Sleep apnea detection based on spectral analysis of three ECG - derived respiratory signals

An apnea detection method based on spectral analysis was used to assess the performance of three ECG derived respiratory (EDR) signals. They were obtained on R wave area (EDR1), heart rate variability (EDR2) and R peak amplitude (EDR3) of ECG record in 8 patients with sleep apnea syndrome. The mean, central, peak and first quartile frequencies were computed from the spectrum every 1 min for each EDR. For each frequency parameter a threshold-based decision was carried out on every 1 min segment of the three EDR, classifying it as `apnea' when its frequency value was below a determined threshold or as `not apnea' in other cases. Results indicated that EDR1, based on R wave area has better performance in detecting apnea episodes with values of specificity (Sp) and sensitivity (Se) near 90%; EDR2 showed similar Sp but lower Se (78%); whereas EDR3 based on R peak amplitude did not detect appropriately the apneas episodes reaching Sp and Se values near 60%.