Key result
A new Lean Mean Square (LMS) Widrow adaptive structure algorithm successfully removed ECG and power line interference artefacts from surface diaphragm EMG signals without supplementary electrodes.
A novel LMS adaptive structure effectively removes ECG and power line noise from surface respiratory EMG signals without needing additional electrodes.
The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.
No takes yet. Share an insight, caveat, or question.
Yacoub et al. (2008) studied Surface electromyography signal noise. Lean Mean Square (LMS) Widrow adaptive structure algorithm vs. Already conducted research results was evaluated on Removal of ECG and power line interference artefacts. A new Lean Mean Square (LMS) Widrow adaptive structure algorithm successfully removed ECG and power line interference artefacts from surface diaphragm EMG signals without supplementary electrodes.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: