# A Heart Rate Variability-Based Paroxysmal Atrial Fibrillation Prediction System
## 5 Conclusions
The following datasets have been used: PAF Prediction Challenge Database (accessed on 20 November 2019), MIT-BIH Atrial Fibrillation Database (accessed on 11 March 2021), and MIT-BIH Normal Sinus Rhythm Database (accessed on 11 March 2021) from [[https://www.physionet.org/about/database/](https://www.physionet.org/about/database/)]([https://www.physionet.org/about/database/](https://www.physionet.org/about/database/))). The authors declare no conflict of interest. The optimum structure of the CNN found by the GA approach. The following datasets have been used: PAF Prediction Challenge Database (accessed on 20 November 2019), MIT-BIH Atrial Fibrillation Database (accessed on 11 March 2021), and MIT-BIH Normal Sinus Rhythm Database (accessed on 11 March 2021) from [[https://www.physionet.org/about/database/](https://www.physionet.org/about/database/)]([https://www.physionet.org/about/database/](https://www.physionet.org/about/database/))). The following datasets have been used: PAF Prediction Challenge Database (accessed on 20 November 2019), MIT-BIH Atrial Fibrillation Database (accessed on 11 March 2021) from https://www. **Table A1. **_Cont._ \begin{tabular}{c c c c c} \hline \hline
**No.** & **Name** & **Type** & **Activations** & **Learnables** \\ \hline \multirow{3}{*}{7} & \multirow{3}{*}{14 16 \(\times\) 16 \(\times\) 16 convolutions with stride [1 1] and padding'same'} & \multirow{3}{*}{Convolution} & 32 \(\times\) 32 \(\times\) 14 & Weights 16 \(\times\) 16 \(\times\) 16 \(\times\) 14 \\  & & & & Bias 1 \(\times\) 1 \(\times\) 14 \\  & & Batch normalization & Batch & 32 \(\times\) 32 \(\times\) 14 & Offset 1 \(\times\) 14 \\  & & & Normalization & & Scale 1 \(\times\) 1 \(\times\) 14 \\
9 & & **relu**2 & ReLU & 32 \(\times\) 32 \(\times\) 14 & - \\  & & **conv**5 & & & \\
10 & 15 12 \(\times\) 12 \(\times\) 14 convolutions with stride [1 1] and padding'same' & Convolution & 32 \(\times\) 32 \(\times\) 15 & Weights 12 \(\times\) 12 \(\times\) 14 \(\times\) 15 \\  & & Batchnorm_3 & Batch & Bias 1 \(\times\) 15 \\  & & Batch normalization with 15 channels & Normalization & 32 \(\times\) 32 \(\times\) 15 & Offset 1 \(\times\) 15 \\
12 & & **relu**3 & ReLU & 32 \(\times\) 32 \(\times\) 15 & - \\  & & ReLU & & & Scale 1 \(\times\) 15 \\  & & **fc** & & & \\
13 & 2 fully connected & Fully Connected & 32 \(\times\) 32 \(\times\) 15360 & Weights 2 \(\times\) 15360 \\  & & layer & & & Bias 2 \(\times\) 1 \\
14 & & **dropout** & Dropout & 1\(\times\) 1 \(\times\) 2 & - \\
15 & & **softmax** & Softmax & 1\(\times\) 1\(\times\) 2 & - \\
16 & & **classoutput** & Classification & & \\  & & crossentropyvex with classes '0' and '1' & Output & & - \\ \hline \hline \end{tabular}   
**Figure A1. ** Heart rate distribution of the HRV sequences in the PAF Prediction Challenge Database (AFPDB). Upper Left: Boxplot of the heart rate values of all of the HRV sequences. Upper Right: Histogram of the heart rate values of all of the HRV sequences. Lower Left: Boxplot of the heart rate values in the range of [0, 200] beats/min. Lower Right: Histogram of the heart rate values in the range of [0, 200] beats/min, from which we determined to adopt the range of [30, 190] for HRV sequence filtering.