Special Issue "Wearable and Ambient Sensors for Healthcare and Wellness Applications 2018"
Deadline for manuscript submissions: closed (1 September 2018).
Prof. Edward Sazonov
Departments of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, USA
Website | E-Mail
Interests: Wearable Sensors; Behavioural Health Informatics; Sensors for Dietary Assessment; Sensors for Smoking Assessment and Cessation; Technology-Driven Interventions; Smart Orthoses and Prostheses; Machine Learning; Deep Learning; Signal Processing
Human-centered sensor technologies are rapidly evolving and extending their reach to critical applications of wellness and healthcare. Ambient sensors integrate into the home, office, or point-of-care environments, and allows for transparent, unobtrusive monitoring for sensitive populations. Wearable technologies allow to extend monitoring into the community and have been used in many research and clinical applications, including monitoring of healthy, elderly and frail individuals, measuring levels of physical activity in disease-association studies, and so on. Combined, ambient and wearable sensors create unique capabilities of continuous monitoring of physiological health indicators and health-related behaviors at home and in the community. Real-time sensing, signal processing, recognition, characterization and interpretation of health metrics and behaviors form sensor data present a challenging problem. Measured variables of interest quite often are contaminated with artifacts originating from activities of daily living, the complexity and variability of real-life behaviors complicate the inference of the information of interest. Substantial advances in the sensor technology and sensor informatics are needed to develop practically deployable solutions relying on ambient and wearable sensors.
The goal of this Special Issue is to highlight state-of-the-art applications of ambient and wearable sensors with focus on wellness and healthcare applications of the technology. Of special interest is research work that combines ambient and wearable sensing approaches into a unified framework; applications of wearable and/or ambient sensors for continuous assessment of physiology or behaviors; use of sensors in just-in-time interventions. Additionally of interest are advances in the design of the on-body and ambient sensors; wearable biomedical and physiological sensors; associated electronics and software; signal processing; pattern recognition; analysis of high-density sensor data; inferring health and behavioral states from the sensor data; application of ambient and wearable sensors in wellness and healthcare; advances in technologies for ambient assisted living; healthcare and wellness applications based on Internet of Things (IoT) technologies.
Prof. Dr. Subhas Chandra Mukhopadhyay
Prof. Dr. Edward Sazonov
Manuscript Submission Information
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