ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction
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- 15 January 2013
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 60 (6), 1660-1666
- https://doi.org/10.1109/tbme.2013.2240452
Abstract
An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database, and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm call independently. This would require a substantially increased set of labeled data in order to train an accurate algorithm.Keywords
This publication has 9 references indexed in Scilit:
- Signal quality indices and data fusion for determining clinical acceptability of electrocardiogramsPhysiological Measurement, 2012
- Reducing false alarm rates for critical arrhythmias using the arterial blood pressure waveformJournal of Biomedical Informatics, 2008
- Robust heart rate estimation from multiple asynchronous noisy sources using signal quality indices and a Kalman filterPhysiological Measurement, 2007
- A robust open-source algorithm to detect onset and duration of QRS complexesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- PhysioBank, PhysioToolkit, and PhysioNetCirculation, 2000
- Multicentric study of monitoring alarms in the adult intensive care unit (ICU): a descriptive analysisIntensive Care Medicine, 1999
- A Unifying Review of Linear Gaussian ModelsNeural Computation, 1999
- Poor prognosis for existing monitors in the intensive care unitCritical Care Medicine, 1997
- Crying wolfCritical Care Medicine, 1994