使用心电图衍生的呼吸来解释休息和呼吸调节期间的BOLD-fMRI波动
Inês Esteves1, Ana R Fouto2,3, Amparo Ruiz-Tagle2,4
1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal. ines.esteves@edu.ulisboa.pt.
Scientific reports
|November 11, 2025
概括
在fMRI期间从心电图 (ECG) 信号中提取呼吸数据是可以在没有额外的设备的情况下做到的. 这种来自心电图的呼吸 (EDR) 方法通过提供有价值的生理噪声校正,有利于同时进行EEG-fMRI研究.
科学领域:
- 神经成像是一种神经成像.
- 生理监测 生理监测
- 生物医学工程 生物医学工程
背景情况:
- 同时脑电图 (EEG) 和功能磁共振成像 (fMRI) 是神经科学研究的强大工具.
- 在fMRI过程中记录呼吸等生理信号至关重要,但使设置和参与者舒适性复杂化.
- 电心电图 (ECG) 经常被记录在EEG-fMRI研究中,为呼吸数据提供了一个潜在的来源.
研究的目的:
- 研究在fMRI环境中从心电图记录中提取呼吸信号的可行性.
- 评估不同的方法来提取ECG衍生的呼吸 (EDR) 信号.
- 评估EDR信号在EEG-fMRI中对生理噪声校正和脑血管反应率估计的有用性.
主要方法:
- 从15名健康受试者同时获得EEG,fMRI,ECG和呼吸数据.
- 应用多个算法从心电图数据中提取EDR信号.
- 将EDR信号与同时记录的呼吸数据进行比较.
- 评估EDR衍生的回归因子用于fMRI无效和脑血管反应率估计.
主要成果:
- 基于振幅的EDR方法显示,与呼吸的相关性较低,可能是由于MRI诱导的心电图扭曲.
- 一致性分析证实EDR信号保留了相关的光谱信息.
- 基于EDR的回归器与来自测量呼吸的回归器相当.
- 基于心率变化的EDR方法在噪声校正和反应率估计方面产生了最佳的整体性能.
结论:
- 可以从MRI环境中的心电图信号中提取有意义的呼吸信息.
- 在EEG-fMRI研究中,当直接记录具有挑战性时,EDR为呼吸监测提供了一个实用的替代方案.
- 这种方法可以在没有额外的硬件的情况下改善fMRI研究中的生理噪声校正和数据分析.
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