NDLI: The progress of research on prediction model for acute hypotensive episodes

Content Provider	IEEE Xplore Digital Library
Author	Lijuan Lai Zhigang Wang Xiaoming Wu
Copyright Year	2010
Description	Author affiliation: Department of Biomedical Engineering, South China University of Technology, Guangzhou, China (Lijuan Lai; Zhigang Wang; Xiaoming Wu)
Abstract	The occurrence of acute hypotensive episode (AHE) in intensive care units (ICU) can result in grave consequences and endanger the patients' lives. How to detect and predict AHE in advance has become a clinical problem which is highly paid attention to by the medical world. In recent years, with the rapid development of the medical monitoring technology and signal analysis and processing methods, promoting a comprehensive study of forecasting approaches for AHE, the study mainly focuses on two aspects: one is the research of the vital signs that is likely related to the occurrence of AHE, showing that arterial blood pressure, heart rate and oxygen saturation, etc. can be acted as effective indicators; the other is to study the trend of changes in these vital signs, which would achieve forecasting AHE up to an hour in advance by defining a certain forecast window and the diagnostic threshold. It illustrates that integration of digitized signal processing technique with clinical monitoring parameters is the development direction for realizing intelligent monitoring technology. On the basis of continuing to enrich the database for monitoring, person concerned are committed to recognize the onset regularity of AHE, looking for approach that might forecast AHE ahead of time and designing intelligent forecast software. The study of this approach is beneficial to early prediction of AHE and intervention, which would significantly reduce the death risk of patients and is of great value to clinical application.
Starting Page	1067
Ending Page	1070
File Size	219642
Page Count	4
File Format	PDF
ISBN	9781424464951
e-ISBN	9781424464982
DOI	10.1109/BMEI.2010.5640544
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Heart rate prediction model Predictive models Feature extraction ICU Cardiology arterial blood pressure (ABP) acute hypotensive episode (AHE) Monitoring feature selection
Content Type	Text
Resource Type	Article

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