Adaptive classification system for real-time detection of apnea and hypopnea events

IEEE EMBS Special Topic Conference on Point-of-Care (POC) Healthcare Technologies: Synergy Towards Better Global Healthcare, PHT 2013

Volumn , Issue , 2013, Pages 42-45

  Koley, B ^a   Dey, D ^b  

^a DR B C ROY ENGINEERING COLLEGE   (India)

^b JADAVPUR UNIVERSITY   (India)

Author keywords

Obstructive sleep apnea; real time monitoring; respiration signal; support vector machine

Indexed keywords

ADAPTIVE CLASSIFICATION; BINARY CLASSIFIERS; BREATHING PATTERNS; CLASSIFICATION SYSTEM; EVENT DETECTION; OBSTRUCTIVE SLEEP APNEA; OFFLINE; ON-LINE TESTS; REAL TIME; REAL TIME MONITORING; REAL-TIME DETECTION; RESPIRATION SIGNALS; SYSTEM USE;

HEALTH CARE; IMAGE RETRIEVAL; INTERACTIVE COMPUTER SYSTEMS; PERSONAL COMPUTERS; REAL TIME SYSTEMS; SUPPORT VECTOR MACHINES;

SIGNAL DETECTION;

EID: 84874569808     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PHT.2013.6461280     Document Type: Conference Paper

References (11)

1. W. W. Flemons, M. R. Littner, J. A. Rowlet, P. Gay, W. M. Anderson, D. W. Hudgel, R. D. McEvoy, and D. I. Loube, "Home diagnosis of sleep apnea: A systematic review of the literature," Chest, vol. 124, pp. 1543-1579, 2003.
2. T. Young, P. E. Peppard, and D. G. Gottlier, "Epidemiology of obstructive sleep apnea, a population health perspective," Amer. J. Respir. Crit. Care Med., vol. 165, pp. 1217-1239, 2002. (Pubitemid 34461732)
3. American Academy of Sleep Medicine (AASM) Task Force, "Sleep-related breathing disorders in adults: Recommendations for syndrome definition and measurement techniques in clinical research," Sleep, vol. 22, pp. 667-689, Aug. 1999.
4. Standards of Practice Committee and American Sleep Disorders Association, "Portable recording in the assessment of obstructive sleep apnea," Sleep, vol. 17, no. 4, pp. 378-392, 1994.
5. H. Nakano, T. Tanigawa, T. Furukawa, and S. Nishima, "Automatic detection of sleep-disordered breathing from a single-channel airflow record," Eur. Respir. J., vol. 29, pp. 728-736, 2007. (Pubitemid 46554623)
6. S. I. Rathnayake, I. A. Wood, U. R. Abeyratne, and C. Hukins, "Nonlinear features for single-channel diagnosis of sleep-disordered breathing diseases," IEEE Trans. Biomed. Eng., vol. 57, no. 8, pp. 1973-1981, Aug. 2010.
7. M. Bsoul, H. Minn, and L. Tamil, "Apnea MedAssist: Real-time sleep apnea monitor using single-lead ECG," IEEE Trans. Inf. Technol. Biomed., vol. 15, no. 3, pp. 416-427, May 2011.
8. A. Burgos, A. Goni, A. Illarramendi, and J. Bermudez, "Real-Time detection of apneas on a PDA," IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 4, pp. 995-1002, July 2010.
9. B. Xie and H. Minn, "Real-time sleep apnea detection by classifier combination," IEEE Trans. Inf. Technol. Biomed., vol. 16, no.3, pp. 469-477, 2012.
10. C. Cortes and V. Vapnik, "Support-vector machines," Mach. Learning, vol. 20, pp. 273-297, 1995.
11. F. Melgani and L. Bruzzone, "Classification of hyper spectral remote sensing images with support vector machine," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, Aug. 2004.