Mohebbi Ali, Engelsholm Signe K D, Puthusserypady Sadasivan, Kjaer Troels W, Thomsen Carsten E, Sorensen Helge B D
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:602-5. doi: 10.1109/EMBC.2015.7318434.
In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO(®) MINDSTORM(®) EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.
在这项初步研究中，开发了一种新颖且简约的基于脑机接口（BCI）的轮椅控制应用程序。该系统基于伪随机码调制视觉诱发电位（c-VEPs）。该方案中的视觉刺激基于Gold码生成，并且使用特定于受试者的算法对视觉诱发电位进行识别和分类。该系统能够根据诱发的c-VEPs在4个不同方向上控制轮椅模型（乐高（®）MINDSTORM（®）EV3机器人）。在测试该系统时对10名健康受试者进行了评估，平均准确率达到了97%。这些有前景的结果说明了在考虑实际轮椅应用时这种方法的潜力。
