寨卡病毒感染的小头畸形儿童中高度节律失调的识别

Identification of Hypsarrhythmia in Children with Microcephaly Infected by Zika Virus.

作者信息

Sousa Gean Carlos, Queiroz Claudio M, Sousa Patrícia, Lima Priscila, Silva Antônio Augusto Moura da, Pires Nilviane, Barros Allan Kardec

机构信息

Department of Electrical Engineering, Federal University of Maranhão (UFMA), São Luís-MA 65080-805, Brazil.

Brain Institute, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.

出版信息

Entropy (Basel). 2019 Feb 28;21(3):232. doi: 10.3390/e21030232.

Abstract

Hypsarrhythmia is an electroencephalographic pattern specific to some epileptic syndromes that affect children under one year of age. The identification of this pattern, in some cases, causes disagreements between experts, which is worrisome since an inaccurate diagnosis can bring complications to the infant. Despite the difficulties in visually identifying hypsarrhythmia, options of computerized assistance are scarce. Aiming to collaborate with the recognition of this electropathological pattern, we propose in this paper a mathematical index that can help electroencephalography experts to identify hypsarrhythmia. We performed hypothesis tests that indicated significant differences in the groups under analysis, where the -values were found to be extremely small.

摘要

高峰失律是一种特定于某些影响一岁以下儿童的癫痫综合征的脑电图模式。在某些情况下,这种模式的识别会导致专家之间的分歧,这令人担忧,因为不准确的诊断会给婴儿带来并发症。尽管在视觉上识别高峰失律存在困难,但计算机辅助选项却很少。为了协助识别这种电病理模式,我们在本文中提出了一种数学指标,该指标可以帮助脑电图专家识别高峰失律。我们进行了假设检验,结果表明在分析的组中存在显著差异,其中p值被发现极小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/266c/7514713/abbc8695e7e6/entropy-21-00232-g001.jpg

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