DocumentCode :
2462109
Title :
Locating of the required key-variables to be employed in a ventilation management decision support system
Author :
Tzavaras, A. ; Weller, P.R. ; Prinianakis, G. ; Lahana, A. ; Afentoulidis, P. ; Spyropoulos, B.
Author_Institution :
Medical Instrumentation Technology Department, Technological Educational Institute (TEI) of Athens, Greece
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
112
Lastpage :
115
Abstract :
The aim of the paper is to identify the key physiological variables and ventilator settings involved in ventilation management, and required for an appropriate Clinical Decision Support System (CDSS). Based on the results of a questionnaire designed for the purpose of the research, 70 hours of physiological and ventilation data were recorded. Recorded data were classified by clinicians into three major lung pathologies and were further statistically analyzed for identifying strong relationships between monitored and controlled ventilator parameters. Correlation analysis was evaluated by Intensive Care Unit (ICU) clinicians. Based on the evaluators´ majority voting the number and type of participating variables in a CDSS was drastically decreased. The number and type of monitored variables ranged from a single one to six, depending on the patient´s lung pathology, and the controlled ventilator setting. Evaluation results were successfully applied to Neural Network models for providing suggestions on Tidal Volume and the Fraction of inspired Oxygen.
Keywords :
Artificial neural networks; Biomedical monitoring; Blood; Correlation; Hospitals; Lungs; Ventilation; Data Interpretation, Statistical; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Humans; Neural Networks (Computer); Pattern Recognition, Automated; Pulmonary Disease, Chronic Obstructive; Respiration, Artificial;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6089909
Filename :
6089909
Link To Document :
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