精神控制无人机:一种创新的基于SSVEP的多级脑机接口

Andrei Chiuzbaian, J. Jakobsen, S. Puthusserypady
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引用次数: 22

摘要

在神经退行性疾病的背景下,失去的一个关键因素是自由探索和与我们周围世界互动的可能性。本文提出的工作重点是开发一种脑控辅助装置(AD),以帮助个人在计算机和他们的思想的帮助下探索周围的世界。通过使用基于非侵入性稳态视觉诱发电位(SSVEP)的脑机接口(BCI)系统的电位,用户可以在三维物理空间中控制飞行机器人(也称为UAV或无人机)。从安装在无人机上的摄像机接收到的视频流中,用户可以在3D控制无人机的同时体验一定程度的自由。本研究中提出的系统使用一种名为Emotiv Epoch的面向消费者的耳机来记录脑电图(EEG)数据。该系统在10名健全的受试者身上进行了测试,检测到四种不同的ssvep (5.3 Hz, 7 Hz, 9.4 Hz和13.5 Hz),并将其用作驱动无人机的控制信号。为了引出每个SSVEP,开发了一个高度可定制的可视化界面。用8阶巴特沃斯带通滤波器对记录的数据进行滤波,然后对信号进行快速傅里叶变换(FFT)频谱分析,对每个SSVEP进行检测和分类。该BCI系统的平均信息传输速率(ITR)为10 bit /min,阳性预测值(PPV)为92.5%。最后进行的测试表明,本文提出的系统可以轻松地在三维空间中控制无人机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mind Controlled Drone: An Innovative Multiclass SSVEP based Brain Computer Interface
A crucial element lost in the context of a neurodegenerative disease is the possibility to freely explore and interact with the world around us. The work presented in this paper is focused on developing a brain-controlled Assistive Device (AD) to aid individuals in exploring the world around them with the help of a computer and their thoughts. By using the potential of a noninvasive Steady-State Visual Evoked Potential (SSVEP)-based Brain Computer Interface (BCI) system, the users can control a flying robot (also known as UAV or drone) in 3D physical space. From a video stream received from a video camera mounted on the drone, users can experience a degree of freedom while controlling the drone in 3D. The system proposed in this study uses a consumer-oriented headset, known as Emotiv Epoch in order to record the electroencephalogram (EEG) data. The system was tested on ten able-bodied subjects where four distinctive SSVEPs (5.3 Hz, 7 Hz, 9.4 Hz and 13.5 Hz) were detected and used as control signals for actuating the drone. A highly customizable visual interface was developed in order to elicit each SSVEP. The data recorded was filtered with an 8th order Butterworth bandpass filter and a fast Fourier transform (FFT) spectral analysis of the signal was applied in other to detect and classify each SSVEP. The proposed BCI system resulted in an average Information Transfer Rate (ITR) of 10 bits/min and a Positive Predictive Value (PPV) of 92.5%. The final conducted tests have demonstrated that the system proposed in this paper can easily control a drone in 3D space.
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