Prediction of the obstruction sites in the upper airway in sleep-disordered breathing based on snoring sound parameters: a systematic review

• Published in: Sleep medicine Vol. 88; pp. 116 - 133
• Main Authors: Huang, Zhengfei, Aarab, Ghizlane, Ravesloot, Madeline J.L., Zhou, Ning, Bosschieter, Pien F.N., van Selms, Maurits K.A., den Haan, Chantal, de Vries, Nico, Lobbezoo, Frank, Hilgevoord, Antonius A.J.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2021
• Subjects: Airway Obstruction; Frequency; Humans; Machine learning; Nose; Prediction model; Sleep Apnea Syndromes - diagnosis; Sleep Apnea, Obstructive; Snoring; Snoring sound; Sound; Upper airway; Frequency; Snoring sound; Prediction model; Machine learning; Upper airway

Identification of the obstruction site in the upper airway may help in treatment selection for patients with sleep-disordered breathing. Because of limitations of existing techniques, there is a continuous search for more feasible methods. Snoring sound parameters were hypothesized to be potential p...