JPWO2020161605A5 - - Google Patents

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JPWO2020161605A5
JPWO2020161605A5 JP2021544789A JP2021544789A JPWO2020161605A5 JP WO2020161605 A5 JPWO2020161605 A5 JP WO2020161605A5 JP 2021544789 A JP2021544789 A JP 2021544789A JP 2021544789 A JP2021544789 A JP 2021544789A JP WO2020161605 A5 JPWO2020161605 A5 JP WO2020161605A5
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pulse
pulses
data
computerized system
ecg
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  1. 患者の心電図(ECG)データを分析するためのコンピュータ化システムであって、前記ECGデータは、複数の時点を横断して1つ以上の電極によって発生され、複数の脈拍を含み、前記コンピュータ化システムは、
    描写アルゴリズムを使用して、前記ECGデータを分析し、前記複数の時点における少なくとも1つの波の存在の可能性に対応する波情報を発生させることと、
    少なくとも1つの波が存在し、複数の脈拍発現および脈拍消失を発生させることが判定される、前記複数の脈拍のうちの脈拍に関して、脈拍発現情報および脈拍消失情報を判定することと、
    前記複数の脈拍発現および脈拍消失に基づいて、ECGデータの複数の脈拍部分を抽出することであって、前記ECGデータの複数の脈拍部分のうちの各脈拍部分は、前記複数の脈拍のうちの脈拍に対応する、ことと、
    前記ECGデータの複数の脈拍部分に基づいて、前記複数の脈拍のうちの少なくとも2つの脈拍がともに群化されるべきであることを判定することであって、前記少なくとも2つの脈拍は、クラスタを形成する、ことと
    を行うように構成される、コンピュータ化システム。
  2. 前記コンピュータ化システムはさらに、
    埋め込みアルゴリズムを使用して、前記ECGデータの複数の部分を分析し、前記複数の脈拍を表す埋め込みデータを発生させることと、
    群化アルゴリズムを使用して、前記埋め込みデータを分析し、群データを発生させることと
    を行うように構成され、
    前記複数の脈拍のうちの前記少なくとも2つの脈拍は、前記群データに基づいて、ともに群化されることが判定される、請求項1に記載のコンピュータ化システム。
  3. 群データは、2つの脈拍の間の距離に対応する、請求項2に記載のコンピュータ化システム。
  4. 前記コンピュータ化システムはさらに、前記ECGデータに対応する不正確度に関して入力デバイスからユーザ入力データを受信するように構成される、請求項2に記載のコンピュータ化システム。
  5. 前記コンピュータ化システムはさらに、前記ユーザ入力データに基づいて、前記描写アルゴリズム、埋め込みアルゴリズム、または群化アルゴリズムのうちの1つ以上を調節するように構成される、請求項に記載のコンピュータ化システム。
  6. 前記コンピュータ化システムはさらに、前記ユーザ入力データに基づいて、表示されたデータを修正するように構成される、請求項に記載のコンピュータ化システム。
  7. 前記ユーザ入力データは、1つ以上のQRSクラスタ、PVCクラスタ、またはPACクラスタを追加、削除、または分割することに対応する、請求項6に記載のコンピュータ化システム。
  8. 前記埋め込みデータは、前記複数の脈拍のうちの脈拍毎にデータのベクトルを含む、請求項に記載のコンピュータ化システム。
  9. 前記複数の脈拍のうちの少なくとも2つの脈拍がともに群化されるべきであることを判定することはさらに、前記群データが閾値を満たすことを判定することを含む、請求項2に記載のコンピュータ化システム。
  10. 前記コンピュータ化システムはさらに、分類アルゴリズムを使用して、前記クラスタ内の前記脈拍を分析し、前記患者に関する心臓事象と関連付けられる、1つ以上の異常、条件、または記述子の存在の可能性を判定するように構成される、請求項1に記載のコンピュータ化システム。
  11. 前記コンピュータ化システムはさらに、分類アルゴリズムを使用して、前記描写アルゴリズムからの前記波情報を分析し、前記患者に関する心臓事象と関連付けられる、1つ以上の異常、条件、または記述子の存在の可能性を判定するように構成される、請求項1に記載のコンピュータ化システム。
  12. 前記波情報は、前記分類アルゴリズムに入力され、前記複数の脈拍のうちの少なくとも2つの脈拍がともに群化されるべきであることを判定するために別個に使用される、請求項11に記載のコンピュータ化システム。
  13. 前記コンピュータ化システムはさらに、前記描写アルゴリズムを使用して、前記ECGデータを分析することに先立って、前記ECGデータを前処理し、前記ECGデータから雑音を除去するように構成される、請求項1に記載のコンピュータ化システム。
  14. 患者の心電図(ECG)データを分析するための方法であって、前記ECGデータは、複数の時点を横断して1つ以上の電極によって発生され、複数の脈拍を含み、前記方法は、
    描写アルゴリズムを使用して、前記ECGデータを分析し、前記複数の時点における少なくとも1つの波の存在の可能性に対応する波情報を発生させることと、
    少なくとも1つの波が存在し、複数の脈拍発現および脈拍消失を発生させることが判定される、前記複数の脈拍のうちの脈拍に関して、脈拍発現情報および脈拍消失情報を判定することと、
    前記複数の脈拍発現および脈拍消失に基づいて、ECGデータの複数の脈拍部分を抽出することであって、前記ECGデータの複数の脈拍部分のうちの各脈拍部分は、前記複数の脈拍のうちの脈拍に対応する、ことと、
    前記ECGデータの複数の脈拍部分に基づいて、前記複数の脈拍のうちの少なくとも2つの脈拍がともに群化されるべきであることを判定することであって、前記少なくとも2つの脈拍は、クラスタを形成する、ことと
    を含む、方法。
  15. 埋め込みアルゴリズムを使用して、前記ECGデータの複数の部分を分析し、前記複数の脈拍を表す埋め込みデータを発生させることと、
    群化アルゴリズムを使用して、前記埋め込みデータを分析し、群データを発生させることと
    をさらに含み、
    前記複数の脈拍のうちの前記少なくとも2つの脈拍は、前記群データに基づいて、ともに群化されることが判定される、請求項14に記載の方法。
JP2021544789A 2015-10-27 2020-02-03 描写および分類のための心電図処理システム Pending JP2022523741A (ja)

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EP15191769 2015-10-27
US16/267,380 2019-02-04
US16/267,380 US10959660B2 (en) 2015-10-27 2019-02-04 Electrocardiogram processing system for delineation and classification
PCT/IB2020/050850 WO2020161605A1 (en) 2015-10-27 2020-02-03 Electrocardiogram processing system for delineation and classification

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