Spectral analysis of R wave attenuation and heart rate variability for detection of cheyne stokes breathing.
Spectral analysis was carried out on the R-Wave Attenuation (RWA) trend and Heart Rate Variability (HRV) series, derived from the polysomnographic Electrocardiogram (ECG) of the subjects with and without Cheyne Stokes Breathing. Nocturnal polysomnography was performed on 16 Normal subjects and 7 subjects with Cheyne Stokes Breathing (CSB) patients. The polysomnographic ECG data was divided into fifteen minute epochs for analysis. These epochs are processed to obtain the RWA. Hilbert Transform based algorithm [4] was used for QRS detection. Power spectrum of RWA and HRV are computed for each clip by using Welch's averaged periodogram method. HRV is sensitive to REM sleep as well and hence not specific to sleep apnea [12]. Hence the parameters derived from HRV alone cannot be used as diagnostic markers. Hence a combined detection scheme which uses parameters derived from RWA and HRV power spectrum is used in the proposed method to increase detection accuracy. This method produced a sensitivity of 84.75% and specificity of 87.03% in the training set and sensitivity of 85.78% and a specificity of 87.19% in the test set.
Suhas
Sanjee
S
Joint Biomedical Engineering Program, University of Texas at Arlington and University of Texas Southwestern, Medical Center at Dallas.
Vijendra
Sridhar
S
Burk
John
J
Lucas
Edgar
E
Behbehani
Khosrow
K