Suppr超能文献

睡眠脑电图瞬变的显式参数化

Explicit parameterization of sleep EEG transients.

作者信息

Malinowska Urszula, Durka Piotr J, Zygierewicz Jarosław, Szelenberger Waldemar, Wakarow Andrzej

机构信息

Department of Biomedical Physics, Institute of Experimental Physics, Warsaw University, ul. Hoza 69, 00-681 Warszawa, Poland.

出版信息

Comput Biol Med. 2007 Apr;37(4):534-41. doi: 10.1016/j.compbiomed.2006.08.005. Epub 2006 Sep 22.

Abstract

Adaptive time-frequency approximations, implemented via the matching pursuit algorithm, offer description of local signals structures in terms of their time occurrence and width, frequency and amplitude. This allows to construct explicit filters for finding EEG waveforms, known from the visual analysis, in the matching pursuit decomposition of signals. In such a way detectors of relevant structures of both transient and oscillatory nature can be constructed in the space of physically meaningful parameters. This study presents evaluation of changes of power and frequency of sleep spindles and delta waves, related to the depth of the sleep, which were previously assessed in a qualitative way. We confirm quantitatively the decrease of frequencies of sleep spindles and delta waves with the depth of the sleep.

摘要

通过匹配追踪算法实现的自适应时频近似,能够根据局部信号的时间出现、宽度、频率和幅度来描述其结构。这使得在信号的匹配追踪分解中,可以构建明确的滤波器来寻找视觉分析中已知的脑电图波形。通过这种方式,可以在具有物理意义的参数空间中构建瞬态和振荡性质的相关结构检测器。本研究对与睡眠深度相关的睡眠纺锤波和δ波的功率和频率变化进行了评估,这些变化此前已通过定性方式进行了评估。我们定量地证实了睡眠纺锤波和δ波的频率随睡眠深度而降低。

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