DOI: 10.5061/dryad.xgxd254kp
title: Synthetic post-dive precordial and subclavian Doppler ultrasound using Kisman-Masurel and Spencer grades

description: Doppler ultrasound (DU) measurements are used to detect and evaluate
 venous gas emboli (VGE) formed after decompression. Automated analysis
 methodologies of these VGE have been developed on varying real-world
 datasets of limited size and without ground truth values preventing
 objective evaluation. We develop and report a method to generate synthetic
 post-dive data using DU signals collected in both precordium and
 subclavian vein with varying degrees of bubbling matching field-standard
 grading metrics. This method is adaptable, modifiable, and reproducible,
 allowing for researchers to tune the produced dataset for their desired
 purpose. We provide the baseline Doppler recordings and code required to
 generate synthetic data for researchers to reproduce our work and improve
 upon it. We also provide a set of pre-made synthetic post-dive DU data
 spanning six scenarios representing the Spencer and Kisman-Masurel (KM)
 grading scales as well as precordial and subclavian DU recordings. By
 providing a method for synthetic post-dive DU data generation, we aim to
 improve and accelerate the development of signal processing techniques for
 VGE analysis in Doppler ultrasound. 
description: Baseline data: 1) Human Precordial Doppler
 Data: The study collected precordial Doppler ultrasound recordings from 16
 healthy volunteers who gave informed consent and were free of heart
 murmurs. The recordings were obtained using two different Doppler
 ultrasound systems, Continuous and Pulsed wave (CW and PW) with the same
 precordial transducer. The audio signals were recorded using an
 Analog-to-Digital converter and Audacity software. Ten subjects were
 measured with both CW and PW systems, and five were measured using only
 the CW system. Each recording lasted between 3:30 to 7 minutes. The study
 was approved by the Duke Health Institutional Review Board.
 2) Human Subclavian Doppler Data: Subclavian Doppler ultrasound
 data was collected from 75 healthy volunteers. The data was de-identified
 and the study was approved by the DAN institutional review board
 (#024-19-22) with informed consent provided by the subjects. The
 O'Dive continuous wave Doppler device was used to perform the
 subclavian Doppler ultrasound, with measurements taken on both the left
 and right subclavian veins at rest. The data was recorded on an iPad at a
 sampling frequency of 48 kHz, and each recording lasted between 18-20
 seconds. 3) Bubble-only Doppler recordings: A
 tissue-mimicking flow phantom was created using porcine gelatin,
 1-propanol, and distilled water. A peristaltic pump was connected to the
 phantom vessel inlet and outlet, with a water reservoir to allow bubbles
 to dissipate without recirculation. Doppler ultrasound measurements were
 acquired using a Siemens/Acuson Sequoia C512 with a transducer set to
 pulse-wave Doppler mode, and the Doppler audio output was recorded using
 Audacity with a sampling frequency of 44.1 kHz. The pump was set to
 various flow rates, and the transducer was placed at different angles
 relative to the water flow. An air-filled syringe was used to inject
 individual bubbles into the flowing water, with recordings of 25-second
 duration taken for each parameter combination. An additional experiment
 was performed with the pump flow randomly varying between 540-900 mL/min
 at each specified angle, producing a total of 45 recordings. Individual
 bubbles were isolated using a thresholding algorithm and saved as a .mat
 file. Fully synthetic data: Using
 the baseline human Doppler audio, a procedure was created that performs a
 mixing of audio with bubbles inserted into the blood flow signals. The
 amount of bubbling was determined using a modified Kisman-Masurel scale
 and includes data augmentation to increase the variability for bubbles and
 cardiac sounds. Different processing methods were employed for precordial
 such that bubbles can be found in any part of the cardiac cycle or can
 only be heard in between cycles (to represent bubbles that are most likely
 to be heard). Data was generated using 2 grading
 scales: Kisman-Masurel (22 classes) or Spencer (5 classes).
description: To generate synthetic data Matlab must be used. Otherwise, all
 data is saved as .wav files and can be opened with any audio processing
 software.