Naslov
Number of EEG Signal Components Estimated Using the Short-Term Renyi Entropy

Autori
Lerga, Jonatan ; Saulig, Nicoletta ; Mozetič, Vladimir ; Lerga, Rebeka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 1st International Multidisciplinary Conference on Computer and Energy Science SpliTech 2016 / - Split, 2016, 1-6

ISBN
978-953-290-060-6

Skup
1st International Multidisciplinary Conference on Computer and Energy Science SpliTech 2016

Mjesto i datum
Split, Hrvatska, 13.07.2016. - 15.07.2016

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Short-term R´enyi entropy ; Multi-component signals ; Time-frequency signal analysis

Sažetak
Multichannel electroencephalogram (EEG) signals are known to be highly non-stationary and often multicomponent. A new method for its complexity, in terms of number of signal components extracted from its time-frequency distributions, has been proposed in this paper. Exploiting its spectral energy variation with time, the joint time-frequency distribution approach was upgraded by the modification of Rényi entropy, called short-term Rényi entropy, and applied to multichannel EEG signal analysis resulting in novel algorithm for its complexity detection. Number of EEG signals components obtained for various EEG signals was shown to provide useful information concerning brain activity at each electrode location, which may further be used to detect the brain activity abnormalities for patients with limb movement difficulties.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA