new strategy for stopping sifting process during bio-signals de-nosing by emd: in case of low frequency artifact reduction from ecg and emg

removal of artifacts from bio-signals is a necessary step before automatic processing and obtaining clinical information. recently, many applications of empirical mode decomposition (emd) on biomedical researches have been presented that artifact reduction from bio-signals is one of them. emd separates a time series into finite numbers of its individual oscillations, which are called intrinsic mode function (imf). the process of the imf extraction from a signal is known as the sifting process. the main issue during sifting process is to select an appropriate criterion for stopping imf extraction when the process reaches the artifact components. in this paper, we try to investigate mean power frequency (mpf) for stopping sifting process, in case of low frequency artifact reduction from ecg and emg signals. in order to evaluate effectiveness of the proposed index during sifting process, reduction of baseline noise from electrocardiogram signals (ecg) and ecg artifact from electromyogram signals (emg) have been investigated. the obtained results indicate mpf can be considered as an acceptable criterion to stop sifting process during low frequency artifact elimination.