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http://dx.doi.org/10.6109/jkiice.2010.14.9.2105

ECG Baseline Wandering Removing Algorithm using Slope analysis and Curve Point Detection  

Cho, Ik-Sung (부산대학교)
Kwon, Hyeog-Soong (부산대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.14, no.9, 2010 , pp. 2105-2112 More about this Journal
Abstract
The noise component of electrocardiogram is not distributed in a certain frequency band. It is expressed in various types of signals by rater's physical and environmental conditions. Particularly, since the baseline wander is occurred by the mixture of the original signal and 0 ~ 2 [Hz] range of the frequency components according to muscle constraction of part attaching to an electrode and respiration rythm, it makes the ECG signal analysis difficult. Several methods have been proposed to eliminate the wandering effectually. However, they have some problems. In some methods, the high processing time is required due to the computational complexity, while in other cases ECG signal morphology can be distorted. This paper suggests a simple and effective algorithm that eliminates baseline wander with low computational complexity and without distorting signal morphology. First, the algorithm detects and segments a baseline wandering interval using slope analysis and curve point detection, second, approximates the wandering in the interval as a sinusoid, and then subtracts the sinusoid from signal. Finally, ecg signals without baseline wander are obtained. In order to evaluate the performance of the algorithm, several ECG signals with baseline wandering in MIT/BIH ECG database 101, 111, 113, 234 record were chosen and applied to the algorithm. It is found that the algorithm removes baseline wanders effectively without significant morphological distortion.
Keywords
baseline wandering; slope analysis; curve point detection; processing time;
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