NDLI: A data mining approach to reduce the false alarm rate of patient monitors

Content Provider	IEEE Xplore Digital Library
Author	Baumgartner, B. Rodel, K. Knoll, A.
Copyright Year	2012
Description	Author affiliation: Dept. of Comput. Sci., Tech. Univ. Munchen, Garching, Germany (Baumgartner, B.; Knoll, A.)
Abstract	Patient monitors in intensive care units trigger alarms if the state of the patient deteriorates or if there is a technical problem, e.g. loose sensors. Monitoring systems have a high sensitivity in order to detect relevant changes in the patient state. However, multiple studies revealed a high rate of either false or clinically not relevant alarms. It was found that the high rate of false alarms has a negative impact on both patients and staff. In this study we apply data mining methods to reduce the false alarm rate of monitoring systems. We follow a multi-parameter approach where multiple signals of a monitoring system are used to classify given alarm situations. In particular we focus on five alarm types and let our system decide whether the triggered alarm is clinically relevant or can be considered as a false alarm. Several classification algorithms (Naive Bayes, Decision Trees, SVM, kNN and Multi-Layer Perceptron) were evaluated. For training and test sets a subset of the freely available MIMIC II database was used. Alarm-specific classification accuracy was between 78.56% and 98.84%. Suppression rates for false alarms were between 75.24% and 99.23%. Classification results strongly depend on available training data, which is still limited in the intensive care domain. However, this study shows that data mining methods are useful and applicable for alarm classification.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	5935
Ending Page	5938
File Size	463446
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347345
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Monitoring Biomedical monitoring Training Data mining Electrocardiography Decision trees
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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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