English

A Neural Network Approach to ECG Denoising

Computational Engineering, Finance, and Science 2012-12-21 v1 Neural and Evolutionary Computing

Abstract

We propose an ECG denoising method based on a feed forward neural network with three hidden layers. Particulary useful for very noisy signals, this approach uses the available ECG channels to reconstruct a noisy channel. We tested the method, on all the records from Physionet MIT-BIH Arrhythmia Database, adding electrode motion artifact noise. This denoising method improved the perfomance of publicly available ECG analysis programs on noisy ECG signals. This is an offline method that can be used to remove noise from very corrupted Holter records.

Keywords

Cite

@article{arxiv.1212.5217,
  title  = {A Neural Network Approach to ECG Denoising},
  author = {Rui Rodrigues and Paula Couto},
  journal= {arXiv preprint arXiv:1212.5217},
  year   = {2012}
}

Comments

15 pages, 5 figures

R2 v1 2026-06-21T22:58:21.807Z