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All Journal JOIV : International Journal on Informatics Visualization
Nakajima, Rio
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Computer Science & IT

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Image Presentation Method for Human Machine Interface Using Deep Learning Object Recognition and P300 Brain Wave Nakajima, Rio; Rusydi, Muhammad Ilhamdi; Ramadhani, Salisa Asyarina; Muguro, Joseph; Matsushita, Kojiro; Sasaki, Minoru
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.949

Abstract

Welfare robots, as a category of robotics, seeks to improve the quality of life of the elderly and patients by availing a control mechanism to enable the participants to be self-dependent. This is achieved by using man-machine interfaces that manipulate certain external processes like feeding or communicating. This research aims to realize a man-machine interface using brainwave combined with object recognition applicable to patients with locked-in syndrome. The system utilizes a camera with pretrained object-detection system that recognizes the environment and displays the contents in an interface to solicit a choice using P300 signals. Being a camera-based system, field of view and luminance level were identified as possible influences. We designed six experiments by adapting the arrangement of stimuli (triangular or horizontal) and brightness/colour levels. The results showed that the horizontal arrangement had better accuracy than the triangular method. Further, colour was identified as a key parameter for the successful discrimination of target stimuli. From the paper, the precision of discrimination can be improved by adopting a harmonized arrangement and selecting the appropriate saturation/brightness of the interface.
Co-Authors Matsushita, Kojiro Muguro, Joseph Muhammad Rusydi H. Ramadhani, Salisa 'Asyarina Sasaki, Minoru