Image Presentation Method for Human Machine Interface Using Deep Learning Object Recognition and P300 Brain Wave

International Journal on Informatics Visualization: JOIV

article

Rio Nakajima¹  Muhammad Ilhamdi Rusydi²  Salisa Asyarina Ramadhani²  Joseph Muguro³  Kojiro Matsushita¹  Minoru Sasaki¹ 

[1] Gifu University;Universitas Andalas;Dedan Kimathi University of Technology, Private Bag

关键词: Image;    human machine interface;    electroencephalogram;    object recognition;    P300.;   

DOI  :  10.30630/joiv.6.3.949

来源: Politeknik Negeri Padang

【 摘 要 】

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.

【 授权许可】

Unknown