Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.
It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.
Torres
M E
ME
Universidad Nacional de Entre Ríos, Facultad de Ingeniería, Bioingeniería, CC 47, Suc 3, Paraná (3100), ER, Argentina. metorres@ceride.gov.ar
Añino
M M
MM
Schlotthauer
G
G
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D001921:Brain / Q000473:pathology; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods; D019277:Entropy; D006801:Humans; D015233:Models, Statistical; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013997:Time Factors