Nonlinear Signal Processing Techniques Applied to EEG Measurements

2011 ◽  
pp. 324-338
Author(s):  
Christos L. Papadelis ◽  
Chrysoula Koutidou-Papadeli ◽  
Panagiotis D. Bamidis ◽  
Nicos Maglaveras
Keyword(s):  
Brain Activity ◽  
Approximate Entropy ◽  
Fluctuation Analysis ◽  
Linear Measurements ◽  
Nonlinear Signal Processing ◽  
Hypoxic Conditions ◽  
Eeg Data ◽  
Nitrogen Mixture ◽  
Nonlinear Signal ◽  
Processing Techniques

The electrical activity of the brain is sensitive to its oxygen supply, and electroencephalography (EEG) has been proposed as a suitable measurement to detect brain activity alterations induced by hypoxia. Since, linear processing techniques that have been used so far in hypoxia studies are based on false linearity assumptions about the generation of the EEG signal, there is a definite need for nonlinear approaches to be applied on EEG data derived from hypoxic conditions. The aim of the present study is to compare nonlinear techniques’ effectiveness to identify significant variations in EEG due to hypoxia. EEG data from two channels were derived from ten healthy subjects participated in the present study. Oxygen and nitrogen mixture was used to simulate hypoxic conditions that correspond to an altitude of 25.000 feet. Non-linear measurements such as correlation dimension, approximate entropy, Lyapunov exponent and detrended fluctuation analysis (DFA) parameters were estimated for EEG signals. The results of the present study confirm the effectiveness of nonlinear techniques to identify significant variations in EEG, which reflect alterations in cerebral function induced by cerebral hypoxic conditions.

scholarly journals Detection of Burst Suppression Patterns in EEG Using Recurrence Rate

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Zhenhu Liang ◽  
Yinghua Wang ◽  
Yongshao Ren ◽  
Duan Li ◽  
Logan Voss ◽  
...  
Keyword(s):  
Recurrence Rate ◽  
Brain Activity ◽  
Approximate Entropy ◽  
Energy Operator ◽  
Burst Suppression ◽  
Multiple Comparison ◽  
Eeg Data ◽  
Electroencephalogram Eeg ◽  
Nonlinear Energy ◽  
Selection Of

Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and multiple comparison tests showed that the RR could detect BSP and that it was superior to other measures with the highest sensitivity of suppression detection (96.49%, P=0.03). Tracking BSP patterns is essential for clinical monitoring in critically ill and anesthetized patients. The purposed RR may provide an effective burst suppression detector for developing new patient monitoring systems.

scholarly journals Fractal Methods and Power Spectral Density as Means to Explore EEG Patterns in Patients Undertaking Mental Tasks

2021 ◽  
Vol 5 (4) ◽  
pp. 225
Author(s):  
Carlos Alberto Valentim ◽  
Claudio Marcio Cassela Inacio ◽  
Sergio Adriani David
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Brain Activity ◽  
Time Domain Analysis ◽  
Relevant Information ◽  
Fluctuation Analysis ◽  
Power Spectral ◽  
Eeg Data ◽  
Electroencephalogram Eeg ◽  
Mental Tasks

Brain electrical activity recorded as electroencephalogram data provides relevant information that can contribute to a better understanding of pathologies and human behaviour. This study explores extant electroencephalogram (EEG) signals in search of patterns that could differentiate subjects undertaking mental tasks and reveals insights on said data. We estimated the power spectral density of the signals and found that the subjects showed stronger gamma brain waves during activity while presenting alpha waves at rest. We also found that subjects who performed better in those tasks seemed to present less power density in high-frequency ranges, which could imply decreased brain activity during tasks. In a time-domain analysis, we used Hall–Wood and Robust–Genton estimators along with the Hurst exponent by means of a detrented fluctuation analysis and found that the first two fractal measures are capable of better differentiating signals between the rest and activity datasets. The statistical results indicated that the brain region corresponding to Fp channels might be more suitable for analysing EEG data from patients conducting arithmetic tasks. In summary, both frequency- and time-based methods employed in the study provided useful insights and should be preferably used together in EEG analysis.

scholarly journals The right thalamus may play an important role in anesthesia-awakening regulation in frogs

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4516 ◽  
Author(s):  
Yanzhu Fan ◽  
Xizi Yue ◽  
Fei Xue ◽  
Steven E. Brauth ◽  
Yezhong Tang ◽  
...  
Keyword(s):  
General Anesthesia ◽  
South African ◽  
Brain Activity ◽  
Approximate Entropy ◽  
Permutation Entropy ◽  
Amphibian Species ◽  
The Awakening ◽  
Eeg Data ◽  
The Right

BackgroundPrevious studies have shown that the mammalian thalamus is a key structure for anesthesia-induced unconsciousness and anesthesia-awakening regulation. However, both the dynamic characteristics and probable lateralization of thalamic functioning during anesthesia-awakening regulation are not fully understood, and little is known of the evolutionary basis of the role of the thalamus in anesthesia-awakening regulation.MethodsAn amphibian species, the South African clawed frog (Xenopus laevis) was used in the present study. The frogs were immersed in triciane methanesulfonate (MS-222) for general anesthesia. Electroencephalogram (EEG) signals were recorded continuously from both sides of the telencephalon, diencephalon (thalamus) and mesencephalon during the pre-anesthesia stage, administration stage, recovery stage and post-anesthesia stage. EEG data was analyzed including calculation of approximate entropy (ApEn) and permutation entropy (PE).ResultsBoth ApEn and PE values differed significantly between anesthesia stages, with the highest values occurring during the awakening period and the lowest values during the anesthesia period. There was a significant correlation between the stage durations and ApEn or PE values during anesthesia-awakening cycle primarily for the right diencephalon (right thalamus). ApEn and PE values for females were significantly higher than those for males.DiscussionApEn and PE measurements are suitable for estimating depth of anesthesia and complexity of amphibian brain activity. The right thalamus appears physiologically positioned to play an important role in anesthesia-awakening regulation in frogs indicating an early evolutionary origin of the role of the thalamus in arousal and consciousness in land vertebrates. Sex differences exist in the neural regulation of general anesthesia in frogs.

scholarly journals Spectral Analysis of Electroencephalographic Data in Serious Games

2021 ◽  
Vol 11 (6) ◽  
pp. 2480
Author(s):  
Branko Babusiak ◽  
Marian Hostovecky ◽  
Maros Smondrk ◽  
Ladislav Huraj
Keyword(s):  
Serious Games ◽  
Brain Activity ◽  
Logic Gates ◽  
Logical Thinking ◽  
Mental Task ◽  
Basic Logic ◽  
Eeg Activity ◽  
Eeg Data ◽  
Processing Techniques ◽  
Signal Processing Techniques

In this paper, we describe an investigation of brain activity while playing a serious game (SG). A SG is focused on improving logical thinking, specifically on cognitive training of students in the field of basic logic gates, and we summarize SG description, design, and development. A method based on various signal processing techniques for evaluating electroencephalographic (EEG) data was implemented in the MATLAB. This assessment was based on the analysis of the spectrogram of particular brain activity. Changes in brain activity power at a characteristic frequency band during the gameplay were calculated from the spectrogram. The EEG of 21 respondents was measured. Based on the results, the respondents can be divided into three groups according to specific EEG activity changes during the gameplay compared to a relaxed state. The beta/alpha ratio, an indicator of brain employment to a mental task, was increased during gameplay in 18 of the 21 subjects. Our results reflected the sex of respondents, time of the game and the indicator, and whether the game was successfully completed.

scholarly journals Regularized two-step brain activity reconstruction from spatiotemporal EEG data

2004 ◽  
Author(s):  
Teodor I. Alecu ◽  
Sviatoslav Voloshynovskiy ◽  
Thierry Pun
Keyword(s):  
Brain Activity ◽  
Eeg Data
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