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Application-Focused Energy-Fidelity Scalability for Wireless Motion-Based Health Assessment

Authors:

Mark A. Hanson,

Harry C. Powell, Jr.,

John LachAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 11, Issue S2

Article No.: 50, Pages 1 - 21

https://doi.org/10.1145/2331147.2331160

Published: 01 August 2012 Publication History

Abstract

Energy-fidelity trade-offs are central to the performance of many technologies, but they are essential in wireless body area sensor networks (BASNs) due to severe energy and processing constraints and the critical nature of certain healthcare applications. On-node signal processing and compression techniques can save energy by greatly reducing the amount of data transmitted over the wireless channel, but lossy techniques, capable of high compression ratios, can incur a reduction in application fidelity. In order to maximize system performance, these trade-offs must be considered at runtime due to the dynamic nature of BASN applications, including sensed data, operating environments, user actuation, etc. BASNs therefore require energy-fidelity scalability, so automated and user-initiated trade-offs can be made dynamically. This article presents a data rate scalability framework within a motion-based health application context which demonstrates the design of efficient and efficacious wireless health systems.

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Cited By

Aldeer MJavanmard MMartin R(2018)A Review of Medication Adherence Monitoring TechnologiesApplied System Innovation10.3390/asi10200141:2(14)Online publication date: 6-May-2018
https://doi.org/10.3390/asi1020014
Aldeer MMartin RHoward RBonato PWang H(2017)Tackling the fidelity-energy trade-off in wireless body sensor networksProceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies10.5555/3204094.3204096(7-12)Online publication date: 17-Jul-2017
https://dl.acm.org/doi/10.5555/3204094.3204096
Aldeer MMartin RHoward R(2017)Tackling the Fidelity-Energy Trade-Off in Wireless Body Sensor Networks2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE.2017.52(7-12)Online publication date: Jul-2017
https://doi.org/10.1109/CHASE.2017.52
Show More Cited By

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Application-Focused Energy-Fidelity Scalability for Wireless Motion-Based Health Assessment

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Information

Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 11, Issue S2

Special Section on CAPA'09, Special Section on WHS'09, and Special Section VCPSS' 09

August 2012

396 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/2331147

Issue’s Table of Contents

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 01 August 2012

Accepted: 01 September 2010

Revised: 01 June 2010

Received: 01 October 2009

Published in TECS Volume 11, Issue S2

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Cited By

Aldeer MJavanmard MMartin R(2018)A Review of Medication Adherence Monitoring TechnologiesApplied System Innovation10.3390/asi10200141:2(14)Online publication date: 6-May-2018
https://doi.org/10.3390/asi1020014
Aldeer MMartin RHoward RBonato PWang H(2017)Tackling the fidelity-energy trade-off in wireless body sensor networksProceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies10.5555/3204094.3204096(7-12)Online publication date: 17-Jul-2017
https://dl.acm.org/doi/10.5555/3204094.3204096
Aldeer MMartin RHoward R(2017)Tackling the Fidelity-Energy Trade-Off in Wireless Body Sensor Networks2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE.2017.52(7-12)Online publication date: Jul-2017
https://doi.org/10.1109/CHASE.2017.52
Oneto LOrtiz JAnguita D(2017)Constraint-Aware Data Analysis on Mobile DevicesAdaptive Mobile Computing10.1016/B978-0-12-804603-6.00007-3(127-149)Online publication date: 2017
https://doi.org/10.1016/B978-0-12-804603-6.00007-3
Oneto LRidella SAnguita D(2016)Learning Hardware-Friendly Classifiers Through Algorithmic StabilityACM Transactions on Embedded Computing Systems10.1145/283616515:2(1-29)Online publication date: 29-Jan-2016
https://dl.acm.org/doi/10.1145/2836165
Jensen UBlank PKugler PEskofier B(2016)Unobtrusive and Energy-Efficient Swimming Exercise Tracking Using On-Node ProcessingIEEE Sensors Journal10.1109/JSEN.2016.253001916:10(3972-3980)Online publication date: May-2016
https://doi.org/10.1109/JSEN.2016.2530019
Gong JLach J(2013)Reconfigurable differentiall accelerometer platform for inertial body sensor networks2013 IEEE SENSORS10.1109/ICSENS.2013.6688327(1-4)Online publication date: Nov-2013
https://doi.org/10.1109/ICSENS.2013.6688327
Kugler PNordhus PEskofier B(2013)Shimmer, Cooja and Contiki: A new toolset for the simulation of on-node signal processing algorithms2013 IEEE International Conference on Body Sensor Networks10.1109/BSN.2013.6575497(1-6)Online publication date: May-2013
https://doi.org/10.1109/BSN.2013.6575497

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