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    • 2. 发明申请
    • Systems and Method for Recording Clinical Manifestations of a Seizure
    • 记录癫痫发作临床表现的系统和方法
    • US20090171168A1
    • 2009-07-02
    • US12343376
    • 2008-12-23
    • Kent W. LeydeMichael Bland
    • Kent W. LeydeMichael Bland
    • A61B5/0476A61B5/024
    • A61B5/4094A61B5/0031A61B5/04012A61B5/0478A61B5/048A61B5/11A61B5/7221A61B5/7246A61B5/7275A61N1/36082
    • A method of comparing a patient's neurological data to data that is indicative of the patient's clinical manifestation of a seizure. In some embodiments, the method includes the steps of monitoring neurological data from a patient indicative of the patient's propensity for having a seizure; automatically recording clinical manifestation data from the patient that may be indicative of the occurrence of a clinical seizure; and analyzing the automatically recorded clinical manifestation data and the monitored neurological data to determine if one of the clinical manifestation data and the neurological data indicates the occurrence of a seizure while the other does not. Systems are described including a monitoring device having a communication assembly for receiving neurological data transmitted external to a patient from a transmitter implanted in a patient; a processor that processes the neurological data to estimate the patient's brain state; and an assembly for automatically recording clinical manifestation data in response to a brain state estimate by the processor.
    • 将患者的神经学数据与指示患者临床表现为癫痫发作的数据进行比较的方法。 在一些实施例中,该方法包括以下步骤:监测来自患者的指示患者癫痫发作倾向的神经学数据; 自动记录患者临床表现资料,可能表明临床发作的发生; 并分析自动记录的临床表现数据和所监测的神经学数据,以确定临床表现数据和神经学数据之一是否表明癫痫发作,而另一个不发生。 描述了系统,其包括具有通信组件的监视设备,该通信组件用于从植入患者体内的发射器接收从患者外部传输的神经学数据; 处理器,处理神经学数据以估计患者的大脑状态; 以及用于响应于处理器的脑状态估计自动记录临床表现数据的组件。
    • 7. 发明授权
    • Processing for multi-channel signals
    • 多通道信号处理
    • US08786624B2
    • 2014-07-22
    • US12792582
    • 2010-06-02
    • Javier Ramón EchauzDavid E. SnyderKent W. Leyde
    • Javier Ramón EchauzDavid E. SnyderKent W. Leyde
    • G06T11/20G09G5/02G06F19/00G06F17/18
    • A61B5/0476A61B5/076A61B5/4094A61B2560/0271G06K9/00536G06T11/206
    • Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.
    • 用于改善多通道信号处理的方法和装置。 在示例性实施例中,针对时间窗口上的多信道信号计算异常度量。 可以使用异常度量的大小来确定在时间窗口上的多通道信号中是否存在异常。 在示例性实施例中,异常度量可以是与时间窗口上的多信道信号的奇异值相关联的条件数,如通过产生数据条件数的信道数进一步调整的。 异常度量计算的应用包括擦除用于癫痫发作检测/预测/反预测算法训练的信号档案,用于实时监测生物系统的多通道信号的预处理,以及启动和/或 这种系统在正常运行期间的自适应自检。
    • 9. 发明申请
    • Patient Entry Recording in an Epilepsy Monitoring System
    • 癫痫监测系统中的患者进入记录
    • US20110172554A1
    • 2011-07-14
    • US13070357
    • 2011-03-23
    • Kent W. LeydeJohn F. Harris
    • Kent W. LeydeJohn F. Harris
    • A61B5/048
    • A61B5/0476A61B5/0006A61B5/0031A61B5/4094A61B2560/0271A61M5/14276A61N1/36082A61N1/37247A61N1/37258A61N1/37282G06F19/3418
    • Systems and methods for monitoring a patient are provided. The system includes: an implantable sensor adapted to collect neurological signals; an implantable assembly configured to sample the neurological signals collected by the sensor; and a rechargeable external assembly configured to wirelessly receive the sampled neurological signals from the implantable assembly, said external assembly being further configured to record a patient entry in response to receiving an input from the patient. The method includes: collecting neurological signals with a sensor implanted in the patient; sampling the neurological signals collected by the sensor with an implantable assembly implanted in the patient; and transmitting the sampled neurological signals from the implantable assembly to a rechargeable external assembly external to the patient; and recording a patient entry in response to receiving an input from the patient.
    • 提供了用于监测患者的系统和方法。 该系统包括:适于收集神经信号的可植入传感器; 植入式组件,被配置为对由所述传感器收集的神经信号进行采样; 以及可充电外部组件,其被配置为从所述可植入组件无线地接收所述取样的神经信号,所述外部组件还被配置为响应于接收到来自所述患者的输入而记录患者入口。 该方法包括:用植入患者的传感器收集神经信号; 用植入患者的可植入组件对由传感器收集的神经信号进行采样; 以及将所述取样的神经信号从所述可植入组件传输到患者外部的可再充电外部组件; 以及响应于从患者接收到输入而记录患者入口。
    • 10. 发明申请
    • Processing for Multi-Channel Signals
    • 多通道信号处理
    • US20100302270A1
    • 2010-12-02
    • US12792582
    • 2010-06-02
    • Javier Ramón EchauzDavid E. SnyderKent W. Leyde
    • Javier Ramón EchauzDavid E. SnyderKent W. Leyde
    • G06T11/20G09G5/02G06F19/00G06F17/18
    • A61B5/0476A61B5/076A61B5/4094A61B2560/0271G06K9/00536G06T11/206
    • Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.
    • 用于改善多通道信号处理的方法和装置。 在示例性实施例中,针对时间窗口上的多信道信号计算异常度量。 可以使用异常度量的大小来确定在时间窗口上的多通道信号中是否存在异常。 在示例性实施例中,异常度量可以是与时间窗口上的多信道信号的奇异值相关联的条件数,如通过产生数据条件数的信道数进一步调整的。 异常度量计算的应用包括擦除用于癫痫发作检测/预测/反预测算法训练的信号档案,用于实时监测生物系统的多通道信号的预处理,以及启动和/或 这种系统在正常运行期间的自适应自检。