Pregled bibliografske jedinice broj: 320934
Extracting Self-affine (Fractal) Features from Physiologic Signals
Extracting Self-affine (Fractal) Features from Physiologic Signals // Proceedings of the 14th International Workshop on Systems, Signals and Image Processing, IWSSIP 2007, Maribor, Slovenija, 2007. / Čučej, Žarko ; Planinšič, Peter ; Gleich, Dušan (ur.).
Maribor: Univerza v Mariboru, 2007. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 320934 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Extracting Self-affine (Fractal) Features from Physiologic Signals
Autori
Michieli, Ivan ; Medved Rogina, Branka
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 14th International Workshop on Systems, Signals and Image Processing, IWSSIP 2007, Maribor, Slovenija, 2007.
/ Čučej, Žarko ; Planinšič, Peter ; Gleich, Dušan - Maribor : Univerza v Mariboru, 2007
ISBN
978-961-248-029-5
Skup
14th International Workshop on Systems, Signals and Image Processing, IWSSIP 2007
Mjesto i datum
Maribor, Slovenija, 27.06.2007. - 30.06.2007
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
fractal; heartbeat; long memory; principal components; power-law correlation; scale invariance; self-affine
Sažetak
It has been recognized that many biological systems exhibit complex behavior that is governed by fractal dynamical process. For revealing such dynamics we propose a method based on principal component analysis (PCA) of system’ s time series or some other measured and ordered data sequence, embedded in high-dimensional pseudo phase space. It is demonstrated that such mapping, together with projection of data vectors on the successive subspaces, reveals scale invariant statistics in the simple and clear fashion. To illustrate the method and to compare the results with others, such as detrended fluctuation analysis (DFA), we applied it on human heartbeat data series of different lengths and from various groups such as healthy young subjects and subjects with congestive heart failure (PhysioBank data library). Results show that the proposed method is appropriate for detection of fractal dynamics when analyzing limited scale intervals (dimensions) from smaller data sets.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
098-0982560-2566 - Mjerenje i karakterizacija podataka iz stvarnog svijeta (Medved-Rogina, Branka, MZOS ) ( CroRIS)
098-0982562-2567 - Metode znanstvene vizualizacije (Skala, Karolj, MZOS ) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb