Silent Aspiration Detection
CWSF · 2026 Disease & Illness Gold Medal
Overview
My project is about building a wearable device that can detect signs of silent aspiration, a condition where food or liquid enters the airway without causing a cough. This is important because it can lead to serious health problems if not noticed early. I studied how different throat actions, like swallowing, coughing, and talking, create unique vibration patterns. Using sensors placed on the neck, I collected data from these activities and compared normal patterns to unusual ones. I then used machine learning, which teaches a computer to recognize patterns, to help identify these differences more accurately. This project matters because it could lead to a simple, at-home tool that warns people early and helps prevent serious health issues.
Awards (2)
- Gold Medal
- Selected for CWSF 2026
Competition history
- CWSF 2026
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