Identification of individual sleep apnea events from the ECG using neural networks and a dynamic Markovian state model

Computers in Cardiology

Volumn 31, Issue , 2004, Pages 297-300

  Bystricky, W ^a   Safer, A ^b  

^a TSD ^*  (Germany)

^b ABBOTT GMBH AND CO KG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; LEARNING SYSTEMS; NATURAL FREQUENCIES; NEURAL NETWORKS; SPURIOUS SIGNAL NOISE;

HEART BEATS; HIGH FREQUENCY NOISE; SLEEP APNEA EVENTS;

ELECTROCARDIOGRAPHY;

EID: 28144433355     PISSN: 02766574     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Bishop CM. Neural Networks for Pattern Recognition. Oxford University Press, 1995.
2. Computers in Cardiology Challenge 2000. Detecting Sleep Apnea from the ECG. Computers in Cardiology 2000; 27:739-760.
3. MacKay DJC. Bayesian Methods for Adaptive Models. Ph.D. Thesis, California Institute of Technology, 1992
4. Numerical Recipes in C: The Art of Scientific Computing. Cambridge Univ Press 1988-1992.
5. Penzel T, McNames J, de Chazal P, Raymond B, Murray A, Moody G. Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings. Medical & Biological Engineering & Computing 2002; 40:402-407.