Capstone Project

SmartDrop

Problem

Self-administering eyedrops is difficult for older adults and those with vision or mobility issues due to hand tremors, poor vision, and difficulty tilting the head. This often leads to missed doses, incorrect application, and poor adherence to medication schedules.

Approach

The team conducted interviews with target users and subject matter experts, followed by thematic analysis and iterative prototyping. They tested functionality and usability through 15 studies to refine the solution.

Solution

SmartDrop is a handheld device paired with a mobile app that uses deep learning for blink and drop detection, real-time guidance, adherence tracking, and auto-dispensing. It enhances independence and accuracy in medication delivery.

Team Members

Ruiqing Wang

Sam Wong

Leo Peng

Jassie He

View the team's poster here (PDF)