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Content Provider | IEEE Xplore Digital Library |
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Author | Ladavich, S. Ghoraani, B. |
Copyright Year | 2014 |
Description | Author affiliation: Biomed. Eng. Dept., Rochester Inst. of Technol., Rochester, NY, USA (Ladavich, S.; Ghoraani, B.) |
Abstract | In this study we propose a novel atrial activity-based method for atrial fibrillation (AF) identification that detects the absence of normal sinus rhythm (SR) P-waves from the surface ECG. The proposed algorithm extracts nine features from P-waves during SR and develops a statistical model to describe the distribution of the features. The Expectation-Maximization algorithm is applied to a training set to create a multivariate Gaussian Mixture Model (GMM) of the feature space. This model is used to identify P-wave absence (PWA) and, in turn, AF. An optional post-processing stage, which takes a majority vote of successive outputs, is applied to improve classier performance. The algorithm was tested on 20 records in the MIT-BIH Atrial Fibrillation Database. Classification combining seven beats showed a sensitivity of 99.28%, a specificity of 90.21%. The presented algorithm has a classification performance comparable to current Heartrate-based algorithms yet is rate-independent and capable of making an AF determination in a few beats. |
Sponsorship | IEEE Eng. Med. Biol. Soc. |
Starting Page | 54 |
Ending Page | 57 |
File Size | 826190 |
Page Count | 4 |
File Format | |
ISBN | 9781424479290 |
ISSN | 1557170X |
DOI | 10.1109/EMBC.2014.6943527 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-08-26 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Feature extraction Training Electrocardiography Vectors Rail to rail inputs Classification algorithms Databases |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Health Informatics Signal Processing Biomedical Engineering |
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