DocumentCode
3032225
Title
Detection of OSAHS using only time-domain property of snoring signal
Author
Hou, Limin ; Xie, Su ; Kai, Shankai ; Song, Wei
Author_Institution
Sch. of Telecommun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear
2011
fDate
26-28 July 2011
Firstpage
519
Lastpage
522
Abstract
Polysomnography (PSG) is the standard method for obstructive sleep apnea hypopnea syndrome (OSAHS) diagnosis in medical, but the shortcomings in it have pushed many researchers to find a more convenient and effective way to detect OSAHS. With this purpose, a new technique for OSAHS assessment is proposed in this paper. It combined the properties of respiratory events with an ingenious dynamic threshold endpoint detection method to realize the automatic detection of respiratory events, and then obtained the apnea hypopnea index (AHI) to determine the patient´s condition. The method was evaluated on the whole night snoring signal of 34 patients. Compared the results with those monitored by PSG, it has shown that the accuracy of this method can reach above 90%, at the same time, it has the advantages in low cost, high speed, easy to operate and so on.
Keywords
medical signal detection; patient diagnosis; OSAHS detection; apnea hypopnea index; ingenious dynamic threshold endpoint detection method; obstructive sleep apnea hypopnea syndrome diagnosis; patient night snoring signal; polysomnography; respiratory event automatic detection; respiratory events; standard method; time-domain property; Accuracy; Indexes; Medical diagnostic imaging; Monitoring; Noise measurement; Sleep apnea; Time domain analysis; Apnea Hyponea Index; Dynamic Threshold Endpoint Detection; Obstructive Sleep Apnea Hypopnea Syndrome; Snore;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-61284-771-9
Type
conf
DOI
10.1109/ICMT.2011.6002183
Filename
6002183
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