An Unsupervised Multichannel Artifact Detection Method for Sleep EEG Based on Riemannian Geometry.
Elizaveta SaifutdinováMarco CongedoDaniela Urbaczka DudysovaLenka LhotskáJana KoprivovaVáclav GerlaPublished in: Sensors (2019)
Keyphrases
- detection method
- sleep stage
- eeg signals
- obstructive sleep apnea
- single channel
- information geometry
- face detection
- detection algorithm
- multi channel
- geodesic distance
- feature detection
- sleep apnea
- tangent space
- signal processing
- supervised learning
- three dimensional
- fisher information
- brain computer interface
- brain activity
- saliency detection
- euclidean space
- manifold learning
- shape analysis
- semi supervised
- riemannian manifolds
- affine invariant
- riemannian metric
- support vector data description
- principal component analysis