Background

Tooth decay and gum diseases are among the most prevalent chronic diseases in both children and adults, most of these issues stem from an accumulation of dental plague and failure in teeth care. Although regular tooth brushing is recommended by the American Dental Association, today?s electric toothbrushes don?t detect the quality of tooth brushing. This application utilizes a learning algorithm to detect tooth brushing activity. The system is able to collect data in regards to surface coverage and brushing frequency.

Technology

Using real-time feedback, the application is able to detect a variety of different gestures. The watch is connected to a hand held device using Blue tooth, sending results to be displayed and creating a brushing quality assessment. Incorrect tooth brushing technique is less effective and may lead to the permanent damage of the enamel.

Advantages

Extensive evaluation results demonstrate that the design reliably detects the brushing activity with 96.4% accuracy, and recognizes gestures of brushing different surfaces of teeth with 83.6% accuracy.