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SYSTEMS AND METHOD PROVIDING A UNIFIED FRAMEWORK FOR DE-NOISING NEURAL SIGNALS

机译:提供用于对神经信号进行去噪的统一框架的系统和方法

摘要

A method removing artifacts from neural signals comprises receiving electroencephalography (EEG) data from an EEG system and providing the EEG data to a unified artifact removal framework for cleaning artifacts. The EEG data is provided to a first cleaning framework utilizing the first reference to clean first artifacts from the EEG data, and the outputting the EEG data from the first cleaning framework to a second cleaning framework. The second cleaning framework may operate in a similar manner utilizing second reference to clean second artifacts from the EEG data. This general process may be repeated as desired to clean various artifacts from EEG data, when a suitable reference for the artifacts to be removed is utilized. The frameworks utilize H∞ method or filtering involving a H∞ adapting rule to properly weigh the reference, and combining the subsequent output with incoming EEG data results in the desired removal of artifacts.
机译:一种从神经信号中去除伪像的方法,包括从EEG系统接收脑电图(EEG)数据,并将EEG数据提供给用于清除伪像的统一伪像去除框架。利用第一参考将EEG数据提供给第一清洁框架,以从EEG数据中清洁第一伪像,并将EEG数据从第一清洁框架输出到第二清洁框架。第二清洁框架可以利用第二参考以从EEG数据中清洁第二伪像的类似方式操作。当利用针对要去除的伪像的合适参考时,可以根据需要重复该一般过程以从EEG数据中清除各种伪像。框架利用H∞方法或涉及H∞自适应规则的滤波来适当地加权参考,并将后续输出与传入的EEG数据组合在一起,从而实现了所需的伪像去除。

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