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 journalArticle

37 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)36-43
Number of pages8
JournalIEEE Pervasive Computing
Volume6
Issue number1
DOIs
StatePublished - Jan 2007

Fingerprint

Patient monitoring
Monitoring
State estimation
Hidden Markov models
Security systems
Learning algorithms
Pattern recognition
Learning systems
Sensors
Costs

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Networks and Communications

Cite this

Distributed healthcare : Simultaneous assessment of multiple individuals. / Hayes, Tamara L.; Pavel, Misha; Larimer, Nicole; Tsay, Ishan A.; Nutt, John; Adami, Andre Gustavo.

In: IEEE Pervasive Computing, Vol. 6, No. 1, 01.2007, p. 36-43.

Research output: Contribution to journalArticle

Hayes, Tamara L. ; Pavel, Misha ; Larimer, Nicole ; Tsay, Ishan A. ; Nutt, John ; Adami, Andre Gustavo. / Distributed healthcare : Simultaneous assessment of multiple individuals. In: IEEE Pervasive Computing. 2007 ; Vol. 6, No. 1. pp. 36-43.
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