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首页> 外文期刊>IEEE Transactions on Biomedical Engineering >Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives
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Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives

机译:基于上下文的脑电图中癫痫发作急剧瞬变的自动检测:消除假阳性

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摘要

A description is given of a knowledge-based system for the elimination of false positives in the automated detection of epileptogenic sharp transients in the EEG (electroencephalogram). The system makes comprehensive use of spatial and temporal context information available on 16 channels of EEG. EKG, (electrocardiogram) EMG (electromyogram), and EOG (electrooculogram). A knowledge-based implementation is used because of the ease with which it allows the contextual rules to be expressed and refined. The resulting system is shown to be capable of rejecting a wide variety of artifacts commonly found in EEG recordings that cause numerous false positive detections in systems making less comprehensive use of context.
机译:给出了一种基于知识的系统的描述,该系统可用于在自动检测EEG(脑电图)中的癫痫发作急瞬变过程中消除误报。该系统综合利用了EEG的16个通道上可用的空间和时间上下文信息。 EKG,(心电图)EMG(肌电图)和EOG(心电图)。使用基于知识的实现是因为它易于表达和完善上下文规则。所显示的系统显示出能够拒绝在EEG录音中常见的各种伪像,这些伪像会导致在对上下文的综合利用较少的系统中引起大量误报检测。

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