prikaz prve stranice dokumenta Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
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Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
Computers in biology and medicine, 80 (2017); 1-13. https://doi.org/10.1016/j.compbiomed.2016.11.002
Lerga, Jonatan; Saulig, Nicoletta; Mozetič, Vladimir

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Lerga, J., Saulig, N. i Mozetič, V. (2017). Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis. Computers in biology and medicine, 80., 1-13. doi: 10.1016/j.compbiomed.2016.11.002

Lerga, Jonatan, et al. "Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis." Computers in biology and medicine, vol. 80, 2017, str. 1-13. https://doi.org/10.1016/j.compbiomed.2016.11.002

Lerga, Jonatan, Nicoletta Saulig i Vladimir Mozetič. "Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis." Computers in biology and medicine 80 (2017): 1-13. https://doi.org/10.1016/j.compbiomed.2016.11.002

Lerga, J., Saulig, N. i Mozetič, V. (2017) 'Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis', Computers in biology and medicine, 80, str. 1-13. doi: 10.1016/j.compbiomed.2016.11.002

Lerga J, Saulig N, Mozetič V. Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis. Computers in biology and medicine [Internet]. 2017. [pristupljeno 03.12.2024.];80:1-13. doi: 10.1016/j.compbiomed.2016.11.002

J. Lerga, N. Saulig i V. Mozetič, "Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis", Computers in biology and medicine, vol. 80, str. 1-13, 2017. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:184:782424. [Citirano: 03.12.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:184:782424
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Podaci o radu
Naslov (engleski)Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
AutorJonatan Lerga
MBZ: 298775
AutorNicoletta Saulig
MBZ: 314984
AutorVladimir Mozetič
Autorova ustanovaSveučilište u Rijeci
Medicinski fakultet
(Katedra za socijalnu medicinu i epidemiologiju)
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Računarstvo
Sažetak (engleski)
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its time-frequency distribution (TFD) has been proposed in this paper. The algorithm utilizes the modification of the Rényi entropy-based technique for number of components estimation, called short-term Rényi entropy (STRE), and upgraded by an iterative algorithm which was shown to enhance existing approaches. Combined with instantaneous frequency (IF) estimation, the proposed method was applied to EEG signal analysis both in noise-free and noisy environments for limb movements EEG signals, and was shown to be an efficient technique providing spectral description of brain activities at each electrode location up to moderate additive noise levels. Furthermore, the obtained information concerning the number of EEG signal components and their IFs show potentials to enhance diagnostics and treatment of neurological disorders for patients with motor control illnesses.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeZavršna verzija rukopisa prihvaćena za objavljivanje (postprint)
Naslov časopisaComputers in biology and medicine
Brojčani podacivol. 80, str. 1-13
p-ISSN0010-4825
DOIhttps://doi.org/10.1016/j.compbiomed.2016.11.002
URN:NBNurn:nbn:hr:184:782424
Datum objave publikacije2017
URL dokumentahttp://bib.irb.hr/849306
Vrsta resursaTekst
Prava pristupaInstitucijski pristup
Uvjeti korištenjaIkona licence Zaštićeno autorskim pravom.
Datum i vrijeme pohrane2022-02-04 10:52:41