Fetal Electrocardiograms (fECG) are an inexpensive and noninvasive method to determine the heart rate (HR) of the fetus. Large variations in the fetal HR is a good indicator that the fetus is in distress thus allowing for clinical intervention. Although advances have been made in the field of fetal HR detection, more can be done to improve accuracy and efficiency. The Variable Pulse Width -Finite Rate of Innovation (VPW-FRI) method is a suitable method given it deals with pulse parameters such as location, width and amplitude. This allows it to automatically segment and identify the foetal QRS complexes and R peak locations from compressed samples which in turn would yield the fetal HR. Our method, which includes model based denoising and multichannel capability, is comparable to other methods involving machine learning, wavelets and ICA.