Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics

Table 1

Main characteristics and findings for the selected algorithms, representative for the PLI cancelling approaches available in the literature.

Authors/year	Title	Type of publication	Category/acronym of the algorithm	Main results
Piskorowski/2012 [32]	Suppressing harmonic powerline interference using multiple-notch filtering methods with improved transient behavior	Review article	Digital fixed notch filters/TVMNF	A new class of digital parameter varying IIR multiple-notch filters with reduced transient response is introduced. The simulations and the quantitative evaluation on suppressing the 60 Hz PLI show that the concept of the filter with time-varying pole radius may be used to improve the dynamic behavior of multiple-notch filter.
Martens et al./2006 [39]	An improved adaptive power line interference canceller for electrocardiography	Research article	Adaptive filters/IAC	An improved version of the adaptive canceller for the reduction of the PLI components is proposed. The algorithm is able to track the frequencies, the amplitudes, and the phases for PLI deviations up to about 4 Hz; it is also insensitive to baseline wander.
Hyvärinen et al./2001 [65]	Independent component analysis: algorithms and applications	Research article	Blind source separation/FastICA	A new ICA algorithm, based on a fixed-point iteration scheme when finding a maximum of the nongaussianity, is proposed. It has some advantages as compared to other existing ICA methods: it finds directly independent components (ICs), which can be estimated one by one; the algorithm is, in addition, parallelizable, computationally simple, and requires little memory space.
Pal and Mitra/2012 [66]	Empirical mode decomposition based ECG enhancement and QRS detection	Research article	EMD and HHT/HHT	A new algorithm is proposed based on EMD methods. The improved algorithm proposed in this article differs from the similar algorithms in the following: the baseline wander is corrected by selective reconstruction from IMFs, considering the slope minimization technique; the noise is removed by eliminating a noisy set of lower order IMFs, based on their power. A statistical peak correction is also performed since the noise cancellation affects the sharp morphology of the peaks. The results reveal that the proposed algorithm shows good detection sensitivity and specificity.
Poungponsri and Yu/2013 [51]	An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks	Research article	Neural networks/WNN	In this article the authors propose an adaptive filtering approach based on discrete wavelet transform and artificial neural network. The obtained results, considering simulated data, show that the algorithm can successfully remove various noise and artifacts, leading to a significant SNR improvement, as compared to other algorithms.
Galiana-Merino et al. /2013 [43]	Power line interference filtering on surface electromyography based on the stationary wavelet packet transform	Research article	Wavelet transform/DSWPT	A new method is proposed to estimate and remove PLI components from EMG signals. The method is based on the stationary wavelet packet transform. The quantitative evaluation is performed using synthetic signals, with different SNR values, and the results are compared with the ones obtained when using an adaptive Laguerre filter and other digital filters. In all cases, the proposed algorithm shows an excellent performance, independent of the SNR value.