Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals

By Fatin A. Elhaj, Naomie Binti Salim, Arief R. Harris, Tan Tian Swee, Taqwa Ahmed. Comput. Methods Programs Biomed., 2016

410 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/9c7f62048f9cf3c4358dddb06bcf0810930155c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Bin Yao
2. Jingshan Huang
3. Wangpeng He
4. Binqiang Chen

In Cognitive Neuroscience

1. Bin Yao
2. Jingshan Huang
3. Wangpeng He
4. Binqiang Chen

Citations in the corpus

• ECG Arrhythmia Classification Using STFT-Based Spectrogram and Convolutional Neural Network (2019, positive): “Elhaj extracted the linear and nonlinear features from the signals for automatic ECG beat recognition [11].”