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    FILTER-BASED ARRHYTHMIA DETECTION
    1.
    发明申请
    FILTER-BASED ARRHYTHMIA DETECTION 审中-公开

    公开(公告)号：WO2023007281A1

    公开(公告)日：2023-02-02

    申请号：PCT/IB2022/056285

    申请日：2022-07-07

    申请人： MEDTRONIC, INC.

    发明人： CHENG, Ya_Jian ,  WARMAN, Eduardo N. ,  GILLBERG, Jeffrey M. ,  KADROLKAR, Abhijit ,  SARKAR, Shantanu ,  OUSDIGIAN, Kevin T.

    IPC分类号： A61B5/346 ,  G16H50/20 ,  A61B5/00

    摘要： This disclosure is directed to a medical system and technique for a filter-based approach to arrhythmia detection. In one example, the medical system comprises one or more sensors configured to sense physiological parameter(s); sensing circuitry configured to generate patient data based on the sensed physiological parameter(s), the patient data comprising signal data to represent cardiac activity of the patient; and processing circuitry configured to: detect a cardiac arrhythmia for the patient based on a classification of the signal data in accordance with a machine learning model, wherein the machine learning model comprises filter(s) for at least one portion of the signal data, wherein the at least one filter corresponds to a feature set that maps to the cardiac activity represented by the portion(s) of the signal data; and generate for display output data indicative of a positive detection of the cardiac arrhythmia.

    HVAD ADVERSE EVENT DETECTION FROM CARDIAC COMPASS DATA
    2.
    发明申请
    HVAD ADVERSE EVENT DETECTION FROM CARDIAC COMPASS DATA 审中-公开

    公开(公告)号：WO2023023545A2

    公开(公告)日：2023-02-23

    申请号：PCT/US2022/075063

    申请日：2022-08-17

    申请人： MEDTRONIC, INC.

    发明人： KADROLKAR, Abhijit ,  JACKSON, Troy E.

    IPC分类号： A61B5/00 ,  A61B5/024 ,  A61B5/361 ,  A61B5/363

    摘要： An example system includes an implantable medical device configured to obtain measurement values of one or more patient metrics; and processing circuitry configured to: determine a baseline value for each of the respective one or more patient metrics based on measurement values of the one or more patient metrics over a first period of time; determine a short-term value for each of the one or more patient metrics based on measurement values of the one or more patient metrics over a second period of time, determine a difference between each of the short-term values and the respective baseline value for each of the one or more patient metrics; determine that a risk of an adverse event occurring in the patient is high in response to the determined difference meeting a respective adverse event risk threshold; and generate for output an adverse event high risk alert.