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首页> 外文期刊>IAENG Internaitonal journal of computer science >Wavelet Design for Automatic Real-Time Eye Blink Detection and Recognition in EEG Signals
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Wavelet Design for Automatic Real-Time Eye Blink Detection and Recognition in EEG Signals

机译:小波设计,用于自动实时眼睛闪烁检测和EEG信号中识别

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The blinking of an eye can be detected in electroencephalographic (EEG) recordings and can be understood as a useful control signal in some information processing tasks. The detection of a specific pattern associated with the blinking of an eye in real time using EEG signals of a single channel has been analyzed. This study considers both theoretical and practical principles enabling the design and implementation of a system capable of precise real-time detection of eye blinks within the EEG signal. This signal or pattern is subject to considerable scale changes and multiple incidences. In our proposed approach, a new wavelet was designed to improve the detection and localization of the eye blinking signal. The detection of multiple occurrences of the blinking perturbation in the recordings performed in real-time operation is achieved with a window giving a time-limited projection of an ongoing analysis of the sampled EEG signal.
机译:可以在脑电图(EEG)记录中检测眼睛的闪烁,并且可以理解为一些信息处理任务中的有用控制信号。已经分析了使用单个通道的EEG信号实时与眨眼相关联的特定图案。本研究考虑了理论和实用的原理,可以实现能够精确实时检测Eyeg信号中的系统的设计和实现。此信号或模式受到相当大的缩放变化和多种发件。在我们提出的方法中,设计了一种新的小波,以改善眼睛闪烁信号的检测和定位。通过窗口实现在实时操作中执行的录制中进行多次出现的闪烁扰动的检测,窗口提供了对采样的EEG信号的持续分析的时间有限的投影。

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