Honorable Mention
Tracking fine-grained finger movements with IMUs for continuous 2D-cursor control poses significant challenges due to limited sensing capabilities. Our findings suggest that finger-motion patterns and the inherent structure of joints provide beneficial physical knowledge, which lead us to enhance motion perception accuracy by integrating physical priors into ML models. We propose MouseRing, a novel ring-shaped IMU device that enables continuous finger-sliding on unmodified physical surfaces like a touchpad. A motion dataset was created using infrared cameras, touchpads, and IMUs. We then identified several useful physical constraints, such as joint co-planarity, rigid constraints, and velocity consistency. These principles help refine the finger-tracking predictions from an RNN model. By incorporating touch state detection as a cursor movement switch, we achieved precise cursor control. In a Fitts’ Law study, MouseRing demonstrated input efficiency comparable to touchpads. In real-world applications, MouseRing ensured robust, efficient input and good usability across various surfaces and body postures.
doi.org/10.1145/3613904.3642225
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)