Projects per year
Abstract
Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database. The signal quality index is capable of discriminating between f-waves and noisy recordings with an accuracy of 98%. The results suggest that the proposed signal quality index correctly identifies noisy recordings, and can be used to improve the reliability of f-wave analysis.
Original language | English |
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Title of host publication | 2017 Computing in Cardiology (CinC) |
Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 4 |
ISBN (Electronic) | 978-1-5386-6630-2 |
ISBN (Print) | 978-1-5386-4555-0 |
DOIs | |
Publication status | Published - 2017 |
Event | 44th Computing in Cardiology, CinC 2017 - Rennes, France Duration: 2017 Sept 24 → 2017 Sept 27 |
Publication series
Name | Computing in Cardiology |
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Publisher | IEEE Computer Society |
ISSN (Print) | 2325-8861 |
Conference
Conference | 44th Computing in Cardiology, CinC 2017 |
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Country/Territory | France |
City | Rennes |
Period | 2017/09/24 → 2017/09/27 |
Subject classification (UKÄ)
- Cardiac and Cardiovascular Systems
Fingerprint
Dive into the research topics of 'Signal quality assessment of f-waves in atrial fibrillation'. Together they form a unique fingerprint.Projects
- 1 Finished
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Modelling and Quality Assessment of Atrial Fibrillatory Waves
Henriksson, M. (Research student), Sörnmo, L. (Supervisor) & Sandberg, F. (Assistant supervisor)
2014/03/01 → 2019/02/01
Project: Dissertation