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Found 3 papers, 1 papers with code
Fully Adaptive Time-Varying Wave-Shape Model: Applications in Biomedical Signal Processing
The algorithm was validated on both real and synthetic signals for the tasks of denoising, decomposition and adaptive segmentation.
Temporal convolutional networks and transformers for classifying the sleep stage in awake or asleep using pulse oximetry signals
In this work, we developed a network architecture with the aim of classifying the sleep stage in awake or asleep using only HR signals from a pulse oximeter.
Classifying sleep-wake stages through recurrent neural networks using pulse oximetry signals
The regulation of the autonomic nervous system changes with the sleep stages causing variations in the physiological variables.
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