A model-based monitor of human sleep stages
Biological Cybernetics
Determining a continuous marker for sleep depth
Computers in Biology and Medicine
Fuzzy reasoning used to detect apneic events in the sleep apnea-hypopnea syndrome
Expert Systems with Applications: An International Journal
Computer program for automated sleep depth estimation
Computer Methods and Programs in Biomedicine
Genetic fuzzy classifier for sleep stage identification
Computers in Biology and Medicine
A reliable probabilistic sleep stager based on a single EEG signal
Artificial Intelligence in Medicine
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Sleep staging is one of the most important tasks within the context of sleep studies. For more than 40 years the gold standard to the characterization of patient's sleep macrostructure has been based on set of rules proposed by Rechtschaffen and Kales and recently modified by the American Academy of Sleep Medicine. Nevertheless the resulting map of sleep, the so-called hypnogram, has several limitations such as its low temporal resolution and the unnatural characterization of sleep through the assignment of discrete sleep states. This study reports an automatic method for the characterization of the structure of the sleep. The main intention is to overcome limitations of epoch-based sleep staging by obtaining a more continuous evolution of the sleep of the patient. The method is based on the use of fuzzy inference in order to avoid binary decisions, provide soft transitions and enable concurrent characterization of the different states. It is proven, in addition, how the new proposed continuous representation can still be used to generate the classical epoch-based hypnogram.