Design and development of an EOG-based simplified Chinese eye-writing system

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Eye movement information provides an alternative way for patients with muscular and neurological disorders to communicate with other people or devices. Electrooculography (EOG) is an effective eye movement recording method that has been widely applied to design human–computer interaction systems. In this paper, we propose a simplified Chinese eye-writing system based on EOG (EsCew) by identifying the basic strokes of Chinese characters. Specifically, we first use a bandpass digital filter to preprocess the raw EOG signals to suppress noise interference. Then, we determine the effective eye movement segments according to different strokes by detecting blink signals using the sliding window technique. On this basis, we establish basic stroke templates in terms of the handwriting characteristics of Chinese characters. To reduce the computational complexity, the DTW algorithm is adopted to classify the EOG segments. Finally, we match the stroke sequence with the encoded Chinese characters to obtain the final recognition results. In the lab environment, the recognition experiments are performed on 10 most representative Chinese characters, i.e., ▪. The average accuracies of the basic strokes and Chinese characters are 93.998% and 94.52%, respectively. The experimental results validate the feasibility of the proposed EsCew system. [Display omitted]