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Improvements resulting from respiratory-swallow phase training visualized in patient-specific computational analysis of swallowing mechanics.

Thi Tu Anh TranBonnie Martin HarrisWilliam G Pearson
Published in: Computer methods in biomechanics and biomedical engineering. Imaging & visualization (2016)
The aim of this study was to visualize improved swallowing mechanics resulting from respiratory-swallow phase training using patient specific computational analysis of Modified Barium Swallow (MBS) videofluoroscopic images. Imaging from a single subject showing improved MBSImP™© scores in 17 of 18 pre- to post-treatment swallows was selected for analysis. Using a semi-automated MATLAB tracker tool, a frame-by-frame annotation of 10 coordinates mapping muscle functional groups was performed during oropharyngeal swallowing. Computational analysis of coordinate shape change was executed using MorphoJ software to determine differences in swallowing mechanics associated with multiple independent variables. Canonical variant analysis indicated significant differences in mechanics associated with respiratory-swallow phase training (D=1.92,p<.0001). Vectors allowed for visualization of changes in swallowing mechanics associated with respiratory-swallow phase training. A regression of shape associated with laryngeal vestibular closure on respiratory-swallow phase training was highly significant (p<.0001) and accounted for 94.1% of the variance.
Keyphrases
  • virtual reality
  • high resolution
  • respiratory tract
  • deep learning
  • machine learning
  • mass spectrometry
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  • electron microscopy