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Erschienen in: Medical & Biological Engineering & Computing 9/2017

04.02.2017 | Original Article

Pseudo-real-time low-pass filter in ECG, self-adjustable to the frequency spectra of the waves

verfasst von: Ivaylo Christov, Tatyana Neycheva, Ramun Schmid, Todor Stoyanov, Roger Abächerli

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 9/2017

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Abstract

The electrocardiogram (ECG) acquisition is often accompanied by high-frequency electromyographic (EMG) noise. The noise is difficult to be filtered, due to considerable overlapping of its frequency spectrum to the frequency spectrum of the ECG. Today, filters must conform to the new guidelines (2007) for low-pass filtering in ECG with cutoffs of 150 Hz for adolescents and adults, and to 250 Hz for children. We are suggesting a pseudo-real-time low-pass filter, self-adjustable to the frequency spectra of the ECG waves. The filter is based on the approximation procedure of Savitzky–Golay with dynamic change in the cutoff frequency. The filter is implemented pseudo-real-time (real-time with a certain delay). An additional option is the automatic on/off triggering, depending on the presence/absence of EMG noise. The analysis of the proposed filter shows that the low-frequency components of the ECG (low-power P- and T-waves, PQ-, ST- and TP-segments) are filtered with a cutoff of 14 Hz, the high-power P- and T-waves are filtered with a cutoff frequency in the range of 20–30 Hz, and the high-frequency QRS complexes are filtered with cutoff frequency of higher than 100 Hz. The suggested dynamic filter satisfies the conflicting requirements for a strong suppression of EMG noise and at the same time a maximal preservation of the ECG high-frequency components.

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Metadaten
Titel
Pseudo-real-time low-pass filter in ECG, self-adjustable to the frequency spectra of the waves
verfasst von
Ivaylo Christov
Tatyana Neycheva
Ramun Schmid
Todor Stoyanov
Roger Abächerli
Publikationsdatum
04.02.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 9/2017
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-017-1625-y

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