کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6950977 | 1451639 | 2018 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Classification of imbalanced ECG beats using re-sampling techniques and AdaBoost ensemble classifier
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Computer-aided heartbeat classification has a significant role in the diagnosis of cardiac dysfunction. Electrocardiogram (ECG) provides vital information about the heartbeats. In this work, we propose a method for classifying five groups of heartbeats recommended by AAMI standard EC57:1998. Considering the nature of ECG signal, we employed a non-stationary and nonlinear decomposition technique termed as improved complete ensemble empirical mode decomposition (ICEEMD). Later, higher order statistics and sample entropy measures are computed from the intrinsic mode functions (IMFs) obtained from ICEEMD on each ECG segment. Furthermore, three data level pre-processing techniques are performed on the extracted feature set, to balance the distribution of heartbeat classes. Finally, these features fed to AdaBoost ensemble classifier for discriminating the heartbeats. Simulation results show that the proposed method provides a better solution to the class imbalance problem in heartbeat classification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biomedical Signal Processing and Control - Volume 41, March 2018, Pages 242-254
Journal: Biomedical Signal Processing and Control - Volume 41, March 2018, Pages 242-254
نویسندگان
Kandala N.V.P.S. Rajesh, Ravindra Dhuli,