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An open-source framework for synthetic post-dive Doppler ultrasound audio generation. | LitMetric

AI Article Synopsis

  • Doppler ultrasound (DU) is used to detect venous gas emboli (VGE) after diving, but existing automated methods for assessment have limitations due to small datasets and lack of objective evaluation.
  • The authors developed a method to create synthetic DU data based on real signals, allowing variability in bubbling to match established grading systems.
  • This work includes baseline recordings and code for synthetic data generation, aiming to advance research in VGE analysis and improve signal processing methodologies.

Article Abstract

Doppler ultrasound (DU) measurements are used to detect and evaluate venous gas emboli (VGE) formed after decompression. Automated methodologies for assessing VGE presence using signal processing 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138468PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0284922PLOS

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