Assessment of artifacts reduction and denoising techniques in Electrocardiographic signals using Ensemble Average-based method.

BACKGROUND AND OBJECTIVE

Outpatient vital signs monitoring has a key role in medical diagnosis and treatment. However, ambulatory vital signs monitoring has great challenges to overcome, being the most important, the reduction of noise and Motion Artifacts, which hide essential information, particularly in Electrocardiographic signals. Despite efforts being made to reduce these artifacts, a comparative performance assessment of proposed techniques does not exist to the best of our knowledge and there are no enhancement level measurements obtained by the signals in the artifacts reduction. This article presents a new method based on Ensemble Average for the performance comparison of reported techniques for the processing and reduction of noise and artifacts in Electrocardiographic signals.

METHODS

The comparison was done using a dataset composed by six synthetic noised Electrocardiographic signals and six real one acquired from healthy volunteers that intentionally introduced Motion Artifacts. Several techniques that have reported positive results in the enhancement of Electrocardiographic signals were applied to this dataset to compare their performance in the reduction of Motion Artifacts. The Signal-to-Noise Ratio and the Ensemble Average as a distortion measurement were used to compare the performance of algorithms to produce an enhanced signal.

RESULTS

In agreement to previous reports, all studied methods show a significant improvement of the Signal-to-Noise Ratio. Concerning the distortion of the waveform, although all methods caused high distortion on the enhanced signal waveform, the Wavelet-ICA method showed the best performance. The percentage of signal distortion introduced by denoising techniques was evaluated through the proposed Ensemble Average Electrocardiographic method.

CONCLUSIONS

It was found that the proposed method based on Ensemble Average offers a complementary way to measure the performance of denoising techniques when considering the introduced distortion in the waveform segments once the artifact reduction process was applied and not only the change in the Signal-to-Noise Ratio.