Detection of heart beats in multimodal data: a robust beat-to-beat interval estimation approach

The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is strai...

Full description

Saved in:
Bibliographic Details
Published in:Physiological measurement 2015-08, Vol.36 (8), p.1679-1690
Main Authors: Antink, Christoph Hoog, Brüser, Christoph, Leonhardt, Steffen
Format: Article
Language:English
Subjects:
Algorithms
Databases, Factual
ECG analysis
Electrocardiography
False Positive Reactions
Heart - physiology
Heart Function Tests - methods
Heart Rate
Humans
medical signal processing
multimodal sensor-fusion
Pattern Recognition, Automated
QRS detection
Sensitivity and Specificity
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is straightforward under ideal conditions, the exact localization can be a challenging task if the signal is severely contaminated with noise and artifacts. At the same time, other signals directly related to cardiac activity are often available. In this multi-sensor scenario, methods of multimodal sensor-fusion allow the exploitation of redundancies to increase the accuracy and robustness of beat detection. In this paper, an algorithm for the robust detection of heart beats in multimodal data is presented. Classic peak-detection is augmented by robust multi-channel, multimodal interval estimation to eliminate false detections and insert missing beats. This approach yielded a score of 90.70 and was thus ranked third place in the PhysioNet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Muthmodal Data follow-up analysis. In the future, the robust beat-to-beat interval estimator may directly be used for the automated processing of multimodal patient data for applications such as diagnosis support and intelligent alarming.
ISSN:0967-3334
1361-6579
DOI:10.1088/0967-3334/36/8/1679