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

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.