Deep learning improves cECG denoising for better cardiac health monitoring.
problem Motion artifacts limit the clinical use of cECG for long-term monitoring.
method End-to-end deep learning architecture trained on motion-corrupted cECG and reference ECG.
result MSE of 0.167 and Cross Correlation of 0.476 for signal denoising.