@article{azarang_blogg_currens_lance_moon_lindholm_papadopoulou_2023, title={Development of a graphical user interface for automatic separation of human voice from Doppler ultrasound audio in diving experiments}, volume={18}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0283953}, abstractNote={Doppler ultrasound (DU) is used in decompression research to detect venous gas emboli in the precordium or subclavian vein, as a marker of decompression stress. This is of relevance to scuba divers, compressed air workers and astronauts to prevent decompression sickness (DCS) that can be caused by these bubbles upon or after a sudden reduction in ambient pressure. Doppler ultrasound data is graded by expert raters on the Kisman-Masurel or Spencer scales that are associated to DCS risk. Meta-analyses, as well as efforts to computer-automate DU grading, both necessitate access to large databases of well-curated and graded data. Leveraging previously collected data is especially important due to the difficulty of repeating large-scale extreme military pressure exposures that were conducted in the 70-90s in austere environments. Historically, DU data (Non-speech) were often captured on cassettes in one-channel audio with superimposed human speech describing the experiment (Speech). Digitizing and separating these audio files is currently a lengthy, manual task. In this paper, we develop a graphical user interface (GUI) to perform automatic speech recognition and aid in Non-speech and Speech separation. This constitutes the first study incorporating speech processing technology in the field of diving research. If successful, it has the potential to significantly accelerate the reuse of previously-acquired datasets. The recognition task incorporates the Google speech recognizer to detect the presence of human voice activity together with corresponding timestamps. The detected human speech is then separated from the audio Doppler ultrasound within the developed GUI. Several experiments were conducted on recently digitized audio Doppler recordings to corroborate the effectiveness of the developed GUI in recognition and separations tasks, and these are compared to manual labels for Speech timestamps. The following metrics are used to evaluate performance: the average absolute differences between the reference and detected Speech starting points, as well as the percentage of detected Speech over the total duration of the reference Speech. Results have shown the efficacy of the developed GUI in Speech/Non-speech component separation.}, number={8}, journal={PLOS ONE}, author={Azarang, Arian and Blogg, S. Lesley and Currens, Joshua and Lance, Rachel M. and Moon, Richard E. and Lindholm, Peter and Papadopoulou, Virginie}, year={2023}, month={Aug} }
 @misc{currens_dayton_buzzacott_papadopoulou_2022, title={Hyperbaric exposure in rodents with non- invasive imaging assessment of decompression bubbles: A scoping review protocol}, volume={17}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0274241}, abstractNote={Hyperbaric pressure experiments have provided researchers with valuable insights into the effects of pressure changes, using various species as subjects. Notably, extensive work has been done to observe rodents subjected to hyperbaric pressure, with differing imaging modalities used as an analytical tool. Decompression puts subjects at a greater risk for injury, which often justifies conducting such experiments using animal models. Therefore, it is important to provide a broad view of previously utilized methods for decompression research to describe imaging tools available for researchers to conduct rodent decompression experiments, to prevent duplicate experimentation, and to identify significant gaps in the literature for future researchers. Through a scoping review of published literature, we will provide an overview of decompression bubble information collected from rodent experiments using various non-invasive methods of ultrasound for decompression bubble assessment. This review will adhere to methods outlined by the Joanna Briggs Institute Manual for Evidence Synthesis and be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). Literature will be obtained from the PubMed, Embase, and Scopus databases. Extracted sources will first be sorted to a list for inclusion based on title and abstract. Two independent researchers will then conduct full-text screening to further refine included papers to those relevant to the scope. The final review manuscript will cover methods, data, and findings for each included publication relevant to non-invasive in vivo bubble imaging.}, number={9}, journal={PLOS ONE}, author={Currens, Joshua and Dayton, Paul A. and Buzzacott, Peter and Papadopoulou, Virginie}, year={2022}, month={Sep} }