Faculty of Engineering and Surveying, Centre for Systems Biology, University of Southern Queensland, Toowoomba, Qld 4350, Australia.
IEEE Trans Biomed Eng. 2013 Jun;60(6):1488-98. doi: 10.1109/TBME.2012.2236649. Epub 2013 Jan 9.
This study applies Bayesian techniques to analyze EEG signals for the assessment of the consciousness and depth of anesthesia (DoA). This method takes the limiting large-sample normal distribution as posterior inferences to implement the Bayesian paradigm. The maximum a posterior (MAP) is applied to denoise the wavelet coefficients based on a shrinkage function. When the anesthesia states change from awake to light, moderate, and deep anesthesia, the MAP values increase gradually. Based on these changes, a new function B(DoA) is designed to assess the DoA. The new proposed method is evaluated using anesthetized EEG recordings and BIS data from 25 patients. The Bland-Alman plot is used to verify the agreement of B(DoA) and the popular BIS index. A correlation between B(DoA) and BIS was measured using prediction probability P(K). In order to estimate the accuracy of DoA, the effect of sample n and variance τ on the maximum posterior probability is studied. The results show that the new index accurately estimates the patient's hypnotic states. Compared with the BIS index in some cases, the B(DoA) index can estimate the patient's hypnotic state in the case of poor signal quality.
本研究应用贝叶斯技术分析脑电图信号，以评估意识和麻醉深度（DoA）。该方法将限制的大样本正态分布作为后验推断来实现贝叶斯范式。最大后验（MAP）应用于基于收缩函数的去噪小波系数。当麻醉状态从清醒变为轻度、中度和深度麻醉时，MAP 值逐渐增加。基于这些变化，设计了一个新的函数 B（DoA）来评估 DoA。该新提出的方法使用来自 25 名患者的麻醉 EEG 记录和 BIS 数据进行评估。使用 Bland-Alman 图验证 B（DoA）和流行的 BIS 指数之间的一致性。使用预测概率 P（K）测量 B（DoA）和 BIS 之间的相关性。为了估计 DoA 的准确性，研究了样本 n 和方差 τ 对后验概率最大值的影响。结果表明，新指标能准确估计患者的催眠状态。与某些情况下的 BIS 指数相比，B（DoA）指数可以在信号质量较差的情况下估计患者的催眠状态。
