Key result
Heart-rate-controlled time-varying high-pass filters suppress ECG baseline drift with minimal signal error.
Why the study?
Baseline drift in ECG signals requires suppression by high-pass filtering, but traditional fixed cut-off frequency filters are suboptimal due to varying heart rates.
The proposed fast linear high-pass filters with time-varying cut-off frequencies controlled by instant heart rate efficiently suppress baseline wander in ECG signals with very low computational costs.
Promises improved ECG signal quality for low-power and wearable monitors; extends algorithmic noise reduction.
The paper presents a method of linear time-varying filtering, with extremely low computational costs, for the suppression of baseline drift in electrocardiographic (ECG) signals. An ECG signal is not periodic as the length of its heart cycles vary. In order to optimally suppress baseline drift by the use of a linear filter, we need a high-pass filter with time-varying cut-off frequency controlled by instant heart rate. Realization of the high-pass (HP) filter is based on a narrow-band low-pass (LP) filter of which output is subtracted from the delayed input. The base of an LP filter is an extremely low computational cost Lynn’s filter with rectangular impulse response. The optimal cut-off frequency of an HP filter for baseline wander suppression is identical to an instantaneous heart rate. Instantaneous length of heart cycles (e.g. RR intervals) are interpolated between QRS complexes to smoothly control cut-off frequency of the HP filter that has been used. We proved that a 0.5 dB decrease in transfer function, at a time-varying cut-off frequency of HP filter controlled by an instant heart rate, is acceptable when related to maximum error due to filtering. Presented in the article are the algorithms that enable the realization of time-variable filters with very low computational costs. We propose fast linear HP filters for the suppression of baseline wander with time-varying cut-off frequencies controlled by instant heart rate. The filters fulfil accepted professional standards and increase the efficiency of the noise suppression.
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Kozumplík et al. (2017) studied Baseline drift in electrocardiographic signals (n=1,500). Time-varying linear high-pass filter controlled by instant heart rate was evaluated on Mean signal error due to filtering. A time-varying linear high-pass filter controlled by instant heart rate successfully suppressed ECG baseline drift with a minimal mean error of 0.0124 µV.
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