首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise
【24h】

Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise

机译:屏气锻炼期间脑电图和潮​​气中二氧化碳信号的相关分析

获取原文

摘要

The central mechanism of breathing control is not totally understood. Several studies evaluated the correlation between electroencephalographic (EEG) power spectra and respiratory signals by performing resting state tasks or adopting hypercapnic/hypoxic stimuli. The observation of brain activity during voluntary breath hold tasks, might be an useful approach to highlight the areas involved in mechanism of breath regulation. Nevertheless, studies of brain activity with EEG could present some limitations due to presence of severe artifacts. When artifact rejection methods, as independent component analysis, cannot reliably clean EEG data, it is necessary to exclude noisy segments. In this study, global field power in the delta band and end-tidal CO2 were derived from EEG and CO2 signals respectively in 4 healthy subjects during a breath-hold task. The cross correlation function between the two signals was estimated taking into account the presence of missing samples. The statistical significance of the correlation coefficients at different time lags was assessed using surrogate data. Some simulations are introduced to evaluate the effect of missing data on the correlational analysis and their results are discussed. Results obtained on subjects show a significant correlation between changes in EEG power in the delta band and end-tidal CO2. Moreover, the changes in end-tidal CO2 were found to precede those of global field power. These results might help to better understand the cortical mechanisms involved in the control of breathing.
机译:呼吸控制的中心机制并不完全理解。几项研究通过进行静止状态任务或采用过脂碱/缺氧刺激来评估脑电图(EEG)功率谱和呼吸信号之间的相关性。在自愿呼吸持有任务期间观察大脑活动,可能是强调呼吸调节机制所涉及的地区的有用方法。然而,由于存在严重伪影,脑电图的脑活动的研究可能会产生一些局限性。当作为独立分量分析的工件拒绝方法不能可靠地清洁EEG数据时,有必要排除嘈杂的段。在该研究中,在呼吸保持任务期间,在4个健康受试者中,达到频带和终端二氧化碳中的全局场功率分别来自EEG和CO2信号。考虑到缺失样本的存在,估计两个信号之间的交叉相关函数。使用替代数据评估不同时间滞后的相关系数的统计学意义。引入了一些模拟以评估缺失数据对相关分析的影响及其结果。对受试者获得的结果显示了ΔBas带和末端CO2中的EEG功率变化之间的显着相关性。此外,发现终端二氧化碳的变化在全球场动力之前。这些结果可能有助于更好地了解呼吸控制中涉及的皮质机制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号