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Sustainable Sensor Systems for Remote Health Monitoring
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Sustainable Sensor Systems for Remote Health Monitoring

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 6037

Special Issue Editors

Prof. Dr. Giorgio Pennazza

E-Mail Website
Guest Editor
Department of Engineering, Campus Bio-Medico University of Rome, 00128 Rome, Italy
Interests: chemical sensors;electronic interface;smart sensors;sensor network
Special Issues, Collections and Topics in MDPI journals
Dr. Anna Sabatini

E-Mail Website
Guest Editor
Computer Systems and Bioinformatics Lab, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Roma, Italy
Interests: embedded systems; graph signal processing; electronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With an increasing elderly population and with an increased incidence of multiple chronic diseases, there is a growing need for more advanced sensor systems to monitor health conditions. 

The focus of this Special Issue is on “Sustainable Sensor Systems for Remote Health Monitoring”.

Distributing autonomous low-power sensing nodes can be useful to monitor the health state condition of both fragile and healthy people. Physiological parameters such as heart rate, respiratory rate, motion, daily life activities, and specific compound concentration can be tracked. 

Sensor networks allow monitoring the population of a specific area and eventually correlate it to the environmental influence.

Predictive and personalized healthcare approaches encourage early detection and prevention of health conditions in subject deterioration.

Topics of interest include biomedical sensor technology and health applications, Internet of Things, embedded systems, but also power management, energy harvesting, and low power systems.

Indeed, energy-efficient deployment of low-power sensor nodes allows developing sensors with a prolonging network life. 

The evaluation of energy, storage, processing, measurement quality, robustness, communication with risk of loss of data (network connectivity, latency, costs, and cybersecurity), but also intelligent decision support to early detection and diagnosis are very thorny aspects.

Main topics:

  • Low-cost sensor
  • Design and development of low-power sensors
  • Intelligent energy harvesting
  • Sensor networks
  • Autonomous health monitoring
  • Medical and biomedical sensing
  • Novel application-specific predictive analytics techniques for sensors

Prof. Dr. Giorgio Pennazza
Dr. Anna Sabatini
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. 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.

Published Papers (2 papers)

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Research

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18 pages, 6122 KiB  
Article
Wearable Ball-Impact Piezoelectric Multi-Converters for Low-Frequency Energy Harvesting from Human Motion
by Alessandro Nastro, Nicola Pienazza, Marco Baù, Pietro Aceti, Markku Rouvala, Raffaele Ardito, Marco Ferrari, Alberto Corigliano and Vittorio Ferrari
Sensors 2022, 22(3), 772; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030772 - 20 Jan 2022
Cited by 16 | Viewed by 2740
Abstract
Multi-converter piezoelectric harvesters based on mono-axial and bi-axial configurations are proposed. The harvesters exploit two and four piezoelectric converters (PCs) and adopt an impinging spherical steel ball to harvest electrical energy from human motion. When the harvester undergoes a shake, a tilt, or [...] Read more.
Multi-converter piezoelectric harvesters based on mono-axial and bi-axial configurations are proposed. The harvesters exploit two and four piezoelectric converters (PCs) and adopt an impinging spherical steel ball to harvest electrical energy from human motion. When the harvester undergoes a shake, a tilt, or a combination of the two, the ball hits one PC, inducing an impact-based frequency-up conversion. Prototypes of the harvesters have been designed, fabricated, fastened to the wrist of a person by means of a wristband and watchband, and experimentally tested for different motion levels. The PCs of the harvesters have been fed to passive diode-based voltage-doubler rectifiers connected in parallel to a storage capacitor, Cs = 220 nF. By employing the mono-axial harvester, after 8.5 s of consecutive impacts induced by rotations of the wrist, a voltage vcs(t) of 40.2 V across the capacitor was obtained, which corresponded to a stored energy of 178 μJ. By employing the bi-axial harvester, the peak instantaneous power provided by the PCs to an optimal resistive load was 1.58 mW, with an average power of 9.65 μW over 0.7 s. The proposed harvesters are suitable to scavenge electrical energy from low-frequency nonperiodical mechanical movements, such as human motion. Full article
(This article belongs to the Special Issue Sustainable Sensor Systems for Remote Health Monitoring)
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Review

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21 pages, 2939 KiB  
Review
Recent Advances in Remote Pulmonary Artery Pressure Monitoring for Patients with Chronic Heart Failure: Current Evidence and Future Perspectives
by Pascal R. D. Clephas, Dilan Aydin, Sumant P. Radhoe and Jasper J. Brugts
Sensors 2023, 23(3), 1364; https://0-doi-org.brum.beds.ac.uk/10.3390/s23031364 - 26 Jan 2023
Cited by 5 | Viewed by 2557
Abstract
Chronic heart failure (HF) is associated with high hospital admission rates and has an enormous burden on hospital resources worldwide. Ideally, detection of worsening HF in an early phase would allow physicians to intervene timely and proactively in order to prevent HF-related hospitalizations, [...] Read more.
Chronic heart failure (HF) is associated with high hospital admission rates and has an enormous burden on hospital resources worldwide. Ideally, detection of worsening HF in an early phase would allow physicians to intervene timely and proactively in order to prevent HF-related hospitalizations, a concept better known as remote hemodynamic monitoring. After years of research, remote monitoring of pulmonary artery pressures (PAP) has emerged as the most successful technique for ambulatory hemodynamic monitoring in HF patients to date. Currently, the CardioMEMS and Cordella HF systems have been tested for pulmonary artery pressure monitoring and the body of evidence has been growing rapidly over the past years. However, several ongoing studies are aiming to fill the gap in evidence that is still very clinically relevant, especially for the European setting. In this comprehensive review, we provide an overview of all available evidence for PAP monitoring as well as a detailed discussion of currently ongoing studies and future perspectives for this promising technique that is likely to impact HF care worldwide. Full article
(This article belongs to the Special Issue Sustainable Sensor Systems for Remote Health Monitoring)
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