Abstract
This paper presents TongueMendous, an non-intrusive, pervasive tongue-gesture recognition interface for the general population and use cases. It uses an infrared sensor to detect tongue gestures when the tongue sticks in different directions. The collected data is recognized by a tiny machine learning (TinyML) model, allowing TongueMendous to classify tongue gestures on a microcontroller. Evaluations on the initial prototype reported a 91.7% cross-validation accuracy and 89.4% leave-one-person-out accuracy. We also conduct a study to explore the user experience and future design space. These results suggest that the proposed system can be accurate and work well across different users.