Optimal Sensing for Patient Health Monitoring

Daniel Miller, Zhengyuan Zhou, Nicholas Bambos, Irad Ben-Gal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper, we construct a framework for optimally sensing a patient's health state with a wireless body area network (WBAN). In such a resource-constrained paradigm, it is often necessary to use lower performance sensing modes, conditionally reducing system performance to increase efficiency and maximize system lifetime. The optimal control architecture trades between shallow and deep sensing modes according to the estimated patient health state, minimizing the expected costs over future states. We construct an implicit formulation for deriving the optimal sensing policy via dynamic programming, an easily implemented myopic sensing policy, and a useful performance bound for evaluating near-optimal approximate sensing policies. We further provide an Monte Carlo experimental evaluation of how such policies depend on key model parameters.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538631805
DOIs
StatePublished - 27 Jul 2018
Event2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States
Duration: 20 May 201824 May 2018

Publication series

NameIEEE International Conference on Communications
Volume2018-May
ISSN (Print)1550-3607

Conference

Conference2018 IEEE International Conference on Communications, ICC 2018
Country/TerritoryUnited States
CityKansas City
Period20/05/1824/05/18

Funding

FundersFunder number
Stanford University

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