基于脑机接口的电动轮椅控制

Nobuaki Kobayashi, M. Nakagawa
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引用次数: 8

摘要

脑机接口(BCI)作为连接大脑与外部设备的接口一直备受关注。然而,为了实现脑机接口,必须建立准确识别大脑状态的方法,并且仍然存在许多挑战。本文提出了一种新的脑机接口系统,该系统利用情绪分形分析方法(EFAM)准确识别和分离喜悦、愤怒、悲伤和快乐等情绪,并根据脑电图数据对情绪进行量化,并利用这些信息控制电动轮椅。使用这种方法,可以实现55-60%的高平均识别情绪(喜悦,愤怒,悲伤和快乐)和97%以上的显着高隔离率。基于EFAM实时获取的情绪数据,我们开发了脑机接口电路来控制电动轮椅。使用这种电路,电动轮椅的速度可以根据情绪的强度来调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BCI-based control of electric wheelchair
BCI (Brain-computer Interface) has been attracting attention as an interface to connect the brain to external devices. However, it is essential to establish methods to recognize the brain state accurately in order to implement BCI, and a number of challenges still remain. Here, we suggest a novel BCI system that accurately recognizes and isolates emotions like delight, anger, sorrow, and pleasure using an Emotion Fractal Analysis Method (EFAM), which can quantify emotions based on data obtained by electroencephalography, and control an electric wheelchair using the information. With this method, a high average rate of recognizing emotions (delight, anger, sorrow, and pleasure) of 55-60% and markedly high rate of isolating them of over 97% can be achieved. We developed the BCI circuit to control an electric wheelchair based on data on emotions obtained in realtime by EFAM. Using this circuit, the speed of an electric wheelchair can be adjusted by the intensity of emotions.
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