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Cited by 233

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

MEDiSN: Medical emergency detection in sensor networks

Ko, Jeonggil, Lim, Jong Hyun, Chen, Yin, Musvaloiu-E, Rvăzvan, Terzis, Andreas, Masson, Gerald M., Gao, Tia, Destler, Walt, Selavo, Leo, Dutton, Richard P.·2010·ACM Transactions on Embedded Computing Systems

Abstract

Staff shortages and an increasingly aging population are straining the ability of emergency departments to provide high quality care. At the same time, there is a growing concern about hospitals' ability to provide effective care during disaster events. For these reasons, tools that automate patient monitoring have the potential to greatly improve efficiency and quality of health care. Towards this goal, we have developed MEDiSN , a wireless sensor network for monitoring patients' physiological data in hospitals and during disaster events. MEDiSN comprises Physiological Monitors (PMs), which are custom-built, patient-worn motes that sample, encrypt, and sign physiological data and Relay Points (RPs) that self-organize into a multi-hop wireless backbone for carrying physiological data. Moreover, MEDiSN includes a back-end server that persistently stores medical data and presents them to authenticated GUI clients. The combination of MEDiSN's two-tier architecture and optimized rate control protocols allows it to address the compound challenge of reliably delivering large volumes of data while meeting the application's QoS requirements. Results from extensive simulations, testbed experiments, and multiple pilot hospital deployments show that MEDiSN can scale from tens to at least five hundred PMs, effectively protect application packets from congestive and corruptive losses, and deliver medically actionable data.

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Metadata

Authors
Ko, J., Lim, J. H., Chen, Y., Musvaloiu-E, R., Terzis, A., Masson, G. M., Gao, T., Destler, W., Selavo, L., & Dutton, R. P.
Venue
ACM Transactions on Embedded Computing Systems
Published
2010-08
Volume
10
Issue
1
Pages
1-29
ISSN
  • 1539-9087 (ISSN-L)
  • 1558-3465
OpenAlex
W1975347960
Cited by
233
References
1
FWCI
12.74
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: MEDiSN: Medical emergency detection in sensor networks. https://app.cochat.ai/papers/10.1145/1814539.1814550
The paper
Ko, J., Lim, J. H., Chen, Y., Musvaloiu-E, R., Terzis, A., Masson, G. M., Gao, T., Destler, W., Selavo, L., & Dutton, R. P. (2010). MEDiSN: Medical emergency detection in sensor networks. ACM Transactions on Embedded Computing Systems. https://doi.org/10.1145/1814539.1814550

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.