Classification of hand movement direction based on EEG high-gamma activity.
Classification of hand movement direction based on EEG high-gamma activity.
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基于脑电图高伽马活动的手部运动方向分类。
DOI：
10.1109/embc.2014.6945119
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Principe,JoseC
中科院分区：
文献类型：
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作者：
Loza,CarlosA;Philips,GavinR;Hazrati,MehrnazKh;Daly,JanisJ;Principe,JoseC
脑电图（EEG）是医学领域用于记录和分析大脑活动的非侵入性技术。特别是，脑机接口（BMI）通过假肢、视觉界面和其他物理设备在大脑信号和外部世界之间建立了这座桥梁。本文研究了使用 BMI 时特定手部运动方向与运动过程中脑电图记录之间的关系。利用高γ频带上的通用空间模式方法（CSP）来区分相反的手部运动方向。该实验由三名受试者进行，获得了两种不同情况的平均分类准确率。
The Electroencephalogram (EEG) is a non-invasive technique used in the medical field to record and analyze brain activity. In particular, Brain Machine Interfaces (BMI) create this bridge between brain signals and the external world through prosthesis, visual interfaces and other physical devices. This paper investigates the relation between particular hand movement directions while using a BMI and the EEG recordings during such movement. The Common Spatial Pattern method (CSP) over the high-γ frequency band is utilized in order to discriminate opposite hand movement directions. The experiment is performed with three subjects and the average classification accuracy is obtained for two different cases.