MEDiSN

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MEDiSN: medical emergency detection in sensor networks

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Conference On Embedded Networked Sensor Systems archive
Proceedings of the 6th ACM conference on Embedded network sensor systems table of contents

Raleigh, NC, USA

DEMONSTRATION SESSION: Demonstrations table of contents

Pages 361-362

Year of Publication: 2008

ISBN:978-1-59593-990-6

Authors

JeongGil Ko	Johns Hopkins University, Baltimore, MD, USA
Rǎzvan Musǎloiu-Elefteri	Johns Hopkins University, Baltimore, MD, USA
Jong Hyun Lim	Johns Hopkins University, Baltimore, MD, USA
Yin Chen	Johns Hopkins University, Baltimore, MD, USA
Andreas Terzis	Johns Hopkins University, Baltimore, MD, USA
Tia Gao	AID-Networks, Rockville, MD, USA
Walt Destler	AID-Networks, Rockville, MD, USA
Leo Selavo	University of Latvia, Riga, Latvia

Sponsors

SIGCOMM: ACM Special Interest Group on Data Communication
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGOPS: ACM Special Interest Group on Operating Systems
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
SIGBED: ACM Special Interest Group on Embedded Systems

Publisher

ACM New York, NY, USA

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ABSTRACT

Staff shortages and an increasingly aging population are straining the ability of emergency departments to provide high-quality care. Moreover, there is a growing concern about the ability of hospitals to provide effective care during disaster events. Tools that automate patient monitoring would greatly improve efficiency, quality of care, and the volume of patients treated. Towards this goal, we have developed MEDiSN, a wireless sensor network for monitoring patients' vital signs in hospitals and disaster events. MEDiSN consists of Patient Monitors which are custom-built, patient-worn motes that sample, compress and secure medical data, and Relay Points that form a static multi-hop wireless backbone for carrying patient data. Moreover, MEDiSN includes a back-end server that persistently stores medical data and presents them to multiple GUI clients. MEDiSN's heterogeneous architecture enables it to address the compound challenge of reliably delivering large volumes of data while meeting the application's QoS requirements.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	The Aging Population and Its Needs, IEEE Pervasive Computing, v.3 n.2, p.12-14, April 2004 [doi>10.1109/MPRV.2004.1316812]
	2	American Association of Colleges of Nursing. Nursing Shortage Fact Sheet. Available at: http://www.aacn.nche.edu/Media/Backgrounders/shortagefacts.htm, March 2004.
	3	The Center for Disease Control. Press Release: Visits to U.S. Emergency Departments at All-Time High; Number of Departments Shrinking. Available at: http://www.cdc.gov/od/oc/media/pressrel/r050526.htm, May 2005.
	4	R. Fonseca, O. Gnawali, K. Jamieson, S. Kim, P. Levis, A. Woo, "The Collection Tree Protocol (CTP)," TEP 123 Draft, 2006
	5	D. Malan, T. Fulford-Jones, M. Welsh, S. Moulton, "CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care," in proc. International Workshop on Wearable and Implantable Body Sensor Networks, 2004.