| Title | Sleep disordered breathing detection using heart rate variability and R-peak envelope spectrogram. | ||
| Author | Al-Abed, Mohammad A; Manry, Michael; Burk, John R; Lucas, Edgar A; Behbehani, Khosrow | ||
| Journal | Annu Int Conf IEEE Eng Med Biol Soc | Publication Year/Month | 2009 |
| PMID | 19963946 | PMCID | -N/A- |
| Affiliation | 1.Department of Bioengineering, the University of Texas at Arlington, Arlington, TX 76010, USA. mohammad@uta.edu. | ||
We report that combining the interbeat heart rate as measured by the RR interval (RR) and R-peak envelope (RPE) derived from R-peak of ECG waveform may significantly improve the detection of sleep disordered breathing (SDB) from single lead ECG recording. The method uses textural features extracted from normalized gray-level cooccurrence matrices of the time frequency plots of HRV or RPE sequences. An optimum subset of textural features is selected for classification of the records. A multi-layer perceptron (MLP) serves as a classifier. To evaluate the performance of the proposed method, single Lead ECG recordings from 7 normal subjects and 7 obstructive sleep apnea patients were used. With 500 randomized Monte-Carlo simulations, the average training sensitivity, specificity and accuracy were 100.0%, 99.9%, and 99.9%, respectively. The mean testing sensitivity, specificity and accuracy were 99.0%, 96.7%, and 97.8%, respectively.