Smart Monitoring Systems for Diagnosis of Anaesthesia Related Events

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Details

Health care professionals often rely on their knowledge and experience together with observations and measurements to make clinical judgments and plan appropriate therapy regimes. In many circumstances, however, intuitive decision-making fails to achieve the optimal balance under competing or conflicting care delivery demands. In certain circumstances a medical professional may be overloaded by patient data from the monitoring equipment and its analysis. Computers have the capability to monitor large volumes of diverse data rapidly, whereas humans are only able to monitor a maximum of seven different parameters at any one time. Computer programs employing fuzzy logic are intended to imitate human thought processes in complex circumstances, but to function at greater speed. This book explains the development of a computer system that has more clinical relevance and has the ability to help the clinician, and can do this in a more user-friendly manner. This research work involved using two different techniques: fuzzy logic with the capability to handle the complex build with high accuracy, and the widely used industrial software called SCADA.

Autorentext

Mirza Mansoor Baig has received his BE in Electrical and Electronics Engineering from JNTU University, India in 2007 and ME (Hons) in EEE from Auckland University of Technology, Auckland, NZ in 2010. He has published many international journals and conferences. He also received several scholarships and awards.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659366475
    • Genre Elektrotechnik
    • Sprache Englisch
    • Anzahl Seiten 280
    • Größe H220mm x B150mm x T18mm
    • Jahr 2013
    • EAN 9783659366475
    • Format Kartonierter Einband
    • ISBN 3659366471
    • Veröffentlichung 24.04.2013
    • Titel Smart Monitoring Systems for Diagnosis of Anaesthesia Related Events
    • Autor Mirza Mansoor Baig
    • Untertitel A Computerized Anaesthesia Monitoring & Diagnostic System using Fuzzy Logic Modelling
    • Gewicht 435g
    • Herausgeber LAP LAMBERT Academic Publishing

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