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    • 2. 发明授权
    • Neural network based learning engine to adapt therapies
    • 基于神经网络的学习引擎适应治疗
    • US07983744B2
    • 2011-07-19
    • US11686757
    • 2007-03-15
    • Carlos RicciSurekha Palreddy
    • Carlos RicciSurekha Palreddy
    • A61B5/0402
    • A61N1/37252Y10S128/924
    • A system for implementing a cardiac device having adaptive treatment therapies utilizing a neural network based learning engine is disclosed. The system includes an implantable cardiac device module and an external data processing system for specifying the operating characteristics of the cardiac device module. Both the cardiac device module and the external processing system possess an artificial neural network to specify the operation of the cardiac device module as it provides adaptive treatment therapies. The external data processing system includes a complete neural network module that trains and validates the operation of the neural network to match the optimal treatment options with a received set of collected patient data. A runtime neural network module that provides real time operation of the neural network using collected patient data is located within the cardiac device module. The cardiac device module and the external processing module are connected via a communication link.
    • 公开了一种使用基于神经网络的学习引擎实现具有适应性治疗疗法的心脏装置的系统。 该系统包括可植入心脏装置模块和用于指定心脏装置模块的操作特性的外部数据处理系统。 心脏装置模块和外部处理系统均具有人造神经网络,用于指定心脏装置模块的操作,因为它提供适应性治疗疗法。 外部数据处理系统包括完整的神经网络模块,其训练和验证神经网络的操作以将最佳治疗选项与收到的一组收集的患者数据进行匹配。 使用收集的患者数据提供神经网络的实时操作的运行时神经网络模块位于心脏装置模块内。 心脏装置模块和外部处理模块经由通信链路连接。
    • 3. 发明授权
    • Delay to therapy following controlled atrial shock therapy request
    • 患者受控心房休克治疗后延迟治疗
    • US07761152B2
    • 2010-07-20
    • US11273980
    • 2005-11-15
    • Victor T. ChenGary T. SeimCarlos RicciMichael L. FavetHal Propp
    • Victor T. ChenGary T. SeimCarlos RicciMichael L. FavetHal Propp
    • A61N1/39
    • A61N1/3956
    • An implantable cardiac device detects a patient therapy request originating from external to the implantable device. A shock therapy delay period is timed in response to the detection of the patient therapy request. Atrial shock therapy is provided to the patient after expiration of the shock therapy delay period (if the presence of an ongoing atrial arrhythmia is detected). The patient therapy request may be provided by a patient activator including a magnet for operating a reed switch in the implanted device to provide the request. A patient activator including an input and receiver/transmitter circuitry may be employed to request the immediate providing of atrial shock therapy, and/or to set the duration the shock therapy delay period. By allowing specific delays to therapy after a therapy request, a patient can prepare for the requested therapy and thereby mitigate therapy discomfort.
    • 可植入心脏装置检测源自可植入装置外部的患者治疗请求。 响应于患者治疗请求的检测,休克治疗延迟期是定时的。 在休克治疗延迟期结束后(如果检测到正在进行的心律失常的存在),向患者提供心房休克疗法。 患者治疗请求可以由患者激活器提供,包括用于在植入装置中操作舌簧开关的磁体以提供请求。 可以使用包括输入和接收器/发射器电路的患者激活器来请求立即提供心房休克疗法和/或设置休克治疗延迟时期的持续时间。 通过在治疗请求后允许特定的延迟治疗,患者可以准备所要求的治疗,从而减轻治疗不适。
    • 6. 发明申请
    • Tachyarrhythmia detection and discrimination based on curvature parameters
    • 基于曲率参数的快速性心律失常检测和鉴别
    • US20070203419A1
    • 2007-08-30
    • US10607818
    • 2003-06-27
    • Robert SweeneyCarlos Ricci
    • Robert SweeneyCarlos Ricci
    • A61B5/04
    • G06K9/00523A61B5/0245A61B5/0452A61B5/046A61B5/0464A61B5/7239A61B5/7264A61N1/362A61N1/3962
    • Estimating a frequency of a sampled cardiac rhythm signal and classifying the rhythm. The received signal is sampled and transformed into a curvature series. A lobe in the curvature series corresponds to a characteristic point in the sampled series. Characteristic points are selected based on a time of a lobe in the curvature series and, in one embodiment, an amplitude of the signal at the time of the lobe. A frequency of the sampled series is estimated by autocorrelating a function of the series of the characteristic points. In one embodiment, the function is a time difference function. The rhythm is classified by plotting the timewise proximity of characteristic points derived from an atrial signal with characteristic points derived from a ventricular signal. Regions of the plot are associated with a particular rhythm and the grouping of the data corresponds to the classification.
    • 估计采样心律信号的频率并对节律进行分类。 接收到的信号被采样并转换成曲率系列。 曲率系列中的凸角对应于采样系列中的特征点。 基于曲率序列中的波瓣的时间选择特征点,并且在一个实施例中,选择在波瓣时的信号的幅度。 通过自相关一系列特征点的函数来估计采样序列的频率。 在一个实施例中,该功能是时差功能。 通过绘制从心房信号得到的特征点与从心室信号得到的特征点的时间接近,分类节律。 地块的区域与特定节奏相关联,数据分组对应于分类。
    • 7. 发明申请
    • Arrhythmia discrimination based on determination of rate dependency
    • 基于速率依赖性确定的心律失常辨别
    • US20070142737A1
    • 2007-06-21
    • US11312280
    • 2005-12-20
    • Shelley CazaresJaeho KimYayun LinCarlos Ricci
    • Shelley CazaresJaeho KimYayun LinCarlos Ricci
    • A61B5/04
    • A61B5/0464A61B5/04525A61B5/7264
    • Cardiac systems and methods provide for discriminating between supraventricular tachyarrhythmia and ventricular tachyarrhythmia based on a determination that the patient's supraventricular rhythm exhibits rate dependency. One approach involves determining if a patient's supraventricular rhythm exhibits rate dependent morphology. If the patient's supraventricular rhythm is determined to exhibit rate dependent morphology, an implantable device classifies a detected tachyarrhythmia episode based on one or more templates selected from a plurality of rate-indexed templates stored in the device. Determining if the supraventricular rhythm exhibits rate dependent morphology may also include determining one or more rates at which the rate dependent morphology occurs.
    • 心脏系统和方法基于确定患者的室上节律表现出速率依赖性,确定了室上性快速性心律失常与室性快速性心律失常之间的区别。 一种方法涉及确定患者的室上节律是否表现出速率依赖性形态。 如果确定患者的室上节律表现出与速率相关的形态,则可植入装置基于从存储在装置中的多个速率索引模板中选择的一个或多个模板来分类检测到的快速性心律失常发作。 确定室性心律显示出速率依赖性形态还可以包括确定发生速率依赖形态的一个或多个速率。
    • 8. 发明授权
    • Neural network based learning engine to adapt therapies
    • 基于神经网络的学习引擎适应治疗
    • US07200435B2
    • 2007-04-03
    • US10668428
    • 2003-09-23
    • Carlos RicciSurekha Palreddy
    • Carlos RicciSurekha Palreddy
    • A61N1/362
    • A61N1/37252Y10S128/924
    • A cardiac device system for implementing a cardiac device having adaptive treatment therapies utilizing a neural network based learning engine includes an implantable cardiac device module and an external data processing system for specifying the operating characteristics of the cardiac device module. Both the cardiac device module and the external processing system possess an artificial neural network to specify the operation of the cardiac device module as it provides adaptive treatment therapies. The external data processing system includes a complete neural network module that trains and validates the operation of the neural network to match the optimal treatment options with a received set of collected patient data. In contrast, a runtime neural network module that only provides real time operation of the neural network using collected patient data is located within the cardiac device module. The cardiac device module and the external processing module communicate with each other to pass collected patient data from the cardiac device module to the external processing system when the operation of the neural network is to be updated. The cardiac device module and the external processing module also communicate with each other to pass operating coefficients for the neural network back from the external processing system to the cardiac device module once these coefficients are updated.
    • 用于实现具有使用基于神经网络的学习引擎的自适应治疗疗法的心脏装置的心脏装置系统包括可植入心脏装置模块和用于指定心脏装置模块的操作特性的外部数据处理系统。 心脏装置模块和外部处理系统均具有人造神经网络,用于指定心脏装置模块的操作,因为它提供适应性治疗疗法。 外部数据处理系统包括完整的神经网络模块,其训练和验证神经网络的操作以将最佳治疗选项与收到的一组收集的患者数据进行匹配。 相比之下,仅使用收集的患者数据提供神经网络的实时操作的运行时神经网络模块位于心脏装置模块内。 当要更新神经网络的操作时,心脏装置模块和外部处理模块相互通信以将收集的患者数据从心脏装置模块传送到外部处理系统。 一旦这些系数被更新,心脏装置模块和外部处理模块也相互通信,以将神经网络的操作系数从外部处理系统传回心脏装置模块。