diagnosed with ADHD. Results show that the control group, composed of neurotypical subjects, presents less kinaesthetic activity than the clinical group diagnosed with ADHD. This indicates that the experimental group presents one of the main characteristics of the disorder. In addition, results also show that practically all the measured body parts present significant differences, being higher in the clinical group, highlighting the head as the joint with the highest effect size. Full article

(This article belongs to the Special Issue Intelligent IoT-Based E-health Systems for a Higher Inclusion of Vulnerable People)

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24 pages, 29952 KiB

Open AccessArticle

Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices

by Antonio-Pedro Albín-Rodríguez, Adrián-Jesús Ricoy-Cano, Yolanda-María de-la-Fuente-Robles and Macarena Espinilla-Estévez

Int. J. Environ. Res. Public Health 2020, 17(18), 6752; https://doi.org/10.3390/ijerph17186752 - 16 Sep 2020

Cited by 10 | Viewed by 2833

Abstract

Hyperactive behaviour refers to a person making more movement than expected for his or her age and development, acting impulsively, and being easily distracted. There is a need to encourage early and reliable detection through the proposal of new methodologies and systems in the context of hyperactive behaviour to prevent or lessen related problems and disorders. This paper presents a methodology to compute a fuzzy protoform (a linguistic description) as an estimator for hyperactive behaviour. The proposed methodology is developed in a system called Smart HyBeDe, which integrate non-invasive and commercial wearable devices, such as activity bracelets, in order to capture data streams from inertial measurement units and optical heart rate sensors. The generated data by the wearable device are synchronized with a mobile device to process the fuzzy protoform to inform family members and professionals. Three datasets generated by the wearable device in real contexts are presented. These datasets are used to evaluate the impact of wrist choice for the wearable device, multiple fuzzy temporal windows, different aggregation operators, and relevant linguistic terms to define the fuzzy protoform as an estimator for the hyperactive behaviour. The results, analysed by a hyperactive behaviour expert, show that the proposed protoform is a suitable hyperactive behaviour estimator. Full article

(This article belongs to the Special Issue Intelligent IoT-Based E-health Systems for a Higher Inclusion of Vulnerable People)

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