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    • 1. 发明授权
    • Real-time waveform analysis using artificial neural networks
    • 使用人工神经网络进行实时波形分析
    • US5598508A
    • 1997-01-28
    • US779219
    • 1991-10-18
    • Julian M. Goldman
    • Julian M. Goldman
    • G06F17/00G06F15/48G06F15/18
    • A61B5/0803A61B5/0836A61B5/7264A61B5/7267
    • A real-time waveform analysis system utilizes neural networks to perform various stages of the analysis. The signal containing the waveform is first stored in a buffer and the buffer contents transmitted to a first and second neural network which have been previously trained to recognize the start point and the end point of the waveform respectively. A third neural network receives the signal occurring between the start and end points and classifies that waveform as comprising either an incomplete waveform, a normal waveform or one of a variety of predetermined characteristic classifications. Ambiguities in the output of the third neural network are arbitrated by a fourth neural network which may be given additional information which serves to resolve these ambiguities. In accordance with the preferred embodiment, the present invention is applied to a system analyzing respiratory waveforms of a patient undergoing anesthesia and the classifications of the waveform correspond to normal or various categories of abnormal features functioning in the respiratory signal. The system performs the analysis rapidly enough to be used in realtime systems and can be operated with relatively low cost hardware and with minimal software development required.
    • 实时波形分析系统利用神经网络来执行分析的各个阶段。 包含波形的信号首先存储在缓冲器中,缓冲器内容被传送到先前已被训练以识别波形的起点和终点的第一和第二神经网络。 第三神经网络接收在起始点和终点之间发生的信号,并将该波形分类为包括不完整波形,正常波形或各种预定特征分类中的一种。 第三神经网络的输出中的模糊度由第四神经网络进行仲裁,第四神经网络可以被给予用于解决这些模糊性的附加信息。 根据优选实施例,本发明应用于分析经历麻醉的患者的呼吸波形的系统,并且波形的分类对应于在呼吸信号中起作用的正常或各种类型的异常特征。 系统执行足够快速的分析,以便在实时系统中使用,并且可以以相对低成本的硬件运行,并且需要最少的软件开发。
    • 5. 发明授权
    • System for diagnosing oxygenator failure
    • 诊断充氧器故障的系统
    • US5591399A
    • 1997-01-07
    • US483953
    • 1995-06-07
    • Julian M. GoldmanLyle Kirson
    • Julian M. GoldmanLyle Kirson
    • A61M1/16A61M1/14
    • A61M1/1698A61M2205/15A61M2205/702A61M2209/02Y10S128/03
    • A system which provides information necessary to diagnose a failure or malfunction of an oxygenator. The system provides information to differentiate oxygenator failure from other causes of hypoxemia (inadequate blood oxygen concentration). Such as malfunction of the ventilating circuit, or components of the ventilating circuit. This is accomplished by analyzing the oxygen concentration of the ventilating gas entering the oxygenator, the flow of the ventilating gas entering the oxygenator, and also the pressure in the ventilating gas circuit or the pressure of gas within the oxygenator. As a result the invention provides information to diagnose ventilating gas flow obstruction or a gas leak from an oxygenator housing.
    • 提供诊断氧合器故障或故障所必需的信息的系统。 该系统提供信息,以区分氧合器故障与其他原因的低氧血症(血氧浓度不足)。 如通风回路的故障或通风回路的部件。 这是通过分析进入氧合器的通风气体的氧浓度,进入氧合器的通气气体的流量,以及通气气体回路中的压力或氧合器内气体的压力来实现的。 因此,本发明提供了用于诊断通气气流阻塞或来自氧合器壳体的气体泄漏的信息。
    • 7. 发明授权
    • Real-time waveform analysis using artificial neural networks
    • 使用人工神经网络进行实时波形分析
    • US5751911A
    • 1998-05-12
    • US747460
    • 1996-11-12
    • Julian M. Goldman
    • Julian M. Goldman
    • G06F17/00G06F15/18
    • A61B5/0803A61B5/0836A61B5/7264A61B5/7267
    • A real-time waveform analysis system utilizes neural networks to perform various stages of the analysis. The signal containing the waveform is first stored in a buffer and the buffer contents transmitted to a first and second neural network which have been previously trained to recognize the start point and the end point of the waveform respectively. A third neural network receives the signal occurring between the start and end points and classifies that waveform as comprising either an incomplete waveform, a normal waveform or one of a variety of predetermined characteristic classifications. Ambiguities in the output of the third neural network are arbitrated by a fourth neural network which may be given additional information which serves to resolve these ambiguities. In accordance with the preferred embodiment, the present invention is applied to a system analyzing respiratory waveforms of a patient undergoing anesthesia and the classifications of the waveform correspond to normal or various categories of abnormal features functioning in the respiratory signal. The system performs the analysis rapidly enough to be used in real-time systems and can be operated with relatively low cost hardware and with minimal software development required.
    • 实时波形分析系统利用神经网络来执行分析的各个阶段。 包含波形的信号首先存储在缓冲器中,缓冲器内容被传送到先前已被训练以识别波形的起点和终点的第一和第二神经网络。 第三神经网络接收在起始点和终点之间发生的信号,并将该波形分类为包括不完整波形,正常波形或各种预定特征分类中的一种。 第三神经网络的输出中的模糊度由第四神经网络进行仲裁,第四神经网络可以被给予用于解决这些模糊性的附加信息。 根据优选实施例,本发明应用于分析经历麻醉的患者的呼吸波形的系统,并且波形的分类对应于在呼吸信号中起作用的正常或各种类型的异常特征。 该系统能够快速地进行分析,以便在实时系统中使用,并且可以以相对较低成本的硬件运行,并且需要最少的软件开发。