Fully automated unsupervised artefact removal in multichannel electroencephalogram using wavelet-independent component analysis with density-based spatial clustering of application with noise.
Chong Yeh SaiNorrima MokhtarMasahiro IwahashiPaul CummingHamzah ArofPublished in: IET Signal Process. (2021)
Keyphrases
- independent component analysis
- fully automated
- spatial clustering
- single channel
- fully automatic
- principal component analysis
- clustering method
- independent subspace analysis
- signal processing
- independent components
- wavelet transform
- multi channel
- factor analysis
- blind source separation
- wavelet decomposition
- spatial objects
- spatial data
- multiscale
- data analysis
- feature extraction
- eeg data
- clustering algorithm
- databases