TY  - JOUR
A1  - Ladeira, Guenia
A1  - Marwan, Norbert
A1  - Destro-Filho, Joao-Batista
A1  - Ramos, Camila Davi
A1  - Lima, Gabriela
T1  - Frequency spectrum recurrence analysis
JF  - Scientific reports
N2  - 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.
KW  - Biomedical engineering
KW  - Brain injuries
KW  - Computational models
KW  - Computational neuroscience
KW  - Data acquisition
KW  - Data processing
KW  - Electrical and electronic engineering
KW  - Neural circuits
KW  - Visual system
Y1  - 2020
U6  - https://doi.org/10.1038/s41598-020-77903-4
SN  - 2045-2322
VL  - 10
IS  - 1
PB  - Nature portfolio
CY  - Berlin
ER  -