This paper presents an Arabic letter encoding system for eye-tracking–based communication designed to assist individuals with locked-in syndrome. Using electrooculography (EOG), eye movements are translated into Arabic text based on an existing eye-movement database. The proposed approach assigns specific stroke combinations to Arabic characters, inspired by Katakana character formation. First, the characteristics of EOG signals are analyzed. Next, code- protocol–based eye-input systems for Katakana characters are reviewed. Based on these principles, a set of basic strokes for Arabic letters is defined, followed by a novel Arabic letter encoding scheme, which constitutes the main contribution of this work. A second contribution is the adaptation of this encoding scheme to extract the corresponding EOG signals. The proposed system adopts a semantic approach in which visually similar Arabic letters share related eye strokes, improving intuitiveness and ease of learning. The resulting dataset contains 2,500 records and enables accurate decoding of EOG data into Arabic text, demonstrating its potential as a non-verbal communication tool for individuals with severe physical disabilities.