Distributed healthcare: Simultaneous assessment of multiple individuals

Tamara L. Hayes; Misha Pavel; Nicole Larimer; Ishan A. Tsay; John Nutt; Andre Gustavo Adami

doi:10.1109/MPRV.2007.9

Distributed healthcare: Simultaneous assessment of multiple individuals

Tamara L. Hayes
, Misha Pavel
, Nicole Larimer
, Ishan A. Tsay
, John Nutt
, Andre Gustavo Adami

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

The use of pervasive technologies to enable continuous patient monitoring and assessment in various setting outside of hospitals, lowering healthcare costs and allowing early detection of problems is discussed. A modified security system technology is a less obstructive alternative for home monitoring. Recent advances in wireless systems provide the basis for a realistic development and deployment of systems to support behavioral monitoring in multiperson homes. Statistical pattern-recognition and machine-learning algorithm integrate noisy and unreliable sensor data with the situation's context and dynamics. A hidden Markov Model can enhance the state estimation provided by modeling only the RSSI probabilities.

Original language	English (US)
Pages (from-to)	36-43
Number of pages	8
Journal	IEEE Pervasive Computing
Volume	6
Issue number	1
DOIs	https://doi.org/10.1109/MPRV.2007.9
State	Published - Jan 2007

Funding

Intel, the Kinetics Foundation, and the National Institute on Aging (P30AG08017) supported this work in part. The Oregon Roybal Center for Aging and Technology (ORCATECH) developed the motion-monitoring system used in this study as part of its ongoing studies. We thank the reviewers for their helpful suggestions in improving the manuscript.

Funders	Funder number
National Institute of Aging	P30AG08017
Kinetics Foundation

ASJC Scopus subject areas

Software
Computer Science Applications
Computational Theory and Mathematics

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10.1109/MPRV.2007.9

Cite this

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abstract = "The use of pervasive technologies to enable continuous patient monitoring and assessment in various setting outside of hospitals, lowering healthcare costs and allowing early detection of problems is discussed. A modified security system technology is a less obstructive alternative for home monitoring. Recent advances in wireless systems provide the basis for a realistic development and deployment of systems to support behavioral monitoring in multiperson homes. Statistical pattern-recognition and machine-learning algorithm integrate noisy and unreliable sensor data with the situation's context and dynamics. A hidden Markov Model can enhance the state estimation provided by modeling only the RSSI probabilities.",

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AU - Nutt, John

AU - Adami, Andre Gustavo

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Distributed healthcare: Simultaneous assessment of multiple individuals

Abstract

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