Nonlinear analysis of scalp EEGs from normal and brain tumour subjects.

Autor:	Selvam V S; Department of Electronics and Communication Engineering, College of Engineering, Guindy, Anna University, Chennai, 600 025, Tamil Nadu, India., Devi S S; Department of Electronics and Communication Engineering, College of Engineering, Guindy, Anna University, Chennai, 600 025, Tamil Nadu, India.
Jazyk:	angličtina
Zdroj:	Biomedizinische Technik. Biomedical engineering [Biomed Tech (Berl)] 2020 Nov 30; Vol. 66 (2), pp. 115-123. Date of Electronic Publication: 2020 Nov 30 (Print Publication: 2021).
DOI:	10.1515/bmt-2020-0035
Abstrakt:	Measurement of features from the chaos theory or as popularly known, the concept of nonlinear dynamics, as indicatives of several pathological conditions and cognition states using the electroencephalography (EEG) signal is very popular. In this paper, the analysis of scalp EEG signals of normal subjects and brain tumour patients using the nonlinear dynamic features has been presented. The nonlinear dynamic features that represent the dimensional and waveform complexities of the signal being analyzed have been considered. The statistical analysis of the selected nonlinear dynamic features has been presented. The results show that the nonlinear dynamic features significantly discriminate the brain tumour group from the normal group. (© 2020 Walter de Gruyter GmbH, Berlin/Boston.)
Databáze:	MEDLINE
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