PMID- 31946271
OWN - NLM
STAT- MEDLINE
DCOM- 20200422
LR  - 20200928
IS  - 2694-0604 (Electronic)
IS  - 2375-7477 (Linking)
VI  - 2019
DP  - 2019 Jul
TI  - A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet 
      Transform.
PG  - 1908-1912
LID - 10.1109/EMBC.2019.8856834 [doi]
AB  - Atrial fibrillation (AF) is one of the most common arrhythmias. The automatic AF 
      detection is of great clinical significance but at the same time it remains a big 
      problem to researchers. In this study, a novel deep learning method to detect AF 
      was proposed. For a 10 s length single lead electrocardiogram (ECG) signal, the 
      continuous wavelet transform (CWT) was used to obtain the wavelet coefficient 
      matrix, and then a convolutional neural network (CNN) with a specific 
      architecture was trained to discriminate the rhythm of the signal. The ECG data 
      in multiple databases were divided into 4 classes according to the rhythm 
      annotation: normal sinus rhythm (NSR), atrial fibrillation (AF), other types of 
      arrhythmia except AF (OTHER), and noise signal (NOISE). The method was evaluated 
      using three different wavelet bases. The experiment showed promising results when 
      using a Morlet wavelet, with an overall accuracy of 97.56%, an average 
      sensitivity of 97.56%, an average specificity of 99.19%. Besides, the area under 
      curve (AUC) value is 0.9983, which showed that the proposed method was effective 
      for detecting AF.
FAU - Wu, Ziqian
AU  - Wu Z
FAU - Feng, Xujian
AU  - Feng X
FAU - Yang, Cuiwei
AU  - Yang C
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Annu Int Conf IEEE Eng Med Biol Soc
JT  - Annual International Conference of the IEEE Engineering in Medicine and Biology 
      Society. IEEE Engineering in Medicine and Biology Society. Annual International 
      Conference
JID - 101763872
SB  - IM
MH  - Atrial Fibrillation/*diagnosis
MH  - *Deep Learning
MH  - *Electrocardiography
MH  - Humans
MH  - *Neural Networks, Computer
MH  - *Wavelet Analysis
EDAT- 2020/01/18 06:00
MHDA- 2020/04/23 06:00
CRDT- 2020/01/18 06:00
PHST- 2020/01/18 06:00 [entrez]
PHST- 2020/01/18 06:00 [pubmed]
PHST- 2020/04/23 06:00 [medline]
AID - 10.1109/EMBC.2019.8856834 [doi]
PST - ppublish
SO  - Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:1908-1912. doi: 
      10.1109/EMBC.2019.8856834.