Background: Preliminary studies have shown that respiratory– swallow training (RST) is a successful treatment for oropharyngeal head and neck cancer patients with refractory dysphagia. Refining the RST protocol with automated analysis software to provide real-time performance feedback has the potential to improve accessibility, reproducibility, and translation to diverse clinical settings. Method: An automated software program for data acquisition and analysis developed to detect swallows, determine respiratory phase, calculate lung volume at the onset of the swallow, and provide real-time performance feedback was tested for feasibility in a small cohort of healthy adults. Outcome Measures: Percent difference in swallow detection and accuracy of real-time performance feedback of respiratory phase and lung volume at swallowing onset between the automated software and the manual gold standard method were determined. Results: The automated software program accurately detected the onset of the swallow on 91% of the swallows completed during the training trials. Feedback of respiratory phase and lung volume was accurate on 94% of the trials in which the swallow was accurately detected. Conclusions: This novel, automated, and real-time RST software successfully detected the onset of the swallow, respiratory phase, and lung volume at swallow onset and provided appropriate real-time performance feedback with a high degree of accuracy in healthy adults. The software has the potential to improve the accessibility, efficiency, and translation of RST to diverse patient populations.
Bibliographical noteFunding Information:
Funding for this project was provided by Northwestern University.
© 2020 American Speech-Language-Hearing Association.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't