| Title |
Signal quality assessment of f-waves in atrial fibrillation / |
| Authors |
Henriksson, Mikael ; Petrėnas, Andrius ; Marozas, Vaidotas ; Sandberg, Frida ; Sörnmo, Leif |
| DOI |
10.22489/CinC.2017.051-153 |
| ISBN |
9781538645550 |
| eISBN |
9781538666302 |
| Full Text |
|
| Is Part of |
Computing in cardiology (CinC): September 24-27, 2017, Rennes, France.. Piscataway, NJ : IEEE, 2017. vol. 44, p. 1-4.. eISSN 2325-887X. ISBN 9781538645550. eISBN 9781538666302 |
| Keywords [eng] |
electrocardiography ; signal to noise ratio ; electrodes ; frequency estimation ; muscles ; frequency modulation ; noise measurement |
| Abstract [eng] |
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 off-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 model-based approach for assessment off-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 off-wave analysis. |
| Published |
Piscataway, NJ : IEEE, 2017 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2017 |
| CC license |
|
