Your browser doesn't support javascript.
loading
Towards a comprehensive bedside swallow screening protocol using cross-domain transformation and high-resolution cervical auscultation.
Anwar, Ayman; Khalifa, Yassin; Lucatorto, Erin; Coyle, James L; Sejdic, Ervin.
Afiliação
  • Anwar A; Edward S. Rogers Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada. Electronic address: ayman.anwar@mail.utoronto.ca.
  • Khalifa Y; Center for Research Computing, University of Pittsburgh, Pittsburgh, PA, USA; Information Technology Analytics, University of Pittsburgh, Pittsburgh, PA, USA; Systems and Biomedical Engineering, Cairo University, Giza, Egypt. Electronic address: yassin.khalifa@pitt.edu.
  • Lucatorto E; Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: erb62@pitt.edu.
  • Coyle JL; Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: jcoyle@pitt.edu.
  • Sejdic E; Edward S. Rogers Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada; North York General Hospital, Toronto, ON, Canada. Electronic address: esejdic@ieee.org.
Artif Intell Med ; 154: 102921, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38991399
ABSTRACT
High-resolution cervical auscultation (HRCA) is an emerging noninvasive and accessible option to assess swallowing by relying upon accelerometry and sound sensors. HRCA has shown tremendous promise and accuracy in identifying and predicting swallowing physiology and biomechanics with accuracies equivalent to trained human judges. These insights have historically been available only through instrumental swallowing evaluation methods, such as videofluoroscopy and endoscopy. HRCA uses supervised learning techniques to interpret swallowing physiology from the acquired signals, which are collected during radiographic assessment of swallowing using barium contrast. Conversely, bedside swallowing screening is typically conducted in non-radiographic settings using only water. This poses a challenge to translating and generalizing HRCA algorithms to bedside screening due to the rheological differences between barium and water. To address this gap, we proposed a cross-domain transformation framework that uses cycle generative adversarial networks to convert HRCA signals of water swallows into a domain compatible with the barium swallows-trained HRCA algorithms. The proposed framework achieved a cross-domain transformation accuracy that surpassed 90%. The authenticity of the generated signals was confirmed using a binary classifier to confirm the framework's capability to produce indistinguishable signals. This framework was also assessed for retaining swallow physiological and biomechanical properties in the signals by applying an existing model from the literature that identifies the opening and closure of the upper esophageal sphincter. The outcomes of this model showed nearly identical results between the generated and original signals. These findings suggest that the proposed transformation framework is a feasible avenue to advance HCRA towards clinical deployment for water-based swallowing screenings.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Auscultação / Transtornos de Deglutição / Deglutição Limite: Female / Humans / Male / Middle aged Idioma: En Revista: Artif Intell Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Auscultação / Transtornos de Deglutição / Deglutição Limite: Female / Humans / Male / Middle aged Idioma: En Revista: Artif Intell Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article