Tracking continuous 2D sequential handwriting trajectories accurately using a single IMU ring is extremely challenging due to the significant displacement between the IMU's wearing position and the location of the tracked fingertip. We propose WritingRing, a system that uses a single IMU ring worn at the base of the finger to support natural handwriting input and provide real-time 2D trajectories. To achieve this, we first built a handwriting dataset using a touchpad and an IMU ring (N=20). Next, we improved the LSTM model by incorporating streaming input and a TCN network, significantly enhancing accuracy and computational efficiency, and achieving an average trajectory accuracy of 1.63mm. Real-time usability studies demonstrated that the system achieved 88.7% letter recognition accuracy and 68.2% word recognition accuracy, which reached 84.36% when restricting the output to words within a vocabulary of size 3000. WritingRing can also be embedded into existing ring systems, providing a natural and real-time solution for various applications.
https://dl.acm.org/doi/10.1145/3706598.3714066
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