Title :
Comparison Between Neural-Network-Based Adaptive Filtering and Wavelet Transform for ECG Characteristic Points Detection
Author :
Szildgyi, S.M. ; Szildgyi, L. ; David, Lorenzo
Author_Institution :
Technical University of Budapest, Hungary
fDate :
Oct. 30 1997-Nov. 2 1997
Abstract :
Although thermodilution is generally viewed as reliable and accurate in comparison to the other cardiac output measurement techniques, there are important sources of error in thermodilution. In this paper, the authors propose a data-adaptive approach to the solution of these problems using the Composite Property Mapping Algorithm (CPMA). The CPMA technique is effective and accurate regardless of the volume of the injectate and the phase of the respiratory cycle in which the bolus injections are made. Due to the smaller size of the injectate that may be used, problems such as hypervolemia and hypothermia in the patient are not a concern and the thermodilution technique can be used as a continuous cardiac output monitoring system in both infants and adults
Keywords :
adaptive signal processinghermodilution; biothermics; cardiology; haemodynamics; medical signal processing; patient monitoring; adults; artefacts filtering; bolus injections; composite property mapping algorithm; continuous cardiac output monitoring system; data-adaptive approach; hypervolemia; hypothermia; infants; injectate volume; respiratory cycle phase; Arteries; Computer errors; Extrapolation; Measurement techniques; Noise reduction; Patient monitoring; Signal processing; Signal processing algorithms; Signal restoration; Temperature;
Conference_Titel :
Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-4262-3
DOI :
10.1109/IEMBS.1997.754520