Multiparameter trend monitoring and intelligent displays using wavelet analysis.
An Intelligent Patient Monitoring (IPM) framework is defined for the analysis and display of multiparameter trends from ICU patients. Wavelet analysis was utilized for detection of physiological events and artifacts in long-term trends. A group of 58 patients from the MIMIC database were identified in which the heart rate (HR), arterial blood pressure (ABP), and pulmonary artery pressure (PAP) were monitored. An estimated cardiac output (CO) signal, using HR and ABP, was shown to correlate strongly (r=.67) with actual CO measurements. Using wavelet analysis, automated artifact and physiological event detection algorithms were developed to monitor left ventricular hemodynamic function. Finally, an intelligent display system is presented for presentation of the data in ICU monitors.
Saeed
M
M
Harvard-MIT, Cambridge, USA. msaeed@mit.edu
Mark
R G
RG
D000465:Algorithms; D016477:Artifacts; D001794:Blood Pressure / Q000502:physiology; D002302:Cardiac Output / Q000502:physiology*; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D007362:Intensive Care Units; D008955:Models, Cardiovascular; D008991:Monitoring, Physiologic; D011651:Pulmonary Artery / Q000502:physiology; D012815:Signal Processing, Computer-Assisted