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Advances in Sensors for Context-Aware, Mobile and Smart Healthcare
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Advances in Sensors for Context-Aware, Mobile and Smart Healthcare

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

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 20859

Special Issue Editor

Dr. Agusti Solanas

E-Mail Website
Guest Editor
Smart Health Research Group, Department of Computer Engineering and Maths, Universitat Rovira i Virgili, Tarragona, Spain
Interests: smart health; cognitive health; data privacy; ubiquitous computing and AI (artificial intelligence)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensing our surroundings is the essential first step towards the perception and comprehension of the continuously changing context in which we live. Perception is natural and it is given for granted by human beings and living creatures. However, providing non-living systems such as homes, hospitals, or cities with the capability to sense, perceive, and understand themselves and their context is a herculean challenge, which involves disciplines ranging from materials engineering to artificial intelligence.

Context-aware environments are characterized by their capability to sense their surroundings, transform sensations into information, make decisions based on the gathered information and, ultimately, actuate on the environment to modify it. Augmenting environments with context-awareness opens the door to a handful of possibilities in complex sectors like healthcare. For instance, context-aware homes along with mobile healthcare solutions foster the use of remote monitoring for outpatients. Similarly, smart cities embracing the concept of smart health help to improve the health of their citizens by promoting healthier habits, suggesting less congested routes, or controlling pollen levels that affect people with respiratory problems.

Sensors are the fundamental enablers of context-aware environments, and their variety and importance are steadily growing. In this Special Issue, we focus on the design and development of more efficient and reliable sensors for healthcare. Also, considering the emerging market push of the Internet of Things, we pay special attention to the communication challenges that thousands of sensors have to overcome to transmit information in very dense and populated environments. Finally, we are also interested in holistic applications showing real sensors experiments, challenges, and solutions within context-aware healthcare environments.

Dr. Agusti Solanas
Guest Editor

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. 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.

Keywords

  • Context-aware environments in healthcare
  • Sensors for smart hospitals
  • Sensors for smart homes
  • Sensors for smart cities and smart health
  • Sensors in telemedicine and remote monitoring of outpatients
  • Sensors as enablers of context-aware environments
  • Sensors in mobile and smart healthcare applications
  • Efficient and resilient sensors for healthcare
  • Security and privacy in sensors for healthcare

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Published Papers (4 papers)

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Research

60 pages, 1347 KiB  
Article
Sensors for Context-Aware Smart Healthcare: A Security Perspective
by Edgar Batista, M. Angels Moncusi, Pablo López-Aguilar, Antoni Martínez-Ballesté and Agusti Solanas
Sensors 2021, 21(20), 6886; https://doi.org/10.3390/s21206886 - 17 Oct 2021
Cited by 35 | Viewed by 7947
Abstract
The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities [...] Read more.
The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people’s welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare. Full article
(This article belongs to the Special Issue Advances in Sensors for Context-Aware, Mobile and Smart Healthcare)
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17 pages, 887 KiB  
Article
Smart Health-Enhanced Early Mobilisation in Intensive Care Units
by Maria Ferre, Edgar Batista, Agusti Solanas and Antoni Martínez-Ballesté
Sensors 2021, 21(16), 5408; https://doi.org/10.3390/s21165408 - 10 Aug 2021
Cited by 9 | Viewed by 5309
Abstract
Critically ill patients that stay in Intensive Care Units (ICU) for long periods suffer from Post-Intensive Care Syndrome or ICU Acquired Weakness, whose effects can decrease patients’ quality of life for years. To prevent such issues and aiming at shortening intensive care treatments, [...] Read more.
Critically ill patients that stay in Intensive Care Units (ICU) for long periods suffer from Post-Intensive Care Syndrome or ICU Acquired Weakness, whose effects can decrease patients’ quality of life for years. To prevent such issues and aiming at shortening intensive care treatments, Early Mobilisation (EM) has been proposed as an encouraging technique: the literature includes numerous examples of the benefits of EM on the prevention of post-operative complications and adverse events. However, the appropriate application of EM programmes entails the use of scarce resources, both human and technical. Information and Communication Technologies can play a key role in reducing cost and improving the practice of EM. Although there is rich literature on EM practice and its potential benefits, there are some barriers that must be overcome, and technology, i.e., the use of sensors, robotics or information systems, can contribute to that end. This article reviews the literature and analyses on the use of technology in the area of EM, and moreover, it proposes a smart health-enhanced scenario. Full article
(This article belongs to the Special Issue Advances in Sensors for Context-Aware, Mobile and Smart Healthcare)
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18 pages, 3968 KiB  
Article
Field Programmable Gate Array-Embedded Platform for Dynamic Muscle Fiber Conduction Velocity Monitoring
by Daniela De Venuto and Giovanni Mezzina
Sensors 2019, 19(20), 4594; https://doi.org/10.3390/s19204594 - 22 Oct 2019
Cited by 1 | Viewed by 3360
Abstract
This paper proposes a novel architecture of a wearable Field Programmable Gate Array (FPGA)-based platform to dynamically monitor Muscle Fiber Conduction Velocity (MFCV). The system uses a set of wireless sensors for the detection of muscular activation: four surface electromyography electrodes (EMGs) and [...] Read more.
This paper proposes a novel architecture of a wearable Field Programmable Gate Array (FPGA)-based platform to dynamically monitor Muscle Fiber Conduction Velocity (MFCV). The system uses a set of wireless sensors for the detection of muscular activation: four surface electromyography electrodes (EMGs) and two footswitches. The beginning of movement (trigger) is set by sensors (footswitches) detecting the feet position. The MFCV value extraction exploits an iterative algorithm, which compares two 1-bit digitized EMG signals. The EMG electrode positioning is ensured by a dedicated procedure. The architecture is implemented on FPGA board (Altera Cyclone V), which manages an external Bluetooth module for data transmission. The time spent for data elaboration is 63.5 ms ± 0.25 ms, matching real-time requirements. The FPGA-based MFCV estimator has been validated during regular walking and in the fatigue monitoring context. Six healthy subjects contributed to experimental validation. In the gait analysis, the subjects showed MFCV evaluation of about 7.6 m/s ± 0.36 m/s, i.e., <0.1 m/s, a typical value for healthy subjects. Furthermore, in agreement with current research methods in the field, in a fatigue evaluation context, the extracted data showed an MFCV descending trend with the increment of the muscular effort time (Rested: MFCV = 8.51 m/s; Tired: 4.60 m/s). Full article
(This article belongs to the Special Issue Advances in Sensors for Context-Aware, Mobile and Smart Healthcare)
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11 pages, 2492 KiB  
Article
Aptamer-Based Nanoporous Anodic Alumina Interferometric Biosensor for Real-Time Thrombin Detection
by Laura Pol, Laura Karen Acosta, Josep Ferré-Borrull and Lluis F. Marsal
Sensors 2019, 19(20), 4543; https://doi.org/10.3390/s19204543 - 19 Oct 2019
Cited by 22 | Viewed by 3243
Abstract
Aptamer biosensors are one of the most powerful techniques in biosensing. Achieving the best platform to use in aptamer biosensors typically includes crucial chemical modifications that enable aptamer immobilization on the surface in the most efficient manner. These chemical modifications must be well [...] Read more.
Aptamer biosensors are one of the most powerful techniques in biosensing. Achieving the best platform to use in aptamer biosensors typically includes crucial chemical modifications that enable aptamer immobilization on the surface in the most efficient manner. These chemical modifications must be well defined. In this work we propose nanoporous anodic alumina (NAA) chemically modified with streptavidin as a platform for aptamer immobilization. The immobilization of biotinylated thrombin binding aptamer (TBA) was monitored in real time by means of reflective interferometric spectroscopy (RIfS). The study has permitted to characterize in real time the path to immobilize TBA on the inner pore walls of NAA. Furthermore, this study provides an accurate label-free method to detect thrombin in real-time with high affinity and specificity. Full article
(This article belongs to the Special Issue Advances in Sensors for Context-Aware, Mobile and Smart Healthcare)
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