Template-based Quality Assessment of the Doppler Ultrasound Signal for Fetal Monitoring

Abstract

One dimensional Doppler Ultrasound (DUS) is a low cost method for fetal auscultation. However, accuracy of any metrics derived from the DUS signals depends on their quality, which relies heavily on operator skills. In low resource settings, where skill levels are sparse, it is important for the device to provide real time signal quality feedback to allow the re-recording of data. Retrospectively, signal quality assessment can help remove low quality recordings when processing large amounts of data. To this end, we proposed a novel template-based method, to assess DUS signal quality. Data used in this study were collected from 17 pregnant women using a low-cost transducer connected to a smart phone. Recordings were split into 1990 segments of 3.75 s duration, and hand labeled for quality by three independent annotators. The proposed template-based method uses Empirical Mode Decomposition (EMD) to allow detection of the fetal heart beats and segmentation into short, time-aligned temporal windows. Templates were derived for each 15 s window of the recordings. The DUS signal quality index (SQI) was calculated by correlating the segments in each window with the corresponding running template using four different pre-processing steps: (i) no additional preprocessing, (ii) linear resampling of each beat, (iii) dynamic time warping (DTW) of each beat and (iv) weighted DTW of each beat. The template-based SQIs were combined with additional features based on sample entropy and power spectral density. To assess the performance of the method, the dataset was split into training and test subsets. The training set was used to obtain the best combination of features for predicting the DUS quality using cross validation, and the test set was used to estimate the classification accuracy using bootstrap resampling. A median out of sample classification accuracy on the test set of 85.8% was found using three features; template-based SQI, sample entropy and the relative power in the 160 to 660 Hz range. The results suggest that the new automated method can reliably assess the DUS quality, thereby helping users to consistently record DUS signals with acceptable quality for fetal monitoring.

A Proxy for Detecting IUGR Based on Gestational Age Estimation in a Guatemalan Rural Population

“…The features were fed into a classifier composed of a logistic regression and a multiclass support vector machine to classify the 3.75-s window into good quality, interference, silence, talking in the background, or low signal to noise ratio. More details of the quality assessment method can be found in Valderrama et al (2017Valderrama et al ( , 2018a.…”

Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring

“…The study by Stroux was followed by another work, which proposed a templatebased method using only the 1D-DUS-based features (Valderrama et al , 2017). It used Empirical Mode Decomposition (EMD) to detect the fetal heart beats and to segment the recording into short, time-aligned temporal windows.…”

“…Using the wavelet analysis, valve movements were visualized as peaks in the detailed signal (at level 2 wavelet decomposition, for an ultrasound frequency of 1.15 MHz). Other studies proposed to use EMD, which is a data-driven algorithm used for decomposing nonlinear and nonstationary time series (Marzbanrad et al , 2014d; Valderrama et al , 2017). Using EMD, the first intrinsic mode function (IMF), i.e.…”

“…As discussed in section 5, development of real-time signal quality feedback might also assist the operator with acquisition of reliable data through a real-time feedback system. This has not been sufficiently studied until recently (Marzbanrad et al , 2015a; Stroux & Clifford, 2016; Valderrama et al , 2017) and requires further development of signal quality metrics. It not only requires raw Doppler signals, but also quality annotation or benchmarking with another approved modality.…”

New Method for Beat-to-Beat Fetal Heart Rate Measurement Using Doppler Ultrasound Signal

“…In addition, any interfering impulses of sufficiently high amplitude can be identified as successive beats [ 23 , 35 , 36 , 37 ]. All of these makes practically impossible to indicate points equivalent to the R-waves in FECG [ 38 ]. Therefore, for FHR determination based on the US signal, correlation methods considering the full impulse shape are used [ 33 , 35 , 39 , 40 , 41 , 42 ].…”