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IEEE transactions on bio-medical engineering v.64 no.2, 2017년, pp.295 - 301   SCI SCIE
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Apnea–Hypopnea Index Prediction Using Electrocardiogram Acquired During the Sleep-Onset Period

Jung, Da Woon (Interdisciplinary Program for Biomedical EngineeringSeoul National University Graduate School ) ; Hwang, Su Hwan (Interdisciplinary Program for Biomedical EngineeringSeoul National University Graduate School ) ; Lee, Yu Jin (Department of Psychiatry and Behavioral ScienceSeoul National University College of Medicine, and the Center for Sleep and ChronobiologySeoul National University Hospital ) ; Jeong, Do-Un (Department of Psychiatry and Behavioral ScienceSeoul National University College of Medicine, and the Center for Sleep and ChronobiologySeoul National University Hospital ) ; Park, Kwang Suk ;
  • 초록  

    The most widely used methods for predicting obstructive sleep apnea are based on clinical or anatomico-functional features. To improve exactitude in obstructive sleep apnea screening, this study aimed to devise a new predictor of apnea-hypopnea index. We hypothesized that less irregular respiration cycles would be observed in the patients with more severe obstructive sleep apnea during the sleep-onset period. From each of the 156 and 70 single-lead electrocardiograms collected from the internal polysomnographic database and from the Physionet Apnea-ECG database, respectively, the 150-s sleep-onset period was determined and the respiration cycles during this period were detected. Using the coefficient of variation of the respiration cycles, obtained from the internal dataset, as a predictor, the apnea-hypopnea index predictive model was developed through regression analyses and k-fold cross-validations. The apnea-hypopnea index predictability of the regression model was tested with the Physionet Apnea-ECG database. The regression model trained and validated from the 143 and 13 data, respectively, produced an absolute error (mean +/- SD) of 3.65 +/- 2.98 events/h and a Pearson's correlation coefficient of 0.97 (P


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