Toward Automated Analysis of Fetal Phonocardiograms: Comparing Heartbeat Detection from Fetal Doppler and Digital Stethoscope Signals.

Longitudinal fetal health monitoring is essential for high-risk pregnancies. Heart rate and heart rate variability are prime indicators of fetal health. In this work, we implemented two neural network architectures for heartbeat detection on a set of fetal phonocardiogram signals captured using fetal Doppler and a digital stethoscope. We test the efficacy of these networks using the raw signals and the hand-crafted energy from the signal. The results show a Convolutional Neural Network is the most efficient at identifying the S1 waveforms in a heartbeat, and its performance is improved when using the energy of the Doppler signals. We further discuss issues, such as low Signal-to-Noise Ratios (SNR), present in the training of a model based on the stethoscope signals. Finally, we show that we can improve the SNR, and subsequently the performance of the stethoscope, by matching the energy from the stethoscope to that of the Doppler signal.

Microphysiological System for High-Throughput Computer Vision Measurement of Microtissue Contraction.

The ability to measure microtissue contraction in vitro can provide important information when modeling cardiac, cardiovascular, respiratory, digestive, dermal, and skeletal tissues. However, measuring tissue contraction in vitro often requires the use of high number of cells per tissue construct along with time-consuming microscopy and image analysis. Here, we present an inexpensive, versatile, high-throughput platform to measure microtissue contraction in a 96-well plate configuration using one-step batch imaging. More specifically, optical fiber microprobes are embedded in microtissues, and contraction is measured as a function of the deflection of optical signals emitted from the end of the fibers. Signals can be measured from all the filled wells on the plate simultaneously using a digital camera. An algorithm uses pixel-based image analysis and computer vision techniques for the accurate multiwell quantification of positional changes in the optical microprobes caused by the contraction of the microtissues. Microtissue constructs containing 20,000-100,000 human ventricular cardiac fibroblasts (NHCF-V) in 6 mg/mL collagen type I showed contractile displacements ranging from 20-200 µm. This highly sensitive and versatile platform can be used for the high-throughput screening of microtissues in disease modeling, drug screening for therapeutics, physiology research, and safety pharmacology.