INTELLIGENT FUZZY ADAPTIVE CONTROL STRATEGIES FOR ANESTHESIA

本研究将收集外科手术全身麻醉患者的血液动力学和生理数据，以及原始脑电图和听觉诱发反应。这些数据将被离线分析脑电图和血流动力学变化的相关性，这些变化将被临床解释为麻醉深度的变化。利用这些信息，将数字信号处理技术、自适应控制理论和模糊逻辑概念应用于麻醉智能模糊自适应控制策略。这些控制策略将通过其在保持患者安全的同时实现所需麻醉深度的能力来评估。将开发与血液动力学和生理/神经学指标偏离其安全和期望的临床值相关的二次成本函数，并用于确定麻醉对患者的损害/创伤。模糊代价函数将决定麻醉的估计深度与期望深度的偏差。这些成本函数将形成一个基础，用于比较实施控制策略的性能与主治麻醉师的性能。估计麻醉深度和期望麻醉深度之间的差异以及患者加权的生理/神经学趋势将用于计算推荐麻醉。估计麻醉深度和期望麻醉深度之间的差异以及患者加权的生理/神经学趋势将用于计算推荐的麻醉管理方案。麻醉剂量将被监测以确保安全，然后由主治麻醉师实施。本研究将招募30名男女均为ASA身体状态为II或I的成年患者，并计划在全身麻醉下进行腰椎间盘切除术和/或椎板切除术。将放置表面脑电图电极和用于听觉刺激的耳机，并连接ECG、血压、脉搏血氧仪和呼吸气体分析的标准监视器。将获得基线唤醒值。每位患者的麻醉诱导将由工作人员麻醉师决定。脑电图、诱发电位、心电图、脉搏率、血压和呼吸信息将通过高速实时计算机从手术室仪器中收集。具体目标和好处将是使用高速实时计算机减少工作负载。具体目标和益处将通过以下方式减少工作量：1)患者状态信息的智能和临床相关呈现；2)实时呈现/记录患者状态信息的简洁临床相关呈现；2)实时呈现/记录简洁的上下文敏感的患者/麻醉状态警报和趋势分析；3)将患者状态解释为对患者健康和麻醉管理的高级建议；4)IAM/MS对麻醉剂和患者气体的综合控制。此外，记录手术时间史和嵌入式推理可以形成计算机化麻醉师患者模拟器的基础。

This study will collect hemodynamic and physiological data in conjunction with raw EEG and Auditory Evoked Responses from patients undergoing general anesthesia for surgical procedures. This data will be analyzed off-line for correlation of EEG and hemodynamic changes that would be interpreted clinically as changes in anesthesia depth. Utilizing this information, digital signal processing techniques, adaptive control theory and fuzzy logic concepts will be applied to develop intelligent fuzzy adaptive control strategies for anesthesia. These control strategies will be evaluated by their ability to achieve the desired depth of anesthesia while maintaining patient safety. Quadratic cost functions related to the deviation of the hemodynamic and physiological/neurological indices from their safe and desired clinical values will be developed and used to determine anesthetic induced insult/trauma to the patient. Fuzzy cost functions will determine deviation of the estimated depth of anesthesia from the desired depth. These cost functions will form a basis for comparing the performance of the implemented control strategy to that of the attending anesthesiologist. The difference between the estimated and desired depth of anesthesia and the patients weighted Physiological/Neurological trends will be used to calculate the recommended anesthesia. The difference between the estimated and desired depth of anesthesia and the patients weighted Physiological/Neurological trends will be used to calculate the recommended anesthesia management scheme. Anesthetic doses will be monitored for safety and then implemented by the attending anesthesiologist. This study will enroll thirty adult patients of both sexes who are ASA physical status II or I and are scheduled for lumbar discectomy and/or laminectomy under general anesthesia. Surface EEC electrodes and ear phones for auditory stimulus will be placed and standard monitors of ECG, blood pressure, pulse oximetry and respiratory gas analysis will be connected. Baseline awake values will be obtained. Each patient's anesthetic induction will be conducted as determined by the staff anesthesiologist. The EEG, Evoked potentials, ECG, Pulse Rate, Blood Pressure, and the respiratory information will be collected from the OR instrumentation using a high-speed real-time computer. The specific aims and benefits will be reduced workload instrumentation using a high-speed real-time computer. The specific aims and benefits will be reduced workload through: 1) Intelligent and clinically relevant presentation of patient status information; 2) Real-time presentation/recording of succinct clinically relevant presentation of patient status information; 2) Real-time presentation/recording of succinct context sensitive patient/anesthetic status alarms and trend analysis: 3) interpretation of patient status into high-level recommendations on patient well-being and anesthetic management and 4) integrated control of anesthetic gents and a patient gases by the IAM/MS. Also, recorded surgical time histories and embedded reasoning could form the foundation of a computerized anesthesiologist patient simulator.