Open AccessMONITORING OF NON-INVASIVE VITAL SIGNS FOR DETECTION OF SLEEP APNEA
Author(s) -
Han Zhang,
Weiwei Zhu,
Songbin Ye,
Sihua Li,
Baoxian Yu,
Zhiqiang Pang,
Rencan Nie
Publication year - 2021
Publication title -
journal of mechanics in medicine and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 30
eISSN - 1793-6810
pISSN - 0219-5194
DOI - 10.1142/s0219519421400078
Subject(s) - polysomnography , gold standard (test) , sleep apnea , vital signs , sleep (system call) , medicine , respiratory system , apnea , respiratory monitoring , obstructive sleep apnea , cardiology , physical medicine and rehabilitation , anesthesia , computer science , operating system
Sleep apnea (SA) syndrome is a respiratory disorder that occurs during the sleep. Polysomnography (PSG) has been widely applied by clinicians as a gold standard in the clinical diagnosis of SA syndrome. However, the use of PSG is inconvenient, intrusive, and significantly affects the sleep quality of patient. In this paper, we provide a nonintrusive solution for SA detection. Specifically, a force sensor was employed for the noninvasive vital sign acquisition during the patient’s sleep, where the respiratory signal was extracted adaptively by using the morphological filter. It was observed that the morphological variations before and during the occurrence of the SA events were significant for the SA discrimination. By taking advantage of the differential features with respect to the respiratory signal, the recognition of the SA event was performed using classifiers. For validation, the all-night PSG recordings of 12 volunteers with 8 SA syndrome patients were obtained from the National Clinical Research Center for Respiratory Disease. Numerical results showed that the proposed scheme achieved an averaged accuracy, sensitivity and specificity of 83.67%, 58.57% and 85.13%, respectively, for the SA recognition.