Reprint

Mobile Health Technologies for Ambient Assisted Living and Healthcare

Edited by
March 2023
240 pages
  • ISBN978-3-0365-7026-6 (Hardback)
  • ISBN978-3-0365-7027-3 (PDF)

This is a Reprint of the Special Issue Mobile Health Technologies for Ambient Assisted Living and Healthcare that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. This Special Issue’s goal was to bring together academics and professionals in healthcare and medicine interested in using information and communication technologies (ICT) to serve people with special needs. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages. Because mobile devices are commonly used for several everyday chores and are equipped with sensors that monitor various physical and physiological indicators, it is crucial to encourage the development of m-Health and e-Health solutions for healthcare practitioners. In this area, several solutions are now being developed. In addition, they can collaborate with emerging technologies for social assistance while enhancing life quality.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
data privacy; taxonomy; IoT; COVID-19; mobile application; accelerometer sensor; stand-up time; total time; aging; linear-map convolutional neural network; direct acyclic graph; action recognition; spatial feature; temporal feature; frailty; home monitoring; user-centered design; usability; user experience; acceptance; activity recognition; Internet of Things; smart house; deep learning; channel state information; deep learning; glaucoma screening; retinal images; segmentation; classification; precision nutrition; food plans; IoT; machine learning; food logging; Eight Hop Test; systematic review; measurement; sensors; diseases; wrist-wearable device; PPG processing; physiological parameters; web-based applications; data analysis; elderly monitoring; successful aging; mobile application; gerontechnology; AAL; IoT; healthcare; prevalidation; deployment; chronic heart failure; large-scale pilot; H2020

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