Automatic HRV estimation method for respiratory events discrimination

The present contribution presents results of wavelet based methods for computing short-term Heart Rate Variability (HRV) in order to better identify respiratory events by means of analyzing only one lead electrocardiographic (ECG) recordings. Besides RR time interval variability, the performance of other approaches was investigated for the assessment of HRV, such as the intervals between the onsets of successive P waves (PP time series), PR intervals, or ST intervals time series. We analyzed their detection capabilities on respiration events, such as apneas, hypopneas, arterial blood O
₂
desaturation or arousals, which are used in the diagnoses and characterization of obstructive sleep apnea syndrome (OSAS). The proposed approach gives good results without prior baseline wandering elimination.