Comparative analysis of different Wigner-Ville distribution implementations for the ECG-based detection of obstructive sleep apnea

Obstructive sleep apnea (OSA) syndrome is a common breathing abnormality. During apnea, the airflow is impeded or totally interrupted. The reaction of the autonomic nervous system terminates the apnea and also leads to changes in heart rate variability (HRV). As shown in previous studies, the spectral analysis of HRV allows for a diagnosis of apnea. Therefore, a high quality time-frequency distribution is of great significance. TheWigner-Ville- Distribution (WVD) offers a very high resolution in both, time and frequency. However, the proper handling of cross terms resulting in the calculation of the WVD is a crucial point using the WVD. To cope with this task, the presented work compares different methods regarding their ability of cross term suppression and applicability. Furthermore it is shown that using spectral information of ECG overnight recordings from the Physionet Apnea Data-base, these datasets can be separated.