TY - GEN
T1 - Atrial Fibrillation Episode Patterns and Their Influence on Detection Performance
AU - Butkuviene, Monika
AU - Petrenas, Andrius
AU - Solosenko, Andrius
AU - Martin-Yebra, Alba
AU - Marozas, Vaidotas
AU - Sornmo, Leif
PY - 2021
Y1 - 2021
N2 - Existing studies offer little insight on how atrial fibrillation (AF) detection performance is influenced by the properties of AF episode patterns. The aim of this study is to investigate the influence of AF burden and median AF episode length on detection performance. For this purpose, three types of AF detectors, using either information on rhythm, rhythm and morphology, or ECG segments, were investigated on 1-h simulated ECGs. Comparing AF burdens of 20% and 80% for a median episode length of 167 beats, the sensitivity of the rhythm- and morphology-based detector increases only slightly whereas the specificity drops from 99.5% to 93.3%. The corresponding figures of specificity are 99.0% and 90.6% for the rhythm-based detector; 88.1% and 70.7% for the segment-based detector. The influence of AF burden on specificity becomes even more pronounced for AF patterns with brief episodes (median episode length set to 30 beats). Therefore, patterns with briefepisodes and high AF burden imply higher demands on detection performance. Future research should focus on how well episode patterns are captured.
AB - Existing studies offer little insight on how atrial fibrillation (AF) detection performance is influenced by the properties of AF episode patterns. The aim of this study is to investigate the influence of AF burden and median AF episode length on detection performance. For this purpose, three types of AF detectors, using either information on rhythm, rhythm and morphology, or ECG segments, were investigated on 1-h simulated ECGs. Comparing AF burdens of 20% and 80% for a median episode length of 167 beats, the sensitivity of the rhythm- and morphology-based detector increases only slightly whereas the specificity drops from 99.5% to 93.3%. The corresponding figures of specificity are 99.0% and 90.6% for the rhythm-based detector; 88.1% and 70.7% for the segment-based detector. The influence of AF burden on specificity becomes even more pronounced for AF patterns with brief episodes (median episode length set to 30 beats). Therefore, patterns with briefepisodes and high AF burden imply higher demands on detection performance. Future research should focus on how well episode patterns are captured.
U2 - 10.23919/CinC53138.2021.9662847
DO - 10.23919/CinC53138.2021.9662847
M3 - Paper in conference proceeding
AN - SCOPUS:85124744440
T3 - Computing in Cardiology
BT - 2021 Computing in Cardiology, CinC 2021
PB - IEEE Computer Society
T2 - 2021 Computing in Cardiology, CinC 2021
Y2 - 13 September 2021 through 15 September 2021
ER -