论文标题
BCI控制的免提轮椅导航与避免障碍物
BCI-Controlled Hands-Free Wheelchair Navigation with Obstacle Avoidance
论文作者
论文摘要
大脑计算机界面（BCI）广泛用于阅读大脑信号并将其转换为现实世界运动。但是，由BCI产生的信号很吵，很难分析。本文专门旨在将BCI的最新技术与超声传感器相结合，以提供可以在拥挤的环境中有效导航的免提轮椅。这种组合提供了BCI导航系统所需的安全性和避免障碍物功能，以获得更大的信心并以相对较高的速度操作轮椅。六个人口的人群测试了BCI控制器和避免障碍物的特征。受试者能够通过将目标从起跑位置移至预定义的位置，在训练10分钟后，将目标从开始位置转移到预定义的位置，平均将目标从起跑位置转移到预定义的位置，并在心理上控制轮椅的目的地。轮椅成功地避免了测试期间受试者放置的所有障碍。
Brain-Computer interfaces (BCI) are widely used in reading brain signals and converting them into real-world motion. However, the signals produced from the BCI are noisy and hard to analyze. This paper looks specifically towards combining the BCI's latest technology with ultrasonic sensors to provide a hands-free wheelchair that can efficiently navigate through crowded environments. This combination provides safety and obstacle avoidance features necessary for the BCI Navigation system to gain more confidence and operate the wheelchair at a relatively higher velocity. A population of six human subjects tested the BCI-controller and obstacle avoidance features. Subjects were able to mentally control the destination of the wheelchair, by moving the target from the starting position to a predefined position, in an average of 287.12 seconds and a standard deviation of 48.63 seconds after 10 minutes of training. The wheelchair successfully avoided all obstacles placed by the subjects during the test.
