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    • 35. 发明申请
    • HEART FAILURE EVENT DETECTION USING MULTI-LEVEL CATEGORICAL FUSION
    • 使用多级分类融合的故障事件检测
    • US20150250428A1
    • 2015-09-10
    • US14637447
    • 2015-03-04
    • Cardiac Pacemakers, Inc.
    • Yi ZhangPramodsingh Hirasingh ThakurQi AnJulie A. ThompsonRamesh WariarRobert J. Sweeney
    • A61B5/00A61B5/0205
    • A61B5/7275A61B5/0205A61B5/4842A61B5/686A61B7/00G06F19/00G16H50/20G16H50/30
    • Systems and methods for detecting a present, or predicting a future, target physiologic event such as worsening heart failure (HF) are described. A system can comprise a patient information receiver circuit, at least two categorical risk analyzer circuits, and a categorical fusion circuit. The patient information receiver circuit receives physiologic signals and generates signal trends. The categorical risk analyzer circuit receives a category-specific input selected from the signal trends according to an associative physiologic condition indicative or correlative of the target event. The categorical risk analyzer circuit produces a signal trend metric indicating relative change in signal strength over time. The categorical risk analyzer circuit calculates a categorical risk index that indicates likelihood of the patient developing or presenting the associative physiologic condition. The categorical fusion circuit uses the categorical risk indices to generate a composite risk indicator indicating likelihood of the patient developing the target physiologic event.
    • 描述了用于检测目前或预测未来的目标生理事件(例如恶化的心力衰竭(HF))的系统和方法。 系统可以包括患者信息接收器电路,至少两个分类风险分析器电路和分类融合电路。 患者信息接收电路接收生理信号并产生信号趋势。 分类风险分析器电路根据指示或相关于目标事件的关联生理条件接收从信号趋势中选择的类别特定输入。 分类风险分析仪电路产生信号趋势指标,指示信号强度随时间的相对变化。 分类风险分析器电路计算出指示患者发展或呈现关联生理状况的可能性的分类风险指数。 分类融合电路使用分类风险指数来产生指示患者发展目标生理事件的可能性的综合风险指标。
    • 37. 发明申请
    • METHODS AND APPARATUS FOR STRATIFYING RISK OF HEART FAILURE DECOMPENSATION
    • 分解心脏衰竭风险的方法和装置
    • US20140343439A1
    • 2014-11-20
    • US14282353
    • 2014-05-20
    • Cardiac Pacemakers, Inc.
    • Robert J. SweeneyYi ZhangQi AnPramodsingh Hirasingh Thakur
    • A61B5/0205A61B5/20A61B5/00A61B5/02A61B5/08A61B5/145
    • A61B5/0205A61B5/0031A61B5/02028A61B5/024A61B5/0245A61B5/08A61B5/0826A61B5/14532A61B5/201A61B5/4818A61B5/7275A61B5/7282G06F19/00
    • Devices and methods for identifying patient at elevated risk of developing future heart failure (HF) events, such as events indicative of HF decompensation status, are described. The devices and methods can stratify the risk using sensor signals or signal metrics selected in accordance with patient chronic conditions. A medical device can receive a patient status input including at least a first and a second chronic condition indicators, sense one or more physiologic signals from the patient, and generate a plurality of signal metrics from the physiologic signals when the first chronic condition indicator and the second chronic condition indicator meets respective criterion. One or more patient-specific signal metrics can be selected from a group including the signal metrics selected for both the first and the second chronic conditions. A risk stratification algorithm can use the selected one or more patient-specific signal metrics to compute a composite risk index indicative of the probability of the patient later developing an event indicative of worsening of HF.
    • 描述了用于识别患有发展未来心力衰竭(HF)事件的高风险的患者的装置和方法,例如指示HF失代偿状态的事件。 设备和方法可以使用根据患者慢性病选择的传感器信号或信号度量来分级风险。 医疗设备可以接收包括至少第一和第二慢性病症指示符的患者状态输入,感测来自患者的一个或多个生理信号,并且当第一慢性病症指示符和 第二项慢性病指标符合相应标准。 可以从包括为第一和第二慢性疾病两者选择的信号度量的组中选择一个或多个患者特异性信号度量。 风险分层算法可以使用所选择的一个或多个患者特异性信号度量来计算指示患者随后发展指示HF恶化的事件的概率的复合风险指数。