Cargando…
Effective automated method for detection and suppression of muscle artefacts from single-channel EEG signal
This Letter proposes an automated method for the detection and suppression of muscle artefacts (MAs) in the single-channel electroencephalogram (EEG) signal based on variational mode decomposition (VMD) and zero crossings count threshold criterion without the use of reference electromyogram (EMG). T...
Autores principales: | Saini, Manali, Satija, Udit, Upadhayay, Madhur Deo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Institution of Engineering and Technology
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199290/ https://www.ncbi.nlm.nih.gov/pubmed/32431850 http://dx.doi.org/10.1049/htl.2019.0053 |
Ejemplares similares
-
An Unsupervised Method for Artefact Removal in EEG Signals
por: Mur, Angel, et al.
Publicado: (2019) -
Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal
por: Satija, Udit, et al.
Publicado: (2017) -
Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests
por: Lorch, Benedikt, et al.
Publicado: (2017) -
Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: Implications for motion artefact correction
por: Spencer, Glyn S., et al.
Publicado: (2018) -
Artefact detection and quality assessment of ambulatory ECG signals
por: Moeyersons, Jonathan, et al.
Publicado: (2019)