Determining a continuous marker for sleep depth
Computers in Biology and Medicine
A new method for sleep apnea classification using wavelets and feedforward neural networks
Artificial Intelligence in Medicine
Classıfıcation of sleep apnea by using wavelet transform and artificial neural networks
Expert Systems with Applications: An International Journal
Journal of Medical Systems
A novel sleep apnea detection system in electroencephalogram using frequency variation
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Computers in Biology and Medicine
IEEE Transactions on Neural Networks
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Continuous positive airway pressure treatment (CPAP) is administered to treat the common disorder of obstructive sleep apnea. However, patients receiving CPAP treatment without a sleep assessment and clinical diagnosis often do not feel or understand the improvement in their condition, necessitating a sleep quality improvement index for physicians to analyze improvements in patient treatment rapidly. This work presents a novel sleep quality evaluation system that calculates the improvement value for sleep quality using electroencephalogram and electrocardiogram signal features, as well as fuzzy inferences. Experimental results indicate that the sleep quality improvement rating of the proposed system and that of the apnea-hyponea index correlate with each other. Importantly, the proposed system can identify considerable levels of improvement in the physiological signals of patients having undergone CPAP treatment.