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Research on vehicle control technology of brain-computer interface based on SSVEP
Author(s): Sheng Long; Zongtan Zhou; Yang Yu; Yadong Liu; Nannan Zhang
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Paper Abstract

In this paper, we propose an asynchronous paradigm for controlling a car using steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) and conduct experimental tests on real car outside the laboratory. The paradigm uses six stimulation frequencies to classify targets by canonical correlation analysis (CCA) method and generates multi-task vehicle control strategies, including left and right turn signals, wipers, horns, doors and hazard lights. Four healthy volunteers participated in the online car control experiment, and the average correct rate reached 88.43%. Subject S1 showed the most satisfactory BCI-based performance, and its true positive rate and false positive rate were in line with expectations. The research shows the feasibility and effectiveness of the paradigm in automotive control applications, which lays the foundation for future research and development of related brain-controlled automotive technologies, thereby helping individuals with mobility impairments to provide supplements or alternatives, and can also provide an auxiliary vehicle driving strategy for healthy people.

Paper Details

Date Published: 27 November 2019
PDF: 10 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113212Q (27 November 2019); doi: 10.1117/12.2549159
Show Author Affiliations
Sheng Long, National Univ. of Defense Technology (China)
Zongtan Zhou, National Univ. of Defense Technology (China)
Yang Yu, National Univ. of Defense Technology (China)
Yadong Liu, National Univ. of Defense Technology (China)
Nannan Zhang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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