Estimation of the foetal heart rate baseline based on singular spectrum analysis and empirical mode decomposition

Abstract

In this paper, we propose a novel automatic baseline estimation algorithm for foetal heart rate (FHR), and we verify the correctness and effectiveness of the algorithm through clinical trials. First, Singular Spectrum Analysis (SSA) is used to improve the denoising algorithm during the pre-processing of FHR. Compared with the traditional denoising method that simply uses the sliding average method, the use of the SSA method to denoise, in terms of the overall aspect, not only maintains the signal trend that is consistent with the traditional method, but it also produces no additional signal decay and distortion, which verifies the correctness of the algorithm. The SSA method could ensure that the processed signal remains smooth, unlike the sliding average method that is susceptible to the influence of oscillatory noise, causing the signal to have still abruptly changed the noise after being filtered. Subsequently, we propose the Empirical Mode Decomposition (EMD) iterative pruning method for the extraction of the FHR baseline. This algorithm combines the characteristics of the two classical algorithms and includes the EMD to make the algorithm more adaptive. This algorithm overcomes the difficulties in the classical algorithms, and the extracted baseline can more accurately reflect the real baseline and improve the effect of acceleration and deceleration detection.