ArticleBiomedical engineering letters2018
The application of ECG cancellation in diaphragmatic electromyographic by using stationary wavelet transform.
Article in Biomedical engineering letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs.Frontiers in bioengineering and biotechnology · 2024Article
- Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality.Sensors (Basel, Switzerland) · 2020Article
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2 authors.
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Abstract
In this paper, we present and investigate a special kind of stationary wavelet algorithm using "inverse" hard threshold to eliminate the electrocardiogram (ECG) interference included in diaphragmatic electromyographic (EMGdi). Differing from traditional wavelet hard threshold, "inverse" hard threshold is used to shrink strong coefficients of ECG interference and reserve weak coefficients of EMGdi signal. Meanwhile, a novel QRS location algorithm is proposed for the position detection of R wave by using low frequency coefficients in this paper. With the proposed method, raw EMGdi is decomposed by wavelet at fifth scale. Then, each ECG interference threshold is calculated by mean square, which is estimated by wavelet coefficients in the ECG cycle at each level. Finally, ECG interference wavelet coefficients are removed by "inverse" hard threshold, and then the de-noised signal is reconstructed by wavelet coefficients. The simulation and clinical EMGdi de-noising results show that the "inverse" hard threshold investigated in this paper removes the ECG interference in EMGdi availably and reserves its signal characteristics effectively, as compared to wavelet threshold.
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