TY  - JOUR
N2  - Sleep Apnea is a breathing disorder that occurs while the patient is sleeping. Traditionally, Polysomnography is used to diagnose it. However, it is quite inconvenient and expensive. Because of the troublesome diagnosis, this ailment often remained undiagnosed. This paper aims at the development of such a method that provides an easy diagnostic solution to the doctors. Electrocardiogram (ECG) is one of the most common tests done at the hospitals. In this paper, we aim to develop a method which deploys ECG data to diagnose the sleep ailment, Apnea. A technique deploying wavelet packet transform on RR interval of ECG has been presented. Probability density functions of data, both when Apnea is present and when it is not, are obtained by constructing histograms of decision variable for each signal segment. From the overlapping PDFs of the normal and abnormal cases, a threshold is then derived. This helped in segregating the Apnea cases from normal cases. The stated method provided a 100 accuracy in diagnosing Sleep Apnea. © 2013 IEEE.
ID  - scholars12207
KW  - Electrocardiography; Probability density function; Signal processing
KW  -  Breathing disorders; Decision variables; ECG data; Novel techniques; Polysomnography; RR intervals; Sleep apnea; Wavelet packet transforms
KW  -  Sleep research
Y1  - 2019///
A1  - Ali, S.Q.
A1  - Khalid, S.
A1  - Belhaouari, S.B.
JF  - IEEE Access
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063769951&doi=10.1109%2fACCESS.2019.2904601&partnerID=40&md5=0398384a3e40417b5cd57eb4db992a8d
VL  - 7
AV  - none
N1  - cited By 5
SP  - 35184
TI  - A Novel Technique to Diagnose Sleep Apnea in Suspected Patients Using Their ECG Data
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 21693536
EP  - 35194
ER  -