利用高密度脑电和近红外光谱的全身麻醉大脑状态监测研究

Many surgical procedures would not be possible without the patient entering a state of general anesthesia. Inadequate GA may lead to intraoperative awareness with recall or to prolonged recovery and an increased risk of postoperative complications for the patient. Therefore, it is essential to monitor the depth of general anesthesia. In view of the inaccuracy of monitoring the depth of anesthesia, we will investigate the neural mechanisms of general anesthesia and further develop the reasonable methods of monitoring the brain status of anesthesia. Firstly, in sensor and source spaces, the neural mechanisms of general anesthesia were explored from the perspective of EEG microstate, functional connectivity and brain networks by using high-density EEG signals. Secondly, the weighted synchrosqueezing wavelet bispectral method was proposed to monitor the brain status of anesthesia by using EEG signals. The computer simulations and clinical experiments were employed to verify the improvement of accuracy of monitoring the brain status of anesthesia when using this proposed algorithm. Thirdly, linear and nonlinear approaches were used to develop the new methods of monitoring the brain status of anesthesia based on near-infrared spectroscopy. The clinical experiments were employed to prove the validity and reliability of new methods. It is expected that the research results of this project can provide new ideas and theoretical foundations for monitoring the depth of anesthesia. The principle investigator already had experiences about EEG and EMG signals processing and EEG source localization. Moreover, the PI has obtained some preliminary results about the computer simulations of new algorithm and the clinical investigations of monitoring the depth of anesthesia based on near-infrared spectroscopy.

麻醉是外科手术中必不可少的环节，临床中保障手术顺利进行的关键是判断并控制合适的麻醉深度，因此麻醉深度监测具有重要的临床实际意义。本项目拟针对麻醉深度监测不准确的问题，研究全身麻醉中更为深层次的脑神经机制，进而设计更合理的麻醉大脑状态监测方法。第一，在传感器空间和源空间上，利用高密度脑电从脑电微状态、功能连接和脑网络的角度去揭示全身麻醉的脑神经机制。第二，本项目提出了一种新的加权同步挤压小波双谱算法，并通过仿真研究和临床实验来验证该方法对脑电麻醉大脑状态监测准确性的提高。第三，本项目拟用线性和非线性方法来探索基于近红外光谱的麻醉大脑状态监测新方法，并依靠临床实验研究来证明其有效性及可靠性。预计该课题的研究成果能够为麻醉深度监测提供新的思路和理论基础。项目申请人已具有脑电和肌电信号处理及脑电源成像的研究经历，并已获得新算法的初步仿真研究结果和基于近红外光谱的麻醉大脑状态监测的初步临床研究结果。

麻醉是外科手术中必不可少的环节，临床中保障手术顺利进行的关键是判断并控制合适的麻醉深度，因此麻醉深度监测具有重要的临床实际意义。本项目针对麻醉深度监测不准确的问题，研究全身麻醉中更为深层次的脑神经机制，进而设计更合理的麻醉过程中大脑状态监测方法。研究获得以下成果：1）利用高密度脑电研究了由异丙酚引导的麻醉过程中脑电微状态和脑功能网络在不同麻醉阶段的时间演化过程，揭示了全身麻醉的脑神经机制，结果表明微状态F和C的基本参数，以及A、B、F 在delta、alpha、beta的功率会随麻醉镇静的程度加深而发生显著变化，并体现出个体与行为学指标的高度相关性；2）利用非线性分析方法开展了基于脑电信号的麻醉大脑状态监测研究，结果表明排序熵区分不同麻醉状态的能力最好，近似熵次之，复杂度最差；3）利用样本熵和相位幅值耦合方法开展了基于近红外光谱信号的麻醉大脑状态监测研究，通过分析研究表明，我们提出的脑血氧信号样本熵值和相位幅值耦合指数（MI）这两种新的麻醉深度监测指标具备对麻醉大脑状态进行监测的能力，并且通过ROC曲线分析验证了这种监测能力较强；4）开发了一套基于脑电和近红外光谱信号的麻醉深度监测软件，能通过串口获取脑电和近红外光谱信号，实时地以图像的方式呈现数据，并对获取的信号进行复杂度等算法的计算以获取麻醉深度指标，提供麻醉程度的参考值。这些研究成果能够为麻醉深度监测提供新的思路和理论基础。项目执行期间，在国内外重要学术期刊上和重要国际学术会议上发表论文11篇，其中：国外学术期刊论文7篇，国内核心学术期刊论文3篇，国际学术会议分组论文1篇，其中SCI检索7篇，EI检索1篇，北大中文核心期刊2篇。申请中国发明专利8项，已获批准授权2项，授权软件著作权4项。培养博士研究生1名，硕士研究生4名，其中3名硕士生已毕业。

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