IPLAB

Thumb-to-Finger Gesture Recognition Using COTS Smartwatch Accelerometers

Riku Tsunoda, Myungguen Choi, Buntarou Shizuki

Thumb-to-finger gestures, such as 12 phalange taps, provide diverse input. This gesture enables eyes-free, rich, and one-handed smartwatch controls. Previous research on recognizing thumb-to-finger gestures has typically relied on additional sensors, making it difficult to achieve recognition using only a commercial off-the-shelf (COTS) smartwatch. In this paper, we developed a thumb-to-finger gesture recognition system that only uses the accelerometers built into a COTS smartwatch. Our recognition system achieved 80.1% accuracy for 17 gestures. Additionally, we developed optimal gesture sets for different numbers of gestures based on the recognition performance of the accelerometer. Consequently, we achieved 94.7% accuracy for 4 gestures in leave-one-participant-out cross-validation and 90.2% accuracy for 11 gestures in participant-specific leave-one-session-out cross-validation.

Download PDF

References

• Riku Tsunoda, Myungguen Choi, Buntarou Shizuki. 2024. Thumb-to-Finger Gesture Recognition Using COTS Smartwatch Accelerometers. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia (MUM ‘24), pp.184-195 December 1-4, 2024, Stockholm, Sweden, ACM, 12 pages, DOI: https://doi.org/10.1145/3701571.3701600