The Aspirometer: A Noninvasive Tool for Detecting Aspiration Aim 3

The Aspirometer: A Noninvasive Tool for Detecting Aspiration

This investigation evaluates the effectiveness of a device called the Aspirometer, which uses high resolution cervical auscultation (HRCA), in detecting when food or liquids enter the airway (aspiration) of the person swallowing, whether the person swallowing shows signs of aspiration (coughing) or not.

This aim of the project seeks to discriminate normal from abnormal airway protection and kinematic functions noninvasively via machine-learning analysis of Aspirometer/HRCA (high resolution cervical auscultation) signals, with similar accuracy as human judgment of VF. Hypothesis: Advanced data analytics can detect pathological airway protection in HRCA signal signatures with 90% accuracy when compared to a human expert's airway protection ratings from VF images. Analytical algorithms that can learn from data (e.g., Bayes' learning) will be used to infer about the continuum of abnormal airway protection during swallowing.

Inclusion Criteria:

- referred by an attending physician as an inpatient, for a modified barium swallow examination due to suspected dysphagia and aspiration

Exclusion Criteria:

• tracheostomy
• pregnant
• unable to follow verbal commands
• anatomic disruption of head neck
• radiation therapy to head or neck