Szczegóły publikacji
Opis bibliograficzny
Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination / A. BRONIEC // Medical & Biological Engineering & Computing : Journal of the International Federation for Medical & Biological Engineering ; ISSN 0140-0118. — 2016 — vol. 54 iss. 12, s. 1935–1947. — Bibliogr. s. 1945–1947, Abstr. — Publikacja dostępna online od: 2016-04-08
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 103104 |
|---|---|
| Data dodania do BaDAP | 2017-01-11 |
| Tekst źródłowy | URL |
| DOI | 10.1007/s11517-016-1491-z |
| Rok publikacji | 2016 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Medical & Biological Engineering & Computing |
Abstract
Flicker-noise spectroscopy (FNS) is a general phenomenological approach to analyzing dynamics of complex nonlinear systems by extracting information contained in chaotic signals. The main idea of FNS is to describe an information hidden in correlation links, which are present in the chaotic component of the signal, by a set of parameters. In the paper, FNS is used for the analysis of electroencephalography signal related to the hand movement imagination. The signal has been parametrized in accordance with the FNS method, and significant changes in the FNS parameters have been observed, at the time when the subject imagines the movement. For the right-hand movement imagination, abrupt changes (visible as a peak) of the parameters, calculated for the data recorded from the left hemisphere, appear at the time corresponding to the initial moment of the imagination. In contrary, for the left-hand movement imagination, the meaningful changes in the parameters are observed for the data recorded from the right hemisphere. As the motor cortex is activated mainly contralaterally to the hand, the analysis of the FNS parameters allows to distinguish between the imagination of the right- and left-hand movement. This opens its potential application in the brain–computer interface.
