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Generating Synthetic ECG Data
Each of our ECG data consists of 12 leads, with a duration of 10 seconds and a frequency of 250 Hz. Therefore, each sample is a data matrix of 12 by 2500. In our case, we worked on 2 sets
of data, one was synthetic, one was real clinical data. Although we cannot share our real clinical data, the simulation code is accessible.
Simulation Code
The simlation part includes two files: 'ecg_simulation_multichannel.py' and 'parameters. py'.
Instruction:
- Install package neurokit2
- Open sample_code_for_simulation.ipynb which is a short sample notebook to show the way to output synthetic data.
- Function simulation is all you need.
1. Input:\
normal_N: the number of normal ECG data;\
abnormal_N: the number of abnormal ECG data;\
save_params: whether save parameters for each ecg sample, default value is False.
2. Output:\
sim_ecg_data.npy: output file, shape = (normal_N + abnormal_N, 12, sampling_rate*duration);\
sim_ecg_labels.npy: output file to save labels, shape = (normal_N + abnormal_N, );\
sim_ecg_params.npy: depend on save_params, file to save parameters for each ecg sample, shape = (normal_N + abnormal_N, ).
The saved data is already shuffled.
- If you want more customized ECG data, please check parameters. py file. All the parameters' definitions are in the following table (_1 stands for normal, _2 stands for abnormal):
| Parameter | Meaning | |
|---|---|---|
| 1 | sampling_rate | sampling rate, default 250 Hz |
| 2 | duration | default 10s |
| 3 | gamma | a (12,5) matrix to modify each lead's five spikes' amplitudes |
| 4 | mu_hr_1 | the mean of heart rate |
| 5 | sigma_hr_1 | the variance of heart rate |
| 6 | min_noise_1, max_noise_1 | the max value and min value of noise |
| 7 | t | the starting position along the circle of each interval in radius |
| 8 | a | the amplitude of each spike; b, the width of each spike |
| 9 | b | the width of each spike |
For a better understanding of the above parameters, please read the following.
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We can see from the above table that each interval in the 3D trajectory can be fixed by 3 parameters: the starting position
along the circle of each interval in radius, The amplitude of each spike a and the width of each wave b. By altering these 3 parameters we can change the shape of the 3D trajectory and thus change the waveform of the resulting ECG.
Prebuilt Synthetic Data
Prebuilt synthetic data can be found at the following link
https://drive.google.com/drive/folders/1iqyAlyHAvNWdOvjEGn8Y6C8kItsdZ_GC?usp=sharing