CAREER: Advanced data analytics and high-resolution cervical auscultation can accurately predict dysphagia

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1652203- SejdicDysphagia (swallowing disorders) causes 150,000 annual hospitalizations, increases pneumonia incidence, and adds 220,000 additional days to hospital admissions each year. Dysphagia risk is currently assessed via screening, and a failed screen then leads to the diagnostic gold-standard, the videofluoroscopic x-ray test. However, many patients who aspirate (take food or drink into their lungs) pass initial screens because they aspirate silently. Therefore, this CAREER project proposes to develop fundamentally new computational tools to be used in conjunction with high-resolution vibration and sound recordings from the neck to screen for dysphagia. First, the project will advance computational models to detect the activities of swallowing from vibration and sound recordings from the neck. Second, the project will advance techniques for making vibration and sound recordings from the neck to better understand how the airway normally protects itself during swallowing to avoid aspiration, and how this is affected during dysphagia. Success in this project will reduce incidence of silent aspiration, but it will also reduce the necessity for overly conservative recommendations that might limit eating and drinking for individuals with neurological disabilities (e.g. stroke, MS, ALS) who are at greater risk of dysphagia. Educational and outreach activities focus on increasing interest in applying new computational techniques to swallowing disorders, as well as encouraging underrepresented groups of students to pursue education and careers in STEM fields.The PI's long-term research goal is to utilize computational approaches and instrumentation to nurture translation of innovative engineering research to clinically relevant solutions for dysphagia. Therefore, the research objective of this CAREER proposal is the advancement of fundamentally new data analytics tools to be used in conjunction with high-resolution cervical auscultation (HRCA - accelerometer and microphone recordings from the neck) in order to instrumentally screen for dysphagia. The HRCA screening device can detect pharyngeal vibrations caused by dysphagia. As of yet the current device cannot detect silent aspiration before patients are placed at risk. New fundamental advances in data analytics are needed, which is the main research contribution of the proposed program. The PI?s long-term educational goal is to translate advances in dysphagia data analytics into educational modules that will be disseminated to a wide clinical and engineering audience. Hence, the educational objective is to create interdisciplinary training opportunities for high school (e.g., educational modules to be distributed across the US), engineering undergraduate, and graduate students (e.g., an easily accessible open online course), while disseminating the results of this project to a clinical audience as well (e.g., grand rounds). In addition, projects will focus on encouraging underrepresented groups to pursue education and career opportunities in STEM fields.