Independent Component Analysis (ICA) is a blind source separation method widely used to extract the fetal electrocardiogram (FECG) from maternal abdominal recordings. However, selection of the most relevant independent component (IC) is still largely empirical and, thus, subjective. To overcome this issue, this study proposes a quantitative and objective index, termed Ic4FECG, for automatically selecting the most relevant IC. By considering that expected fetal RR-interval (FRR) should be around 428ms, correspond-ing to a fetal heart rate (FHR) of 140bpm, and that very different FHR val-ues likely relate to wrong fetal R-peaks identifications due to the presence of maternal interference or noise, Ic4FECG index is defined as follows: Ic4FEC G=||(428ms-μFRR)×σFRR||, where μFRR and σFRR are FRR mean and standard deviation, respectively. To evaluate the goodness of Ic4FECG in selecting the most relevant IC, 36 clean maternal recordings, taken from the "NinFea" database (PhysioNet), were used. Maternal interference was removed using Principal Component Analysis, under the assumption of FECG being represented in the lowest 5% of the explained variance. Subsequently, ICA was used to decompose FECG into 20 ICs using maximum likelihood estimation to optimize the contrast function based on kurtosis. Fetal R peaks were then localized in each IC and used to compute Ic4FECG. The IC that minimized Ic4FECG was selected as the most relevant IC, FHR was computed on it (FHRIC). Eventually, FHRIC distribution was compared with that obtained using the Doppler ultrasound (FHRDUS) by using Pearson's correlation coefficient (ρ) and linear regres-sion analysis. Results indicate that FHRIC (140±9bpm) and FHRDUS (141±8bpm) were strongly associated (ρ=0.75; P<10-8; FHRDUS=0.90∙FHRIC+13.7bpm). In conclusion, Ic4FECG appears to be a potentially useful tool for automated selection of the most relevant IC in FECG analysis. Future studies will further test Ic4FECG on larger datasets and evaluate its possible integration into real-time fetal monitoring systems.