An application of sensor networks with data mining to patient controlled analgesia

Yuh-Jyh Hu*, Rong Hong Jan, Kuo-Chen Wang, Yu-Chee Tseng, Tien Hsiung Ku, Shu Fen Yang, Hung Shan Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

We designed an information integration system, iPCA, which combined wireless sensor networks with a data mining system, to help anesthesiologists provide better post-operative pain control. To reduce labor work and to collect analgesic usage information and physiological data efficiently, we connected three kinds of medical instruments with Zigbee nodes through IEEE 802.11 and Zigbee networks. We developed a positioning system that allowed the medical staff to monitor the patient's locations, so they could give immediate care when necessary. The data mining system in iPCA analyzed the patient data, and made reasonable predictions about the total analgesic dosage and the need for PCA control readjustments. We completed a prototype of iPCA, which could help the medical staff monitor the patient's health conditions and locations, and provide the anesthesiologists with useful hypotheses for better PCA control to increase patient satisfactions.

Original languageEnglish
Title of host publication12th IEEE International Conference on e-Health Networking, Application and Services, Healthcom 2010
DOIs
StatePublished - 19 Oct 2010
Event12th IEEE International Conference on e-Health Networking, Application and Services, Healthcom 2010 - Lyon, France
Duration: 1 Jul 20103 Jul 2010

Publication series

Name12th IEEE International Conference on e-Health Networking, Application and Services, Healthcom 2010

Conference

Conference12th IEEE International Conference on e-Health Networking, Application and Services, Healthcom 2010
CountryFrance
CityLyon
Period1/07/103/07/10

Keywords

  • Bagging
  • Data mining
  • PCA
  • Sensor networks

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