Automated Recognition of Obstructive Sleep Apnea Syndrome Using Support Vector Machine Classifier

Obstructive sleep apnea (OSA) is a common sleep disorder that causes pauses of breathing due to repetitive obstruction of the upper airways of the respiratory system. The effect of this phenomenon can be observed in other physiological signals like the heart rate variability, oxygen saturation, and...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2012-05, Vol.16 (3), p.463-468
Hauptverfasser:	Al-Angari, H. M., Sahakian, A. V.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adolescent Adult Case-Control Studies Child Heart Rate - physiology Heart rate variability Humans Kernel Middle Aged obstructive sleep apnea (OSA) Oximetry Oxygen - blood oxygen saturation paradoxical breathing Pattern Recognition, Automated - methods Polynomials Polysomnography - methods respiratory efforts Respiratory Rate - physiology Respiratory system Sensitivity Sleep apnea Sleep Apnea, Obstructive - blood Sleep Apnea, Obstructive - physiopathology Sleep disorders Support Vector Machine Support vector machines support vector machines (SVM)
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