基于SSVEP和ERD的非疲劳脑机接口指挥自动驾驶汽车

IF 0.9 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Javier Castillo-Garcia, S. Muller, E. C. Bravo, T. Filho, A. D. Souza
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引用次数: 1

摘要

这项工作描述了一种基于稳态诱发电位(SSVEP)和事件相关去同步(ERD)的非疲劳脑机接口(BCI)的发展,以控制自动驾驶汽车。通过自动驾驶汽车中呈现给用户的图形界面,可以显示目的地。指令的选择是通过视觉刺激和大脑信号来完成的。这些信号被捕获到头皮的枕部区域,并经过处理,以获得自动驾驶汽车规划系统所需的数据。执行的测试获得同步BCI的成功率为90%,异步BCI的成功率为83%。该系统是一种混合脑机接口,包括启用和禁用视觉刺激的能力,减少与使用基于ssvep的脑机接口相关的疲劳。展示这一进展的视频可以在cbeb2020.org/AutonomousCarVideo.mp4上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonfatigating Brain-Computer Interface Based on SSVEP and ERD to Command an Autonomous Car
This work describes the development of a nonfatigating Brain–Computer Interface (BCI) based on Steady State Evoked Potentials (SSVEP) and Event-Related Desynchronization (ERD) to control an autonomous car. Through a graphical interface presented to the user in the autonomous car, destination places are shown. The selection of commands is performed through visual stimuli and brain signals. The signals are captured on the occipital region of the scalp, and are processed in order to obtain the necessary data for the planning system of the autonomous car. Test performed obtained success rate of 90% for a synchronous BCI and 83% for an asynchronous BCI. The proposed system is a hybrid-BCI, which includes the ability to enable and disable the visual stimuli, reducing fatigue associated with the use of SSVEP-based BCIs. The video showing this development can be accessed on: cbeb2020.org/AutonomousCarVideo.mp4.
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来源期刊
Advances in Data Science and Adaptive Analysis
Advances in Data Science and Adaptive Analysis MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
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