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Journal of Clinical Monitoring and Computing

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01-12-2016 | Original Research

Sensor fusion methods for reducing false alarms in heart rate monitoring

Authors: Gabriel Borges, Valner Brusamarello

Published in: Journal of Clinical Monitoring and Computing | Issue 6/2016

Abstract

Automatic patient monitoring is an essential resource in hospitals for good health care management. While alarms caused by abnormal physiological conditions are important for the delivery of fast treatment, they can be also a source of unnecessary noise because of false alarms caused by electromagnetic interference or motion artifacts. One significant source of false alarms is related to heart rate, which is triggered when the heart rhythm of the patient is too fast or too slow. In this work, the fusion of different physiological sensors is explored in order to create a robust heart rate estimation. A set of algorithms using heart rate variability index, Bayesian inference, neural networks, fuzzy logic and majority voting is proposed to fuse the information from the electrocardiogram, arterial blood pressure and photoplethysmogram. Three kinds of information are extracted from each source, namely, heart rate variability, the heart rate difference between sensors and the spectral analysis of low and high noise of each sensor. This information is used as input to the algorithms. Twenty recordings selected from the MIMIC database were used to validate the system. The results showed that neural networks fusion had the best false alarm reduction of 92.5 %, while the Bayesian technique had a reduction of 84.3 %, fuzzy logic 80.6 %, majority voter 72.5 % and the heart rate variability index 67.5 %. Therefore, the proposed algorithms showed good performance and could be useful in bedside monitors.

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Title: Sensor fusion methods for reducing false alarms in heart rate monitoring
Authors: Gabriel Borges
Valner Brusamarello
Publication date: 01-12-2016
Publisher: Springer Netherlands
Published in: Journal of Clinical Monitoring and Computing / Issue 6/2016
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI: https://doi.org/10.1007/s10877-015-9786-4

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Springer Medicine

Sensor fusion methods for reducing false alarms in heart rate monitoring

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

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