Autodetection of J Wave Based on Random Forest with Synchrosqueezed Wavelet Transform

作者：Li, Dengao^*; Liu, Xinyan; Zhao, Jumin; Zhou, Jie

来源：Biomed Research International, 2018, 2018: 1315357.

DOI：10.1155/2018/1315357

• TIME-FREQUENCY
• CLASSIFICATION
• ENTROPY
• DEATH
• ELECTROCARDIOGRAM
• ALGORITHM

J wave is the bulge generated in the descending slope of the terminal portion of the QRS complex in the electrocardiogram. The presence of J wave may lead to sudden death. However, the diagnosis of J waive variation only depends on doctor's clinical experiences at present and missed diagnosis is easy to occur. In this paper, a new method is proposed to realize the automatic detection of J wave. First, the synchrosqueezed wavelet transform is used to obtain the precise time-frequency information of the ECG. Then, the inverse transformation of SST is computed to get the intrinsic mode function of the ECG. At last, the time-frequency features and SST-based and the entropy features based on modes are fed to Random forest to realize the automatic detection of J wave. As the experimental results shown, the proposed method has achieved the highest accuracy, sensitivity, and specificity compared with existing techniques.

• 出版日期2018
• 单位太原理工大学