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Journal Article

Frequency spectrum recurrence analysis


Ladeira,  Guênia
External Organizations;


Marwan,  Norbert
Potsdam Institute for Climate Impact Research;

Destro-Filho,  João-Batista
External Organizations;

Davi Ramos,  Camila
External Organizations;

Lima,  Gabriela
External Organizations;

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Ladeira, G., Marwan, N., Destro-Filho, J.-B., Davi Ramos, C., Lima, G. (2020): Frequency spectrum recurrence analysis. - Scientific Reports, 10, 21241.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_24968
In this paper, we present the new frequency spectrum recurrence analysis technique by means of electro-encephalon signals (EES) analyses. The technique is suitable for time series analysis with noise and disturbances. EES were collected, and alpha waves of the occipital region were analysed by comparing the signals from participants in two states, eyes open and eyes closed. Firstly, EES were characterized and analysed by means of techniques already known to compare with the results of the innovative technique that we present here. We verified that, standard recurrence quantification analysis by means of EES time series cannot statistically distinguish the two states. However, the new frequency spectrum recurrence quantification exhibit quantitatively whether the participants have their eyes open or closed. In sequence, new quantifiers are created for analysing the recurrence concentration on frequency bands. These analyses show that EES with similar frequency spectrum have different recurrence levels revealing different behaviours of the nervous system. The technique can be used to deepen the study on depression, stress, concentration level and other neurological issues and also can be used in any complex system.