Development of Night Time Calling System by Eye Movement Using Wearable Camera

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Abstract

This paper proposes a night time call system using a wearable camera for patients. The proposed system consists of a wearable camera, computer, relay controller, and nurse call. The user wears the wearable camera. All captured eye images are fed to the convolutional neural network to detect the pupil center. When the detected pupil center exceeds a preset threshold value, the computer sends the signal to operate the nurse call via each relay controller. Two experiments were conducted to evaluate the proposed system: verification of the accuracy of pupil center detection and quantitative evaluation of call success. In the former experiment, we collected 2,800 eye images from seven people and conducted a pupil center detection experiment on several training conditions. As a result, an average error of 1.17 pixels was obtained. In the latter experiment, a call experiment was conducted on five healthy people. The experiment time for each subject was about five minutes. The subject experimented while lying on the bed. Twelve audio stimuli were given in one experiment, after getting the stimuli, the subject moved his eye. The correct call in response to the audio stimulus was considered successful, and the precision, recall, and F-measure were calculated. As a result, we obtained the precision, recall, and F-measure of 0.83, 1.00, and 0.91, respectively. These experimental results show the effectiveness of the proposed system.

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Sakamoto, K., Saitoh, T., & Itoh, K. (2020). Development of Night Time Calling System by Eye Movement Using Wearable Camera. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12426 LNCS, pp. 345–357). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60149-2_27

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