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Wavelet Design for Automatic Real-Time Eye Blink Detection and Recognition in EEG Signals

机译:脑电信号实时自动眨眼检测与识别的小波设计

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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)记录中检测到眨眼,并且可以将其理解为某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信号实时检测与眨眼相关的特定模式。这项研究考虑了理论和实践原理,使系统的设计和实现能够精确实时检测EEG信号中的眨眼。该信号或模式容易发生规模变化和多次入射。在我们提出的方法中,设计了一个新的小波来改善眨眼信号的检测和定位。实时操作执行的记录中多次出现闪烁摄动的检测是通过一个窗口来完成的,该窗口给出了对采样的EEG信号进行中的分析的限时投影。

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