Automatic detection of cardiac waves on fetal magnetocardiographic signals

Fetal magnetocardiography (fMCG) provides fetal cardiac traces useful for the prenatal monitoring of fetal heart function. In this paper, we describe an analytical model (ACWD) for the automatic detection of cardiac waves boundaries that works on fetal signals reconstructed from fMCG by means of independent component analysis. ACWD was validated for 45 healthy and 4 arrhythmic fetuses ranging from 22 to 37 weeks; ACWD outcomes were compared with the estimates of three independent investigators. Descriptive statistics were used to assess correspondence between the outcomes of the automatic and manual approaches. The parametric two-tailed Pearson correlation test (α = 0.01) was employed to quantify, by means of the coefficients of determination, the amount of common variation between the sequences of intervals quantified automatically and manually. ACWD performances on short and long rhythm strips were investigated. ACWD demonstrated to be a robust tool providing dependable estimates of cardiac intervals and their variability during the third gestational trimester also in case of fetal arrhythmias. SNR and stability of fetal traces were the factors limiting ACWD performances. ACWD computation time, which was approximately 1:600 with respect to the manual procedure, was comparable with the time required for fCTI estimation on averaged beats