Signal Processing - March 2016 - 59
SIGNAL PROCESSING FOR ASSISTED LIVING
Klaus Witrisal, Paul Meissner, Erik Leitinger, Yuan Shen,
Carl Gustafson, Fredrik Tufvesson, Katsuyuki Haneda, Davide Dardari,
Andreas F. Molisch, Andrea Conti, and Moe Z. Win
High-Accuracy Localization for Assisted Living
5G systems will turn multipath channels from foe to friend
IMAGE LICENSED BY INGRAM PUBLISHING,
WOMAN-© ISTOCKPHOTO.COM/SILVIAJANSEN
A
sisted living (AL) technologies, enabled by technical advances such as the advent of the
Internet of Things, are increasingly gaining importance in our aging society. This article discusses the potential of future high-accuracy localization systems as a key component of AL applications. Accurate location information can be tremendously useful to
realize, e.g., behavioral monitoring, fall detection, and real-time assistance. Such services are expected to provide older adults and people with disabilities with more independence and thus to
reduce the cost of caretaking. Total cost of ownership and
ease of installation are paramount to make sensor systems for AL viable. In case of a radio-based indoor
localization system, this implies that a conventional solution is unlikely to gain widespread
adoption because of its requirement to install
multiple fixed nodes (anchors) in each room.
This article therefore places its focus on 1)
discussing radiolocalization methods that
reduce the required infrastructure by
exploiting information from reflected multipath components (MPCs) and 2) showing that knowledge about the propagation
environment enables localization with high
accuracy and robustness. It is demonstrated
that new millimeter-wave (mm-wave) technology, under investigation for 5G communications systems, will be able to provide
centimeter (cm)-accuracy indoor localization in
a robust manner, ideally suited for AL.
Introduction
Digital Object Identifier 10.1109/MSP.2015.2504328
Date of publication: 7 March 2016
1053-5888/16©2016IEEE
The robust provisioning of accurate location information is
a key enabler for AL systems. A recent survey on ambient intelligence in health care [1] illustrates the wide range of applications that
could be supported by a cm-accuracy indoor positioning system alone: activity
recognition, behavioral pattern discovery, anomaly detection, and decision support methods
can all be based on such a sensor modality. Application examples include behavioral monitoring to assess the physical and mental health of individuals, emergency (fall) detection to
alert caretakers or emergency services, real-time assistance to provide context awareness to
medication management systems (as a reminder-for instance-to take medications
IEEE SIgnal ProcESSIng MagazInE
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March 2016
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59
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Table of Contents for the Digital Edition of Signal Processing - March 2016
Signal Processing - March 2016 - Cover1
Signal Processing - March 2016 - Cover2
Signal Processing - March 2016 - 1
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Signal Processing - March 2016 - Cover3
Signal Processing - March 2016 - Cover4
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