SimGANs: Simulator-based generative adversarial networks for ECG synthesis to improve deep ECG classification International Conference on Machine Learning, PMLR (2020), pp. 3597-3606 Google Scholar [74] T. Golany, D. Freedman, K. Radinsky, Ecg ode-gan: Learning ordinary differential equations of ...
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The ECG signals used in the development and testing of the biomedical signal processing algorithms are mainly from three sources: 1) Biomedical databases (for example, MIT-BIH Arrhythmia Database) or other prerecorded ECG data; 2) ECG simulator; 3) Real-time ECG data acquisition. This example...
In this study, a multi-parameter patient simulator (FLUKE ProSim 8), the heart rate of which was 60 beats/min, was used to generate 5 types of ECG signals. Then, our developed wearable Holter (Mini-Holter, 58×50×10 mm, 20 g, over 30 h of battery working time, single channel thre...
An arrhythmia waveform was generated through the ECG simulator linked to the VB. The data loaded by the dummy VB contained an arrhythmia waveform, and it was verified as to whether the alarm was generated for the arrhythmia waveform. The alarm was displayed in the graph area where the ECG ...
An arrhythmia waveform was generated through the ECG simulator linked to the VB. The data loaded by the dummy VB contained an arrhythmia waveform, and it was verified as to whether the alarm was generated for the arrhythmia waveform. The alarm was displayed in the graph area where the ECG ...
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Synthetic data acquired from a patient simulator at different sampling rates. Table 3. SNR (signal-to-noise ratio) measurement in the synthetic data. 3.2. System Calibration and Functional Validation The developed arm-ECG sensor system (WAMECG1) was calibrated using a high-resolution ECG clin...
They used a simulated fECG signal database (fecgsyndb) [69], which is a publicly available simulator that generates simultaneously the mECG and fECG signals in 34 channels, which is 5 min long and with sampling rate 250 Hz, and real data from adfecgdb [10,47,48,49,50], which ...