NDLI: Hidden Markov Models for modeling blood pressure data to predict acute hypotension

Content Provider	IEEE Xplore Digital Library
Author	Singh, A. Tamminedi, T. Yosiphon, G. Ganguli, A. Yadegar, J.
Copyright Year	2010
Description	Author affiliation: UtopiaCompression Corporation, 11150 W Olympic Blvd, Suite 680, Los Angeles, CA 90064, USA (Tamminedi, T.; Yosiphon, G.; Ganguli, A.; Yadegar, J.) \|\| Dept. of Electrical & Computer Engineering, University of Florida, Gainesville, 32611, USA (Singh, A.)
Abstract	The ability to predict episodes of acute hypotension (abnormal drop in arterial blood pressure) would be of immense benefit to the healthcare community, and is therefore a focus of research in both medical and engineering domains. This paper presents the use of Hidden Markov Models to predict the onset of acute hypotension, using blood pressure measurements over time. Our use of HMMs has been motivated by their ability to characterize sequential/temporal trends in a given time signal. This lends the ability to infer the health status based on blood pressure information collected over an interval of time, rather than just instantaneous measurements. We have tested the proposed technique on standard physiological signal datasets available online and have obtained promising results. As part of a bigger project, we see potential in the proposed technique being used in real time health monitoring systems.
Starting Page	550
Ending Page	553
File Size	629323
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495603
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Predictive models Blood pressure Biomedical monitoring Pressure measurement Time measurement Arterial blood pressure Medical services Biomedical engineering Testing Hidden Markov Models Biomedical Signal Analysis Acute Hypotension
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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