KR20230110374A - 살아있는 대상체의 심장 기능을 결정하기 위한 장치및 방법 - Google Patents
살아있는 대상체의 심장 기능을 결정하기 위한 장치및 방법 Download PDFInfo
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- KR20230110374A KR20230110374A KR1020237023073A KR20237023073A KR20230110374A KR 20230110374 A KR20230110374 A KR 20230110374A KR 1020237023073 A KR1020237023073 A KR 1020237023073A KR 20237023073 A KR20237023073 A KR 20237023073A KR 20230110374 A KR20230110374 A KR 20230110374A
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- living subject
- mathematical model
- cardiac output
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Abstract
Description
도 1은 본 발명에 따른 의료용 침습 장치의 한 실시예의 횡단면도;
도 2는 본 발명에 따른 의료용 침습 장치의 한 실시예의 측면도;
도 3은 일체형의 가요성 전자 보드 및 수용 코일 회로를 가진 시스의 한 실시예 및 본 발명에 따른 일체형 이미터 코일 회로를 가진 샤프트의 한 실시예의 도면;
도 4는 본 발명의 따라 동축 배열된 샤프트(내측 요소)의 한 세그먼트를 덮고 있는 시스(외측 요소)의 한 실시예의 도면.
Claims (23)
- 살아있는 대상체의 심박출량(CO)의 계산 방법에 있어서, 상기 방법은 입력 데이터 벡터와 목표 CO 값을 연결하는 수학적 모델이 구성되는 것을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 수학적 모델은 비선형인 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는 의료용 침습 장치에 의해 획득된 하나 이상의 센서 측정을 포함하고;
상기 의료용 침습 장치는 전자 회로 및 몸체 부분을 포함하고 - 상기 몸체 부분은 환자의 혈관, 환자의 체강, 및 환자의 신체 조직 중 하나에 삽입되도록 배치됨 -;
상기 몸체 부분에 센서 장치 및 디지털 데이터 전송 장치가 일체형으로 구성되는 것; 을 특징으로 하는 심박출량 계산 방법. - 제1항에 있어서, 입력 데이터 벡터는 살아있는 대상체로부터의 생리적 입력 공급원 데이터를 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는 반복되는 온도 측정 곡선 하의 면적을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는 유체 볼루스를 정액 순환에 주입한 후에 반복되는 온도 측정의 곡선 하의 면적을 포함하며, 상기 주입된 볼루스는 혈액 온도와 상이한 온도를 가지는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는 동맥 맥박 압력 분석으로부터 얻어진 숫자들을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는 동맥 맥박 압력 분석으로부터 얻어진 숫자들을 포함하고, 상기 숫자들은, 비트-비트 기간, 심박동수, 수축기 혈압, 확장기 혈압, 맥압, 시간 차이당 최고 수축기 혈압 차이, 맥박 곡선 하의 면적, 및 맥압파의 수축기 부분 하의 면적 중 하나인 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는, 살아있는 대상체의 수축기 혈압, 살아있는 대상체의 확장기 혈압, 및 살아있는 대상체의 맥압 중 하나 이상을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는, 살아있는 대상체의 나이, 살아있는 대상체의 성별, 살아있는 대상체의 키, 살아있는 대상체의 몸무게, 살아있는 대상체의 체온 중 하나 이상을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 입력 데이터 벡터는, 심장 펌프 타입, 심장 펌프 성능 설정, 심장 펌프 크기, 심장 펌프 혈류, 심장 펌프 회전 속도, 심장 펌프 소비 전력, 심장 펌프 소비 전류, 심장 펌프 압력 센서 판독 중 하나 이상을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 목표 CO 값은 다수의 시간 지점들에서 반복적으로 측정된 온도의 곡선 하의 면적을 결정하는 것을 포함하는 알고리즘에 의해 결정되는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 목표 CO 값은 의료용 침습 장치에 의해 측정된 생리적 신호들을 분석하여 결정되고;
상기 의료용 침습 장치는 전자 회로 및 몸체 부분을 포함하고 - 상기 몸체 부분은 환자의 혈관, 환자의 체강, 및 환자의 신체 조직 중 하나에 삽입되도록 배치됨 -;
상기 몸체 부분에 센서 장치 및 디지털 데이터 전송 장치가 일체형으로 구성되는 것을 특징으로 하는 심박출량 계산 방법. - 제1항에 있어서, 수학적 모델을 생성하는 것은 최소 자승 최적법으로 입력 데이터 벡터를 목표 CO 값에 맞추는 것을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 수학적 모델을 구성하는 것은 인공 신경망(ANN)의 훈련을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 수학적 모델은 심층 신경망(DNN)의 비지도 훈련을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 수학적 모델은 심층 신경망(DNN)의 지도 훈련을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 수학적 모델은 심층 믿음망(DBN)의 훈련을 포함하는 것을 특징으로 하는 심박출량 계산 방법.
- 제1항에 있어서, 상기 방법은:
입력 데이터 벡터를 얻는 단계;
적어도 수학적 모델을 이용하여 입력 데이터 벡터를 변환하는 단계; 및
변환 결과를 생리적 유닛들에서 CO 값으로 나타내는 단계;를 더 포함하는 것을 특징으로 하는 심박출량 계산 방법. - 제1항에 있어서, 상기 방법은:
복수의 목표 CO 값을 얻는 단계;
적어도 부분적으로 목표 CO 값들에 따라 수학적 모델을 생성하는 단계;
입력 데이터 벡터를 얻는 단계;
적어도 수학적 모델을 이용하여 입력 데이터 벡터를 변환하는 단계; 및
변환 결과를 생리적 유닛들에서 CO 값으로 나타내는 단계;를 더 포함하는 것을 특징으로 하는 심박출량 계산 방법. - 컴퓨터에서 실행될 때, 입력 데이터 벡터와 목표 CO 값을 연결하는 수학적 모델이 구성되는 것을 포함하는 살아있는 대상체의 심박출량(CO)의 계산 방법을 수행하도록 배열된 코드 구성을 포함하는 것을 특징으로 하는 컴퓨터 판독가능한 기록 매체.
- 제21항에 있어서, 컴퓨터 판독 매체에 저장된 것을 특징으로 하는 컴퓨터 판독가능한 기록 매체.
- 기계 판독 캐리어에 저장된 컴퓨터 판독가능한 기록 매체 제품에 있어서, 컴퓨터에서 실행될 때, 입력 데이터 벡터와 목표 CO 값을 연결하는 수학적 모델이 구성되는 것을 포함하는 살아있는 대상체의 심박출량(CO)의 계산 방법을 수행하기 위한 프로그램 코드 수단을 포함하는 것을 특징으로 하는 컴퓨터 판독가능한 기록 매체 제품.
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PCT/EP2018/051255 WO2018134330A2 (en) | 2017-01-19 | 2018-01-19 | Devices and methods for determining heart function of a living subject |
KR1020197024179A KR102555070B1 (ko) | 2017-01-19 | 2018-01-19 | 살아있는 대상체의 심장 기능을 결정하기 위한 장치 및 방법 |
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KR1020237023073A KR20230110374A (ko) | 2017-01-19 | 2018-01-19 | 살아있는 대상체의 심장 기능을 결정하기 위한 장치및 방법 |
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EP (1) | EP3570739A2 (ko) |
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KR (2) | KR102555070B1 (ko) |
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2018
- 2018-01-19 JP JP2019560468A patent/JP7113851B2/ja active Active
- 2018-01-19 CN CN202310823231.1A patent/CN116919343A/zh active Pending
- 2018-01-19 WO PCT/EP2018/051255 patent/WO2018134330A2/en unknown
- 2018-01-19 EP EP18701150.7A patent/EP3570739A2/en active Pending
- 2018-01-19 CN CN201880018884.XA patent/CN110545717B/zh active Active
- 2018-01-19 KR KR1020197024179A patent/KR102555070B1/ko active IP Right Grant
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- 2018-01-19 US US16/479,438 patent/US11389640B2/en active Active
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JP7113851B2 (ja) | 2022-08-05 |
CN110545717B (zh) | 2023-08-04 |
KR102555070B1 (ko) | 2023-07-12 |
CN116919343A (zh) | 2023-10-24 |
US20190381226A1 (en) | 2019-12-19 |
CN110545717A (zh) | 2019-12-06 |
JP2024153675A (ja) | 2024-10-29 |
JP2022169520A (ja) | 2022-11-09 |
US11389640B2 (en) | 2022-07-19 |
JP2020515361A (ja) | 2020-05-28 |
EP3570739A2 (en) | 2019-11-27 |
JP7520923B2 (ja) | 2024-07-23 |
WO2018134330A3 (en) | 2018-08-30 |
WO2018134330A2 (en) | 2018-07-26 |
US20220296875A1 (en) | 2022-09-22 |
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