Suppr超能文献

正常人和脑瘤患者头皮 EEG 的非线性分析。

Nonlinear analysis of scalp EEGs from normal and brain tumour subjects.

机构信息

Department of Electronics and Communication Engineering, College of Engineering, Guindy, Anna University, Chennai, 600 025, Tamil Nadu, India.

出版信息

Biomed Tech (Berl). 2020 Nov 30;66(2):115-123. doi: 10.1515/bmt-2020-0035. Print 2021 Apr 27.

Abstract

Measurement of features from the chaos theory or as popularly known, the concept of nonlinear dynamics, as indicatives of several pathological conditions and cognition states using the electroencephalography (EEG) signal is very popular. In this paper, the analysis of scalp EEG signals of normal subjects and brain tumour patients using the nonlinear dynamic features has been presented. The nonlinear dynamic features that represent the dimensional and waveform complexities of the signal being analyzed have been considered. The statistical analysis of the selected nonlinear dynamic features has been presented. The results show that the nonlinear dynamic features significantly discriminate the brain tumour group from the normal group.

摘要

使用脑电图 (EEG) 信号来测量混沌理论或俗称的非线性动力学特征,以作为几种病理状况和认知状态的指示物,这在医学领域非常流行。本文提出了使用非线性动力学特征分析正常受试者和脑肿瘤患者的头皮 EEG 信号。考虑了代表被分析信号的维度和波形复杂性的非线性动力学特征。还呈现了所选非线性动态特征的统计分析。结果表明,非线性动态特征可以显著区分脑肿瘤组和正常组。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验