bispectrum estimation of electroencephalogram signals during meditation
نویسندگان
چکیده
objective: electroencephalogram is a reliable reflection of many physiological factors modulating the brain. the bispectrum is very useful for analyzing non-gaussian signals such as eeg, and detecting the quadratic phase coupling between distinct frequency components in eeg signals.the main aim of this study was to test the existence of nonlinear phase coupling within the eeg signals in a certain psycho-physiological state meditation. methods: eleven meditators and four non-meditators were asked to do meditation by listening to the guidance of the master, and 10 subjects were asked to do meditation by themselves. bispectrum estimation was applied to analyze eeg signals, before and during meditation. eeg signals were recorded using 16-channel powerlab. anova test was used to establish significant changes in bispectrum parameters, during two different states (before and during meditation). results: mean bispectrum magnitude of each channel increased during meditation. these increments of phase coupling are more obvious in occipital region (pz channel) than frontal and central regions (fz and cz channels). besides that phase coupled harmonics are shifted to the higher frequencies during meditation. conclusion:bispectrum methods can be useful for distinction between two states (before and during meditation). declaration of interest: none. citation: goshvarpoura, goshvarpour a, rahati s, saadatian v.bispectrum estimation of electroencephalogram signals during meditation. iran j psychiatry behav sci 2012 6(1): 48-54.
منابع مشابه
Bispectrum Estimation of Electroencephalogram Signals During Meditation
OBJECTIVE Electroencephalogram is a reliable reflection of many physiological factors modulating the brain. The Bispectrum is very useful for analyzing non-Gaussian signals such as EEG, and detecting the quadratic phase coupling between distinct frequency components in EEG signals.The main aim of this study was to test the existence of nonlinear phase coupling within the EEG signals in a certai...
متن کاملA Unique Approach of Noise Elimination from Electroencephalography Signals between Normal and Meditation State
In this paper, unique approach is presented for the electroencephalography (EEG) signals analysis. This is based on Eigen values distribution of a matrix which is called as scaled Hankel matrix. This gives us a way to find out the number of Eigen values essential for noise reduction and extraction of signal in singular spectrum analysis. This paper gives us an approach to classify the EEG signa...
متن کاملDetection of schizophrenia patients using convolutional neural networks from brain effective connectivity maps of electroencephalogram signals
Background: Schizophrenia is a mental disorder that severely affects the perception and relations of individuals. Nowadays, this disease is diagnosed by psychiatrists based on psychiatric tests, which is highly dependent on their experience and knowledge. This study aimed to design a fully automated framework for the diagnosis of schizophrenia from electroencephalogram signals using advanced de...
متن کاملDetection of Fatigue from Electroencephalogram Signal During Neurofeedback Training
Timely diagnosis of fatigue helps to improve the quality and effectiveness of neurofeedback training. Neurofeedback training (NFT) is a method that can change brain activity by altering brain signal fluctuations and teaches individuals to produce or reproduce their brain activity patterns in order to improve performance. Neurofeedback training has been widely utilized over the recent years owi...
متن کاملEstimation of the cool executive function using frontal electroencephalogram signals in first-episode schizophrenia patients
BACKGROUND In schizophrenia, executive dysfunction is the most critical cognitive impairment, and is associated with abnormal neural activities, especially in the frontal lobes. Complexity estimation using electroencephalogram (EEG) recording based on nonlinear dynamics and task performance tests have been widely used to estimate executive dysfunction in schizophrenia. METHODS The present stu...
متن کاملUsing Invariant Translation to Denoise Electroencephalogram Signals
Problem statement: Because of the distance between the skull and the brain and their different resistivity’s, Electroencephalogram (EEG) recordings on a machine is usually mixed with the activities generated within the area called noise. EEG signals have been used to diagnose major brain diseases such as Epilepsy, narcolepsy and dementia. The presence of these noises however can result in misdi...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
iranian journal of psychiatry and behavioral sciencesجلد ۶، شماره ۲، صفحات ۴۸-۵۴
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023