Wavelet-based algorithms for noninvasive fetal ECG post-processing: A methodological review

Objective Downstream of noninvasive fetal electrocardiography (fECG) extraction, a post-processing signal enhancement step is generally required. To date, wavelet denoising (WD) was successfully adopted but typically parameterizations are largely empiric. This comprehensive review aims to systematize the knowledge by presenting and assessing WD algorithms for this application. Methods 17 WD algorithms for fECG enhancement were identified, presented and quantitatively compared on the same public datasets. Overall performance, effectiveness in noise reduction and signal morphology preservation were separately assessed by using a novel methodology based on principal component analysis, to synthetize different performance metrics by a single unbiased index. Results The comparison reveals different best solutions according to the different analyzed performance, which can be used for a reasoned selection of the right algorithm for a given enhancement problem. The proposed unbiased performance index was effective in supporting the analysis. Conclusions WD represents a powerful tool for fECG enhancement, but the parameterizations severely affect the algorithm performance. Our findings can be used for a reasoned selection of an algorithm or for the proposal of new WD approaches.