• Title/Summary/Keyword: 비가압식 혈압 추정방법

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Cuffless Blood Pressure Estimation Based on a Convolutional Neural Network using PPG and ECG Signals for Portable or Wearable Blood Pressure Devices (휴대용 및 웨어러블 측정기를 위한 ECG와 PPG 신호를 활용한 합성곱 신경망 알고리즘 기반의 비가압식 혈압 추정 방법)

  • Cho, Jinwoo;Choi, Ahyoung
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.3
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    • pp.1-10
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    • 2020

  • In this paper, we propose an algorithm for estimating blood pressure using ECG (Electrocardiogram) and PPG (Photoplethysmography) signals. To estimate the BP (Blood pressure), we generate a periodic input signal, remove the noise according to the differential and threshold methods, and then estimate the systolic and diastolic blood pressures based on the convolutional neural network. We used 49 patient data of 3.1GB in the MIMIC database. As a result, it was found that the prediction error (RMSE) of systolic BP was 5.80mmHg, and the prediction error of diastolic BP was 2.78mmHg. This result confirms that the performance of class A is satisfied with the existing BP monitor evaluation method proposed by the British High Blood Pressure Association.

  • https://doi.org/10.9723/jksiis.2020.25.3.001 인용 PDF KSCI