基于模式识别和集成CNN-LSTM的阵发性房颤预测模型

杨萍,王丹,康子健,李童,付利华,余悦任

Prediction model of paroxysmal atrial fibrillation based on pattern recognition and ensemble CNN-LSTM

Ping YANG,Dan WANG,Zi-jian KAGN,Tong LI,Li-hua FU,Yue-ren YU

表 7 模型在不同采样频率ECG信号上的实验结果

Tab.7 Experimental results of proposed method on ECG signals with different sampling frequencies

f / Hz ACC / % SEN / % SPE / % 128 79.1 69.3 83.7 64 80.2 70.7 84.8 32 78.5 68.6 83.9 16 75.3 69.5 78.1 8 80.6 75.7 82.7