Li Tianning, Wen Peng
Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, QLD, 4350, Australia.
Australas Phys Eng Sci Med. 2016 Sep;39(3):773-81. doi: 10.1007/s13246-016-0459-5. Epub 2016 Jun 21.
This paper presents a new method to apply timing characteristics of electroencephalograph (EEG) beta frequency bands to assess the depth of anaesthesia (DoA). Firstly, the measured EEG signals are denoised and decomposed into 20 different frequency bands. The Mobility (M), permutation entropy (PE) and Lempel-Ziv complexity (LCZ) of each frequency band are calculated. The M, PE and LCZ values of beta frequency bands (21.5-30 Hz) are selected to derive a new index. The new index is evaluated and compared with measured bispectral (BIS). The results show that there is a very close correlation between the proposed index and the BIS during different anaesthetic states. The new index also shows a 25-264 s earlier time response than BIS during the transient period of anaesthetic states. In addition, the proposed index is able to continuously assess the DoA when the quality of signal is poor and the BIS does not have any valid outputs.
本文提出了一种应用脑电图（EEG）β频段的时间特征来评估麻醉深度（DoA）的新方法。首先，对测量的EEG信号进行去噪，并分解为20个不同的频段。计算每个频段的迁移率（M）、排列熵（PE）和莱姆尔-齐夫复杂度（LCZ）。选择β频段（21.5 - 30Hz）的M、PE和LCZ值来推导一个新指标。对该新指标进行评估，并与测量的脑电双频指数（BIS）进行比较。结果表明，在不同麻醉状态下，所提出的指标与BIS之间存在非常密切的相关性。在麻醉状态的过渡期间，新指标还显示出比BIS早25 - 264秒的时间响应。此外，当信号质量较差且BIS没有任何有效输出时，所提出的指标能够持续评估麻醉深度。
