Pregled bibliografske jedinice broj: 723329
Evaluation and Extraction of Mismatch Negativity through Independent Component Analysis and Wavelet Decomposition
Evaluation and Extraction of Mismatch Negativity through Independent Component Analysis and Wavelet Decomposition // 6th European Conference of the International Federation for Medical and Biological Engineering / Lacković, Igor ; Vasić, Darko (ur.).
Dubrovnik: Springer, 2014. str. 94-97 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 723329 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Evaluation and Extraction of Mismatch Negativity through Independent Component Analysis and Wavelet Decomposition
Autori
Paprika, Marina ; Friganović, Krešimir ; Cifrek, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
6th European Conference of the International Federation for Medical and Biological Engineering
/ Lacković, Igor ; Vasić, Darko - Dubrovnik : Springer, 2014, 94-97
Skup
6th European Conference of the International Federation for Medical and Biological Engineering (MBEC2014)
Mjesto i datum
Dubrovnik, Hrvatska, 07.09.2014. - 11.09.2014
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
mismatch negativity ; wavelet decomposition ; independent component analysis
Sažetak
Mismatch negativity (MMN) is an event- related potential (ERP) which reflects the detection of a mismatch between the incoming deviant stimulus and the memory representation of the preceding standard stimuli. In this study MMN is elicited by the conventional oddball paradigm, so we focused on comparing procedures for extracting MMN and compared conventional difference wave (DW), Wavelet decomposition and independent component analysis (ICA) decomposition procedures. The main aim of this research is to extract and remove other evoked components (N1, P1) in order to eliminate their influence on MMN, since it can be overlapping. Wavelet decomposition of the grand averaged signal extracts components that do not contain information about MMN, but whose removal get clearly defined MMN. It has been shown that MMN extracted by ICA decomposition of standard and deviant stimuli, compared with DW, does not differ in latency for each participant.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
207-0000000-2293 - Funkcionalni verbotonalni dijagnostički program za djecu oštećena sluha i govora (Runjić, Nađa, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Poliklinika SUVAG