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This book summarizes various approaches for theautomatic detection of health threats to older patients at home living alone. Thetext begins by briefly describing those who would most benefit from healthcaresupervision. The book then summarizes possible scenarios for monitoring anolder patient at home, deriving the common functional requirements formonitoring technology. Next, the work identifies the state of the art oftechnological monitoring approaches that are practically applicable to geriatricpatients. A survey is presented on a range of such interdisciplinary fields assmart homes, telemonitoring, ambient intelligence, ambient assisted living,gerontechnology, and aging-in-place technology. The book discusses relevantexperimental studies, highlighting the application of sensor fusion, signalprocessing and machine learning techniques. Finally, the text discusses futurechallenges, offering a number of suggestions for further research directions.
List of contents
Introduction.- Reviews and Taxonomies.- Relevant Scenarios for Home Monitoring Solutions for Older Adults.- Monitoring Technology.- Datasets.- Discussion.- Conclusion.
About the author
Juris
Klonovs is a PhD student in the Department of Mechanical and
Manufacturing Engineering at Aalborg University Copenhagen, Denmark.
Mohammad
A. Haque is a PhD Fellow in the Department of Architecture, Design and Media
Technology at Aalborg University, Aalborg, Denmark.
Dr. Volker
Krueger is a Professor and Head of the Robotics, Vision and Machine
Intelligence group in the Department of Mechanical and Manufacturing
Engineering at Aalborg University Copenhagen, Denmark. His other publications
include the Springer title Visual
Analysis of Humans – Looking at People.
Dr. Kamal
Nasrollahi is an Associate Professor in Computer Vision in the Department of Architecture, Design and Media
Technology at Aalborg University, Aalborg, Denmark.
Dr. Karen
Andersen-Ranberg is an Associate Professor in the Danish Aging Research Center at the University of
Southern Denmark, Odense, Denmark. She is also a Specialist Consultant in
Geriatrics and Internal Medicine at Odense University Hospital.
Dr.
Thomas B. Moeslund is a Professor in the Department of Architecture, Design and Media
Technology at Aalborg University, Denmark, where he serves as Head
of Media Technology, and Head of the Visual Analysis of People Lab. His other
publications include the Springer titles Computer
Vision in Sports, Introduction to
Video and Image Processing, and Visual
Analysis of Humans – Looking at People.
Dr.
Erika G. Spaich is an Associate Professor
in the Department of Health
Science and Technology at Aalborg University, Aalborg, Denmark.
Summary
This book summarizes various approaches for the
automatic detection of health threats to older patients at home living alone. The
text begins by briefly describing those who would most benefit from healthcare
supervision. The book then summarizes possible scenarios for monitoring an
older patient at home, deriving the common functional requirements for
monitoring technology. Next, the work identifies the state of the art of
technological monitoring approaches that are practically applicable to geriatric
patients. A survey is presented on a range of such interdisciplinary fields as
smart homes, telemonitoring, ambient intelligence, ambient assisted living,
gerontechnology, and aging-in-place technology. The book discusses relevant
experimental studies, highlighting the application of sensor fusion, signal
processing and machine learning techniques. Finally, the text discusses future
challenges, offering a number of suggestions for further research directions.
