IOTeeth

Overview

Fabricated and deployed PVDF-type sensors in dental retainers. Developed ML solution to detect occlusal disease and evaluated the findings on 12 patients. Designed and built an impact hammer for sensor characterization.

Results

• F1 score of 0.97 for activity recognition with leave-one-out validation
• Average F1 score of 0.92 for dental disease recognition for different activities with leave-one-out validation

Technologies

Python, Machine Learning, C, SolidWorks

Related Paper

• IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition — ACM IMWUT, 2024