Key result
Morphology-pair algorithm removes ECG baseline drift with less signal distortion than conventional methods.
Why the study?
Baseline drift noise in ECG signals impairs accurate waveform analysis and requires effective removal methods that do not distort the original signal.
Answers are grounded in this paper and cite their sources.
A novel morphology-pair and median value operation algorithm effectively removes baseline drift from ECG signals without distorting the original waveform.
본 논문에서는 심전도 파형에서 P, R, T-wave와 같은 local maxima 신호 영역과 Q, S-wave와 같은 local minima 신호영역을 제거하여 기저선 변동 잡음을 제거하기 위한 방법을 제시한다. 이를 위해 형태연산을 개선한 morphology-pair 연산을 심전도 파형에 적용하고, 그 결과 발생되는 돌출 파형을 제거하고자 중간 값 연산을 적용하였다. 제안한 알고리즘의 성능을 확인하기 위해 실제 심전도 임상 데이터인 MIT/BIH 데이터베이스를 이용하였으며, 실험 결과 원 신호를 왜곡 하지 않고, 기저선 변동 잡음을 효과적으로 제거함을 확인하였다. This paper proposed the method of removing baseline drift by eliminating local maxima such as P, R, T-wave signal region and local minima Q, S-wave signal region. We applied morphology-pair operations improved from morphology operation to the ECG signal. To eliminate overshoot in the result of morphology-pair operation, we apply median value operation to the result of morphology-pair operation. We use MIT/BIH database to estimate the proposed algorithm. Experiment result show that proposed algorithm removing baseline drift effectively without orignal ECG signal distortion.
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Park et al. (2014) studied ECG baseline drift. Morphology-pair operation with median value filter vs. Conventional morphology operation and morphology-pair operation alone was evaluated on Signal difference value (dB) after removing sine wave noise. The proposed algorithm using morphology-pair operation and median value effectively removed baseline drift noise from ECG signals with less signal distortion compared to conventional morphology operations.
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