将基于脑电图的服务集成到消费电子产品中

Youngrae Kim, Jinyoung Moon, Hyung-Jik Lee, Changseok Bae, Sungwon Sohn
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引用次数: 7

摘要

商品化的脑电图传感器可以更便宜、更方便地提取脑电图数据。由于商品化的脑电信号传感器可以普遍使用,因此需要对脑电信号所能提供的服务以及脑电信号所能实现的交互进行研究。在本文中,我们展示了将基于EEG的服务和交互集成到使用商业化EEG传感器的消费电子产品中的可行性。我们使用支持向量机(SVM)分类器对用户的状态进行分类,使用从感兴趣的对象和噪声中收集的EEG数据。结果表明,商用脑电信号传感器采集的脑电信号可以用于用户状态分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of electroencephalography based services into consumer electronics
Commercialized electroencephalography (EEG) sensors are available that one could extract EEG data more cheaply and more easily. As commercialized EEG sensors can be used commonly, the services that could be provided using EEG and interactions that can be achieved by EEG are needed to be studied. In this paper, we show the feasibility of integrating EEG based services and interactions into consumer electronics using commercialized EEG sensors. We use support vector machine (SVM) classifiers to classify the user's status using EEG data gathered from objects of interest and noise. The results show that EEG gathered from commercialized EEG sensors can be used to classify the user's status.
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