Detection and Classification of Sleep Apnea and Hypopnea Using PPG and SpO$_2$ Signals.
Remo LazazzeraMargot DeviaeneCarolina VaronBertien BuyseDries TestelmansPablo LagunaEduardo GilGuy CarraultPublished in: IEEE Trans. Biomed. Eng. (2021)
Keyphrases
- sleep stage
- sleep apnea
- independent component analysis
- automatic classification
- automatic analysis
- detection method
- classification method
- feature extraction
- automatic detection
- feature space
- classification accuracy
- support vector
- pattern recognition
- neyman pearson
- false alarms
- classification models
- classification algorithm
- digital mammograms
- microcalcification clusters
- eeg signals
- classification scheme
- false positives
- training samples
- text classification
- detection rate
- signal processing
- feature set
- object detection
- noisy environments
- robust detection
- support vector machine
- training data
- physiological parameters
- image processing
- feature selection
- neural network