Achieving Accurate Automatic Sleep Apnea/Hypopnea Syndrome Assessment Using Nasal Pressure Signal.
Ying-Sheng LinYi-Pao WuYi-Chung WuPei-Lin LeeChia-Hsiang YangPublished in: IEEE J. Biomed. Health Informatics (2022)
Keyphrases
- apnea hypopnea
- sleep apnea
- obstructive sleep apnea
- sleep stage
- signal processing
- physiological parameters
- high quality
- automatic analysis
- non stationary
- semi automatic
- website
- signal detection
- neural network
- high frequency
- highly accurate
- fully automatic
- computationally efficient
- data driven
- high precision
- frequency domain
- random noise
- radio frequency
- multiscale
- feature extraction
- image sequences
- machine learning