Automated recognition of obstructive sleep apnea syndrome using support vector machine classifier

IEEE Transactions on Information Technology in Biomedicine

Volumn 16, Issue 3, 2012, Pages 463-468

  Al Angari, Haitham M ^a   Sahakian, Alan V ^a  

^a Northwestern University   (United States)

Author keywords

Heart rate variability; obstructive sleep apnea (OSA); oxygen saturation; paradoxical breathing; respiratory efforts; support vector machines (SVM)

Indexed keywords

HEART RATE VARIABILITY; OBSTRUCTIVE SLEEP APNEA; OXYGEN SATURATION; PARADOXICAL BREATHING; RESPIRATORY EFFORTS;

HEART; OXYGEN; POLYNOMIALS; RESPIRATORY SYSTEM; SLEEP RESEARCH;

SUPPORT VECTOR MACHINES;

OXYGEN;

ADOLESCENT; ADULT; ARTICLE; AUTOMATED PATTERN RECOGNITION; BLOOD; BREATHING RATE; CASE CONTROL STUDY; CHILD; HEART RATE; HUMAN; METHODOLOGY; MIDDLE AGED; OXIMETRY; PATHOPHYSIOLOGY; PHYSIOLOGY; POLYSOMNOGRAPHY; SLEEP APNEA SYNDROME; SUPPORT VECTOR MACHINE;

ADOLESCENT; ADULT; CASE-CONTROL STUDIES; CHILD; HEART RATE; HUMANS; MIDDLE AGED; OXIMETRY; OXYGEN; PATTERN RECOGNITION, AUTOMATED; POLYSOMNOGRAPHY; RESPIRATORY RATE; SLEEP APNEA, OBSTRUCTIVE; SUPPORT VECTOR MACHINES;

EID: 84860670119     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2012.2185809     Document Type: Article

References (22)

1. American Academy of Sleep Medicine, "Sleep-related breathing disorders in adults: Recommendations for symptom definition and measurement techniques in clinical trials," Sleep, vol. 22, pp. 667-689, 1999.
2. T. Penzel, J. McNames, P. de Chazal, B. Raymond, A. Murray, and G. Moody, "Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings," Med. Biol. Eng. Comp., vol. 40, pp. 402-407, 2002.
3. P. deChazal, C. Heneghan, E. Sheridan, R. Reilly, P. Nolan, and M. J. O'Malley, "Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea," IEEE Trans. Biomed. Eng., vol. 50, no. 6, pp. 686-696, Jun. 2003.
4. C. Maier, V. Rödler, H. Wenz, and H. Dickhaus, "ECG fingerprints of obstructed breathing in sleep apnea patients," IEEE Eng. Med. Biol. Mag., vol. 28, no. 6, pp. 41-48, Nov./Dec. 2009.
5. E. Gil, M. Mendez, J. M. Vergara, S. Cerutti, A. M. Bianchi, and P. Laguna, "Discrimination of sleep-apnea-related decreases in the amplitude fluctuations of PPG signal in children by HRV analysis," IEEE Trans. Biomed. Eng., vol. 56, no. 4, pp. 1005-1014, Apr. 2009.
6. P. Várady, S. Bongár, and Z. Benyó, "Detection of airway obstructions and sleep apnea by analyzing the phase relation of respiration movement signals," IEEE Trans. Instrum. Measure., vol. 52, no. 1, pp. 2-6, Feb. 2003.
7. Y. S. Shalom, "Analysis of sleep apnea", U.S. Patent, no. 693 601 1B2, Aug. 2005.
8. M. Hoke, K. Lehnertz, C. Pantev, and B. Lükenher, "Spatiotemporal aspects of synergetic processes in the auditory cortex as revealed by the magnetoencephalogram," in Brain Dynamics, Progress and Perspectives (Springer Series in Brain Dynamics). Berlin, Germany: Springer-Verlag, 1989.
9. J. P. Lachaux, E. Rodriguez, J. Martinerie, and F. J. Varela, "Measuring phase synchrony in brain signals," Hum. BrainMap., vol. 8, pp. 194-208, 1999.
10. F. Mormann, K. Lehnertz, P. David, and C. E. Elger, "Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients," Physica D, vol. 144, pp. 358-369, 2000.
11. R. Q. Quiroga, A. Kraskov, T. Kreuz, and P. Grassberger, "Performance of different synchronization measures in real data: A case study on electroencephalographic signals," Phys. Rev. E, vol. 65, p. 041903, 2002.
12. [Online]. Available: www.jhucct.com/shhs
13. J. Pan andW. J. Tompkins, "A real-time QRS detection algorithm," IEEE Trans. Biomed. Eng., vol. BME-32, no. 3, pp. 230-236, Mar. 1985.
14. V. N Vapnik, The Nature of Statistical Learning Theory. NewYork: Springer-Verlag, 1995.
15. A. H. Khandoker, C. K. Karmakar, and M. Palaniswami, "Automated recognition of patients with obstructive sleep apnoea using wavelet-based features of electrocardiogram recordings," Comput. Biol. Med., vol. 39, pp. 88-96, 2009.
16. J. M. Bland and D. G. Altman, "Statistical methods for assessing agreement between two methods of clinical measurement," Lancet, vol. 1, pp. 307-310, 1986.
17. J.A. Loadsman and I. Wilcox, "Is obstructive sleep apnoea a rapid eye movement-predominant phenomenon?" Br. J. Anaesth., vol. 85, pp. 354-358, 2000.
18. M. C. K. Khoo, T. S. Kim, and R. B. Berry, "Spectral indices of cardiac autonomic function in obstructive sleep apnea," Sleep, vol. 22, pp. 443-451, 1999.
19. C. Guilleminault, S. Connolly, R. Winkle, K. Melvin, and A. Tilkian, "Cyclical variation of the heart rate in sleep apnoea syndrome," Lancet, vol. 1, pp. 126-131, 1984.
20. R. Ferri, L. Parrino, A. Smerieri, M. G. Tarzano, M. Elia, S. A. Musumeci, and S. Pettinato, "Cyclic alternation pattern and spectral analysis of heart rate variability during normal sleep," J. Sleep. Res., vol. 9, pp. 13-18, 2000.
21. B. Raymond, R. M. Cayton, andM. J. Chappell, "Combined index of heart rate variability and oximetry in screening for the sleep apnoea/hypopnea syndrome," J. Sleep. Res., vol. 12, pp. 53-61, 2003.
22. X. Li, L. Wang, and E. Sung, "AdaBoost with SVM-based component classifier," Eng. Appl. Artif. Intell., vol. 21, pp. 785-795, 2008.