Natural entropy fluctuations discriminate similar-looking electric signals emitted from systems of different dynamics.
Complexity measures are introduced that quantify the change of the natural entropy fluctuations at different length scales in time series emitted from systems operating far from equilibrium. They identify impending sudden cardiac death (SD) by analyzing 15 min electrocardiograms, and comparing to those of truly healthy humans (H). These measures seem to be complementary to the ones suggested recently [Phys. Rev. E 70, 011106 (2004)]] and altogether enable the classification of individuals into three categories: H, heart disease patients, and SD. All the SD individuals, who exhibit critical dynamics, result in a common behavior.
Varotsos
P A
PA
Solid State Section, Physics Department, University of Athens, Panepistimiopolis, Zografos 157 84, Athens, Greece. pvaro@otenet.gr
Sarlis
N V
NV
Skordas
E S
ES
Lazaridou
M S
MS
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000145:classification / Q000175:diagnosis* / Q000401:mortality / Q000503:physiopathology*; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D019277:Entropy; D006329:Heart Conduction System / Q000503:physiopathology; D006339:Heart Rate; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity