Mobile-AeroText: Air Writing Recognition of Japanese Hiragana for Practical Touchless Text Input

This study proposes an air-handwriting recognition technique that enables seamless, touchless text input in environments such as public displays, in-vehicle systems, and AR glasses. By leveraging intuitive handwriting, the approach expands the design space for human-computer interaction in contexts where physical keyboards or touchscreens are impractical. It offers potential privacy advantages by eliminating the need for voice or touch input, and promotes inclusivity by supporting arbitrary vocabulary without relying on predefined lexicons or prior training. The proposed system, Mobile-AeroText, employs a single-stage object detection network based on GELAN. It transforms fingertip trajectories into binary images while simultaneously detecting and recognizing character regions, enabling robust word-level recognition without explicit boundary gestures. In an evaluation with 25 participants and 1, 600 words, Mobile-AeroText achieved a word recognition rate of 91.44%, a character recognition rate of 95.86%, and an average latency of 417 milliseconds on a CPU. Subjective assessments yielded a System Usability Scale score of 78.5 and a NASA-TLX score of 33.6, indicating high usability and low cognitive load. Overall, this study presents a practical “write-anywhere” input method that addresses a fundamental challenge in human-computer interaction: enabling expressive, accessible, and low-burden text input in scenarios where traditional methods are unavailable or limited.