TY - GEN
T1 - A novel method for identification of obstructive sleep apnea
AU - Hossen, Abdulnasir
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/18
Y1 - 2017/10/18
N2 - A novel and robust non-invasive method for identification of patients with obstructive sleep apnea (OSA) is introduced in this paper. Most sleep clinics suffer from the large number of patients with snoring who think that they have OSA and needs full overnight polysomnography. Thus, a need for simple non-invasive methods is of great importance to screen this large number of patients before the polysomnography. The method used in this paper depends on the continuous-wavelet transform and to be considered one of the methods with high-identification efficiency. A clear advantage of this method is its consistency with changing the wavelet-filter type. The data used in this paper are downloaded from MIT data bases. 60 subjects (40 OSA and 20 normal) are to be divided equally for both training and testing cycles.
AB - A novel and robust non-invasive method for identification of patients with obstructive sleep apnea (OSA) is introduced in this paper. Most sleep clinics suffer from the large number of patients with snoring who think that they have OSA and needs full overnight polysomnography. Thus, a need for simple non-invasive methods is of great importance to screen this large number of patients before the polysomnography. The method used in this paper depends on the continuous-wavelet transform and to be considered one of the methods with high-identification efficiency. A clear advantage of this method is its consistency with changing the wavelet-filter type. The data used in this paper are downloaded from MIT data bases. 60 subjects (40 OSA and 20 normal) are to be divided equally for both training and testing cycles.
KW - Continuous Wavelet Transform
KW - Entropy
KW - Histogram
KW - Identification
KW - Obstructive Sleep Apnea
UR - http://www.scopus.com/inward/record.url?scp=85040022851&partnerID=8YFLogxK
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U2 - 10.1109/ISCAIE.2017.8074943
DO - 10.1109/ISCAIE.2017.8074943
M3 - Conference contribution
AN - SCOPUS:85040022851
T3 - ISCAIE 2017 - 2017 IEEE Symposium on Computer Applications and Industrial Electronics
SP - 22
EP - 27
BT - ISCAIE 2017 - 2017 IEEE Symposium on Computer Applications and Industrial Electronics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2017
Y2 - 24 April 2017 through 25 April 2017
ER -