Detection of Sleep Apnea from Electrocardiogram Using Wavelet Transform

Nopadol Uchaipichat(1*)

(1) Med-Intelligence and Innovation Laboratory (MII), Department of Electrical Engineering, Faculty of Engineering, Thammasat University, Thailand
(*) Corresponding author


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Abstract


The objective of this study is to investigate the characteristic of electrocardiogram (ECG) for detecting sleep apnea. The heart rate variability (HRV) was extracted from RR interval information from ECG trace. In this study the HRV within 5 minutes sliding window was analyzed with continuous wavelet transform.  The sum energy of wavelet power spectrum density between 0.015 and 0.05 Hz was studied in this analysis. Then the position of sliding 5-minute window was shifted along the HRV signal in steps of 3 minutes until the end of trace. The interquartile range (IQR) of the analyzed energy was used as the maker in this investigation. As the results it is found that the IQR performs in order to detect sleep apnea with area under receiving operating characteristics of 0.83. The performance in sleep apnea detection achieved at 100% sensitivity and 70% specificity.
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Keywords


Sleep Apnea; Electrocardiogram; Wavelet Transform; Heart Rate Variability; Stroke

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References


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