基于样本熵与决策树的麻醉意识深度评价指数的研究

发布时间：2018-01-19 22:25

本文关键词： 麻醉监护脑电参数决策树麻醉深度指数 BIS指数　出处：《生物医学工程学杂志》2015年02期 　论文类型：期刊论文

【摘要】：麻醉意识深度监测是临床中保证全身麻醉(全麻)手术顺利进行的关键手段之一,脑电图(EEG)作为检测大脑皮层活动的主要信号,是评价麻醉意识深度的重要工具。本文根据脑电信号随麻醉意识深度变化的趋势,提出结合脑电分析中的时域、频域及复杂度方法,采用决策树分类器与最小二乘拟合法计算麻醉深度指数(DOAI)。利用临床采集的40例丙泊酚全麻手术患者的脑电信号和麻醉专家对信号的分类、评分对此方案进行验证,实验结果与目前临床上广泛使用的BIS指数进行对比,结果显示DOAI与BIS指数的Pearson相关性可达0.89,从而证实此方案的可行性与准确性,为麻醉监护工作者提供了一种思路。
[Abstract]:The depth monitoring of anesthesia consciousness is one of the key means to ensure the smooth operation of general anesthesia (general anesthesia) in clinic. EEG (EEGG) is the main signal to detect cerebral cortex activity. It is an important tool to evaluate the depth of anesthesia consciousness. According to the trend of EEG changes with the depth of anesthetic consciousness, this paper puts forward the method of time domain, frequency domain and complexity in combining EEG analysis. The anaesthesia depth index (DOAI) was calculated by using the decision tree classifier and the least square fitting method. The EEG signals of 40 patients undergoing general anesthesia with propofol and the classification of the signals by anesthesiologists were used. The experimental results were compared with the BIS index which is widely used in clinical practice. The results showed that the Pearson correlation between DOAI and BIS index could reach 0.89. Thus, the feasibility and accuracy of the scheme are verified, and a train of thought is provided for the anesthesiologist.
【作者单位】：浙江大学生物医学工程与仪器科学学院生物医学工程教育部重点实验室;浙江普可医疗科技有限公司;
【基金】：浙江省自然科学基金资助项目(LY13H180004) 中央高校基本科研业务费专项资金资助项目
【分类号】：R614
【正文快照】： 2(浙江普可医疗科技有限公司,杭州310007)引言全麻手术中,为使手术顺利进行,会使用麻醉药物使患者呈现意识消失、全身痛觉丧失等状态,准确监测患者麻醉过程中意识变化情况可保证患者不会发生术中知晓,同时减少麻醉药物的使用量[1]。麻醉过程中,麻醉药物会对大脑神经元突触间神

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