Key result
PC-based PPG system designed to predict early cardiovascular disease by analyzing heart rate variability.
Describes the technical design of a PC-based system for early prediction of cardiovascular disease using PPG signals.
Requires prospective validation before clinical use; leaves open whether PPG-based autonomic and vascular analysis improves cardiovascular outcomes.
광용적맥파(photoplethysmogram, PPG)는 심장의 수축과 이완으로 변화하는 혈액용적(blood volume)과 혈액내의 헤모글로빈에 흡수되는 빛의 양의 선형적 관계를 이용하여 신호를 획득하는 방법이다. 본 논문에서는 PPG 센서를 이용하여 질환 예측을 할 수 있는 시스템을 제안하였다. 본 시스템은 PPG 센서를 이용하여 심박수의 변이를 살펴볼 수 있는 심박수 변이 분석과 이전 심박수와 이후 심박수를 구분지어 그래프로 표현하는 심박수 분포를 보여준다. 또한 심박수를 스펙트럼 분석하여 자율신경계 균형도, 가속도 맥파로부터 혈관 상태를 분석하여 심혈관 질환을 조기 예측하는 개인용 컴퓨터 기반의 시스템을 설계하고 구현하였다. Photoplethysmogram(PPG) is the method to obtain the biomedical signal using the linear relationships between the blood volume for changing the cardiac contraction and relaxation and the amount of light for absorbing the hemoglobin in the blood. In this paper, we proposed the analyzed results which show the heart rate variability and the distribution of heart rate for before and after using PPG. Moreover, this paper designed and implemented the system based on personal computer to predict cardiovascular disease in advance using the analyzed results for the autonomic balance from taking the spectral analysis of heart rate and the state of the blood vessel for analyzing APG(acceleration plethysmogram).
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Song et al. (2011) studied Cardiovascular disease. PPG-based cardiovascular disease prediction system was evaluated. A personal computer-based system was designed and implemented to predict cardiovascular disease early by analyzing heart rate variability, autonomic balance, and blood vessel state using a PPG sensor.
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