독립요소분석을 이용한 태아심전도 추출을 위한 시변 칼만 평활기의 개발-예비연구

Abstract

Fetal heart rate monitoring is important information to assess fetal well-being. Non-invasive fetal ECG (electrocardiography) can be derived from maternal abdominal signal. And various promising signal processing methods have been introduced to extract fetal ECG from mother’s composite abdominal signal. However, non-invasive fetal ECG monitoring still has not been widely used in clinical practice due to insufficient reliable measurement and difficulty of signal processing. In application of signal processing method to extract fetal ECG, it might be lower signal to noise ratio due to time varying white Gaussian noise. In this paper, time varying Kalman smoother is proposed to remove white noise in fetal ECG and its feasibility is confirmed. Wiener process was set as Kalman system model and covariance matrix was modified according to white Gaussian noise level. Modified error covariance matrix changed Kalman gain and degree of smoothness. Optimal covariance matrix according to various amplitude in Gaussian white noise was extracted by 5 channel fetal ECG model, and feasibility of proposed method could be confirmed.