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The study was intended to analyze the effect of three types of music, namely Indian classical music, Bhajan (spiritual anthem) music and rock music, on the electroencephalogram (EEG) activity for two different age groups, viz. young subjects (23–27 years) and elder subjects (40–55 years). We recorded EEG in 10 healthy elder subjects and 10 healthy young subjects at eyes closed condition during without...
EEG contains immense information about the brain activity which cannot be understood completely by visual inspection. Powerful signal processing algorithms in EEG analysis can greatly assist the physicians and neurologists to extract such hidden information. It has been found that EEG being a time-varying and non-stationary signal, can be analyzed by non-linear methods. In this paper we tried to evaluate...
In this paper we try to evaluate the multifractality displayed by the EEG signals obtained from subjects with sleep apnea syndrome. The Multifractal Detrended Fluctuation Analysis (MF-DFA) shows that the EEG signals have different degree of multifractality and we suspected this variety is due to various stages of sleep. In an attempt to identify the origin of multifractality we extend our study and...
This article presents the results of the application of different measures of complexity based on nonlinear dynamics techniques, to evaluate the effect of a neurofeedback therapy in patients with Attention Deficit Hyperactivity Disorder (ADHD) utilizing electroencephalographic (EEG) registers as unique source of information. Every EEG register analyzed in this study contains 26 channels and was acquired...
Nonlinear dynamic properties in evoked potential (EP) with correlation dimension (CD) and the distribution of CDs of EPs on scalp are studied. EPs are recorded by averaging method. The CDs of EEG before and after stimulations (averaged) are calculated by Grass Berger and Procaccia method. The CDs of EP in multi-channel and their distribution are calculated. Results from this study show that the CD...
Manual acupuncture(MA), as a mechanical action, can be equivalent to an external stimulus to the neural system. To explore the effect of MA on brain activities, we design an experiment that acupuncture at Zusanli acupoint with four different frequencies to obtain electroencephalograph (EEG) signals. Neural system is a complex nonlinear dynamics system that possesses strong nonlinear characteristic,...
Magnetic stimulation is a non-invasive and almost painless technique and has been used to modulate nerve activities, treat disorders and maintain health, just like acupuncture. Acupuncture point (acupoint) is a specific point in human body with high sensitivity to acupuncture treatment. In this paper, magnetic stimulation was used to stimulate Neiguan (PC6) acupoint. 64-channel EEG signals in three...
The article emphasizes clinical significance and analysis of electroencephalogram (EEG) test with nonlinear analysis applied on patients with unilateral temporal lobe epilepsy (TLE). The entire epileptic onset of seizures in 22 patients with TLE were recorded with the synchronous 18-lead EEG. According to the shape of EEG waves and the corresponding symptoms of the clinic during their seizures, data...
This work aims at examining the influence of lorazepam, an anxiolytic drug with sedative effects, on brain activity and specifically on EEG Fractal Dimension (FD). The main objective is to clarify the reasons for FD increase after drug intake and to establish a relationship between FD and EEG energy bands. 14 healthy subjects that received either 2.5mg of lorazepam (verum case) or placebo (placebo...
The automated seizure detection in EEG is significant for epilepsy monitoring, diagnosis and rehabilitation. In this study, we evaluated the differences between epileptic EEG and normal EEG by computing some nonlinear features. Correlation Dimension (CD) and Approximate Entropy (ApEn) were calculated for one hundred segments of epileptic EEG and one hundred segments of normal EEG. A comparison is...
The use of both linear autoregressive model coefficients and nonlinear measures for classification of EEG signals recorded from healthy subjects and epilepsy patients is investigated. A total of seven nonlinear measures namely the approximate entropy, largest lyapunov exponent, correlation dimension, nonlinear prediction error, hurst exponent, third order autocovariance, asymmetry due to time reversal,...
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