Wearable Sensors in Healthcare: Methods, Algorithms, Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 October 2019) | Viewed by 123663
Special Issue Editors
Interests: signal processing and classification of biomedical signals; algorithms and software to improve both performance and usability of continuous glucose monitoring (CGM) sensors; statistical methods and machine learning techniques to analyze big data in medicine
Special Issues, Collections and Topics in MDPI journals
Interests: signal processing and modeling techniques for the analysis of glucose sensor data; strategies for type 1 diabetes insulin therapy optimization; statistical learning; machine-learning techniques applied to clinical predictive model development
Special Issues, Collections and Topics in MDPI journals
Interests: mechatronics for implantable artificial organs (mainly artificial pancreas and artificial bladder systems) with a particular focus on magnetic actuation and sensing for implantable devices; microfabrication; smart magnetic materials; smart microsystems for targeted therapy
Interests: real-time biomedical signal processing, including non-invasive fetal electrocardiography, neural signal decoding for motor neuroprostheses, and electrophysiology of taste; wearable electronics and textile electrodes; tele-health systems
Special Issues, Collections and Topics in MDPI journals
Interests: sensors and algorithms for continuous glucose monitoring; deconvolution and parameter estimation techniques for the study of physiological systems; linear and nonlinear biological time-series analysis; measurement and processing of biomedical signals (EEG, event-related potentials, local field potentials, fNIRS, etc.) for clinical research and applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Wearable sensors enabling the continuous-time monitoring of health-related parameters outside the clinical setting have the potential to revolutionize healthcare. Indeed, wearable sensors, coupled with tailored signal processing algorithms for the extraction of digital biomarkers, often outperform traditional clinical methods in detecting health events. For instance, in people with diabetes, glucose monitoring sensors can detect hypoglycemic events that standard blood tests cannot reveal. Similarly, ambulatory dynamic and long-term electrocardiograms can detect arrhythmias that happen unpredictably throughout the day and thus can be difficult to capture by conventional 10 seconds rest electrocardiography. Wearable sensors have also acquired increasing importance in the field of rehabilitation thanks to the possibility of detecting not only physiological but also movement data.
Data collected by wearable sensors offer a more detailed picture of the patient health status that allows planning personalized interventions with the aim of minimizing potential health risks. When monitoring chronic diseases, this can be done, for example, by telemedicine applications or personalized decision-support systems. Such preventive and personalized medicine applications will potentially change the healthcare system from a reactive to a proactive system.
Given their potentialities, wearable sensors are currently the object of intense research activity, both in academic groups and industries, including multinational IT companies. A broad variety of wearable sensing technologies have been proposed, such as mechanical sensors for tracking movements and pressure, chemical sensors measuring analytes in biological fluids (e.g., interstitial fluids, breath, sweat, saliva, and tears), and other sensors based on electrical, optical, thermal, and acoustic techniques to sense physiological signals.
Although great steps forward have been made in recent years, wearable sensors still need to be improved from both hardware and software points of view, in order to increase their usability, accuracy, and medical utility, and finally integrate them in the healthcare system.
In this Special Issue, we seek original research papers or review papers about algorithms for wearable sensors and their application in the medical field. In particular, we look for contributions on:
- algorithms to enhance the performance of wearable sensors in terms of accuracy and precision (e.g. calibration and filtering algorithms)
- algorithms using wearable sensors data to extract medical knowledge (e.g. event detection or prediction)
- methods to provide personalized interventions (e.g. therapy adjustment, behavioral coaching and biofeedback) based on wearable sensors data.
Prof. Dr. Andrea Facchinetti
Dr. Martina Vettoretti
Dr. Veronica Iacovacci
Prof. Dr. Danilo Pani
Prof. Dr. Giovanni Sparacino
Guest Editors
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