title: Real-Time "Eye-Writing" Recognition Using Electrooculogram.
abstract: Eye movements can be used as alternative inputs for human-computer interface (HCI) systems such as virtual or augmented reality systems as well as new communication ways for patients with locked-in syndrome. In this study, we developed a real-time electrooculogram (EOG)-based eye-writing recognition system, with which users can write predefined symbolic patterns with their volitional eye movements. For the "eye-writing" recognition, the proposed system first reconstructs the eye-written traces from EOG waveforms in real-time; then, the system recognizes the intended symbolic inputs with a reliable recognition rate by matching the input traces with the trained eye-written traces of diverse input patterns. Experiments with 20 participants showed an average recognition rate of 87.38% (F1 score) for 29 different symbolic patterns (26 lower case alphabet characters and three functional input patterns representing Space, Backspace, and Enter keys), demonstrating the promise of our EOG-based eye-writing recognition system in practical scenarios.
authors.lastname: Kwang-Ryeol Lee
authors.lastname: Won-Du Chang
authors.lastname: Sungkean Kim
authors.lastname: Chang-Hwan Im
mesh_terms: D000465:Algorithms; D003143:Communication Devices for People with Disabilities; D003199:Computer Systems; D004585:Electrooculography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated / Q000379:methods*; D015443:Word Processing; D014956:Writing; D055815:Young Adult