NDLI: A 24/7 monitorization tool for avoiding hypotensive episodes in critical care

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A 24/7 monitorization tool for avoiding hypotensive episodes in critical care

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A 24/7 monitorization tool for avoiding hypotensive episodes in critical care

Content Provider	ACM Digital Library
Author	Bernardino, Jorge Santos, Ricardo Jorge Henriques, Jorge
Abstract	The sudden fall of blood pressure (hypotension) is a common complication in medical care. In critical care patients, hypotension (HT) may cause serious heart, endocrine or neurological disorders, inducing severe or even lethal events. Moreover, recent studies report an increase of mortality in HT prone hemodialysis patients in need of critical care. If HT could be predicted in advance, medical staff could take action to minimize its effects, or even avoid its occurrence. Typically, most medical systems have focused on monitoring and detecting current patient status, rather than determining biosignal trends or predicting a patient's future status. Therefore, predicting HT episodes in advance remains a challenge. Furthermore, since critical care actions such as hemodialysis are oftenly inconvenient and uncomfortable procedures, HT prediction or detection methods should be non-invasive, whenever possible. In this paper, we present a solution for continuous monitorization and prediction of HT episodes, using heart rate (HR) and mean blood pressure (BP) non-invasive measured biosignals. We propose an architecture for a HT Predictor (HTP) Tool, presenting a set of tools and a real-time database capable of continuously storing and real-time monitoring all patient's historical HR and BP biosignal data, and efficiently alerting both probable and detected occurrences of HT episodes for each patient for the following 60 minutes. Additionally, the system promotes medical staff mobility, by taking advantage of using mobile personal devices such as mobile phones and PDA's, optimizing human resources. Finally, an experimental evaluation on real-life data from the well known Physionet database shows the efficiency of the tool, outperforming the winning proposal of the Physionet 2009 Challenge.
Starting Page	169
Ending Page	178
Page Count	10
File Format	PDF
ISBN	9781605589008
DOI	10.1145/1866480.1866505
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-08-16
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Biosignals analysis and processing Hypotension detection and prediction Medical care systems and applications
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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