测量麻醉深度的光容积图时频分析

Ahmad Al-Taan, W. Stork, S. Schumann, S. Wirth, Karla Hahn, J. Guttmann
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引用次数: 4

摘要

麻醉医师最重要的目标之一是确保手术期间患者的麻醉深度足够。适当的麻醉深度并不意味着病人睡得尽可能深,而是指在不让病人无意中过量服用麻醉药物的情况下,保持清醒的必要深度。已经有心脏病史或其他疾病的患者,在手术后恢复期,负荷过重可能导致死亡或并发症。因此,监测麻醉深度可以防止此类并发症的发生,并保证适当的用药剂量。脉搏血氧仪是手术室中已经使用的标准设备之一。光容积脉搏图(PPG)是脉搏血氧仪给出的信号,它携带着心肺系统的信息。在手术过程中,心脏和呼吸系统的节律都会发生变化。自主神经系统(ANS)在意识状态下控制心肺系统,但这种控制在无意识状态下的作用更大。我们研究手术期间光容积图的变化,以确定手术期间的麻醉水平。采用时频分析方法对系统进行辨识,得到了代表系统的数学模型。结果表明,标准方法(BIS指数)与本研究方法的相关性高达95.27%。结果取决于信号的处理部分和识别方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-frequency analysis of photoplethysmogram for measuring deepness of anesthesia
One of the most important objectives of anesthesiologists is to ensure an adequate depth of anesthesia for patients during surgeries. The adequate depth of anesthesia does not mean patient's sleeping as deep as possible but it means as deep as necessary to prevent awareness without unintentional overloading the patient with high doses of the anesthesia's drug. Overloading patients that already have history of cardiac illness or other diseases may cause death or complications during recovery stage after the surgery. Therefore monitoring depth of anesthesia will prevent such complications and ensure suitable dose of drugs. Pulse oximeter is one of the standard devices already used in the operation theater. Photoplethysmogram (PPG) is the signal given using pulse oximeter carries information about cardiopulmonary system. The rhythms of both the cardiac and respiratory systems are changed during surgeries. The Autonomic Nervous system (ANS) controls the cardiorespiratory systems during consciousness but this control will have more effects during unconsciousness. We studied the changes of the photoplethysmogram during surgeries to determine level of anesthesia during surgery. Time-Frequency method of analysis was used then system identification to get a mathematical model that represents our system. The results show high correlation up to (95.27%) between the standard methods (BIS Index) with the method developed in this study. The results depend on the processed part of the signal and on the identification methods.
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