Energy-Dependent RLS Architecture for the Separation of Fetal ECG Using Thoracic and Abdominal Lead ECG of Mother

This paper proposes a fetal electrocardiogram separation approach based on an energy dependent recursive least square filtering approach that uses the mother’s R-peaks collected from both the abdomen and thorax. This approach initially identifies the mother’s R-peaks from the thorax electrocardiogram which is used to represent the mother’s R-peaks in both the abdominal and thorax channels. Instead of using the recent abdominal and thorax electrocardiogram samples, the proposed filter also considers the energy ofL1number of mother’s past R-peak abdominal and thorax samples along with the energy ofL2number of non-R-peak abdominal samples for estimating the R-peak energy factor. The energy factor is estimated for each sample for the updation of weights in the recursive least square filter. An architecture for the filter is also proposed which can be used in hardware implementation. The evaluation of the proposed filtering approach was performed using the datasets such as Synthetic and Daisy with the evaluation metrics namely correlation coefficient, fetal R-peak detection accuracy, fetal to maternal signal-to-noise ratio, and percent root mean square difference. With filter lengthP= 24, the proposed filter results in correlation, signal-to-noise ratio, and percent root mean square difference of 0.9901, 9.03dB, and 80.84% respectively. For the Daisy and Synthetic datasets, the R-peak detection accuracy was estimated as 96.4%, and 98.12% respectively. The architecture of the proposed filter was implemented in Virtex VC707 hardware which utilizes a power of 1.378W, resulting in a maximum clock frequency and throughput of 128.43MHzand 31.5Mbpsrespectively with a wordlength ofL= 24 bits.