Abstract
The suppression of baseline disturbance in electrocardiogram (ECG) is necessary to avoid distorting diagnostic features in the data. In order to remove baseline drift, digital filter specifications had been designing along with detrending fluctuation algorithms. However, all these methods require a high amount of off-line computation. To address this, we propose a new method to remove baseline drift in ECG signals with semi-real-time computation while compensating for the phase distortion from the frequencies in the passband of the infinite impulse response low-pass filter and estimating its sample delay for the filtered signal. Regarding evaluation of the proposed filter, we can find the fact that the signal-to-noise ratio increases by approximately 3 dB after applying the filter to the MIT-BIH stress data consisted of arrhythmias corrupted with the intentional baseline wander and the disturbances due to muscle interactions as well as electrode–skin impedance mismatch during the electrocardiogram recordings.
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