Coherence Analysis Of EEG Signal Using Power Spectral Density

Mrs. Sukhada A. Unde Department of Instrumentation,

Cummins College of Engineering for Women,

Karve Nagar,Pune, India. sukhadak23@gmail.com

Miss.Revati Shriram Department of Instrumentation,

Cummins College of Engineering for Women,

Karve Nagar,Pune, India revatishriram@yahoo.com

AbstractCoherence analysis can be detect for coordination of EEG rhythms between brain areas. It could not reflect the dynamic properties changing with time. Coherence analysis is a method developed on base of classic coherence analysis and signals joint time-frequency representations in recent years. It was used to extract transient characteristics of interactions among brain areas. It describes the temporal, spatial and frequency relationships of brain activities. This paper discuss the frequency-varying coherence of EEG (Electroencephalogram) to study the coordination mechanism of brain. The power spectral density is the frequency-varying method to study the coordination mechanism of brain areas. The Welch method and the periodogram method are the two methods to study the power spectral density. The results showed that appropriate methods were effective tools for EEG to study the coordination between brain areas.

Keywords- Electroencephalogram(EEG), Coherence, Power spectral density(PSD), Synchronization.

I. INTRODUCTION

Brain electric signals recorded from the scalp have been proved to correspond with the activity of neural network constructed by numerous neurons under cerebral cortex. It can help neuroscientists to explore the functional partition of cerebral cortex and the neuron cooperation mechanism between different cerebral areas, which had become one of the major concerns in neuroscience. The electroencephalogram (EEG) is a biological electric activity generated by a large number of neurons, that is, it is a kind of brain rhythm produced by numerous brain cells when they are depolarized simultaneously.[4] This property indicates the brain rhythms result from cooperation of large amount of neurons by synchronization. Hence the researchers can use the synchronization of EEG to study the co-operation mechanism of neural network and reveal brains temporal and also, spatial characteristics during the cognitive task. The coherence analysis is a kind of study based on spectrum analysis, which can be describe the synchronization of the brain electric activities of different frequencies between brain areas. But the non stationary of EEG data made the classic coherence analysis not able to explore the dynamical properties of the brain rhythms. Hence, on the basis of classic coherence analysis and

signals time-frequency representations, frequency-varying coherence method has been developed and applied to certain cognitive task.[7]

In this paper we discuss about the power spectral density which use to check the synchronization among the brain areas. PSD describes how the power of a signal or time series is distributed with the frequency.

II. SYSTEM FLOW CHART

Fig 1. gives the system flow chart.The flow of the system is as follows,

A. 10-20 Placement Of Electrodes

The 10-20 system or International 1020 placement of electrodes system is an internationally recognized method to describe and to apply location of scalp electrodes in the context of an EEG test or experiment. This method was developed to ensure standardized reproducibility so, subject's studies could be compared over time and subjects could be compared to each other. This system is based on the relationship between the location of an electrode and the underlying area of the cerebral cortex. The "10" and "20" refer to the actual distances between adjacent electrodes are either 10% or 20% of the total frontback or rightleft distance of the skull. Here EEG is capture using the 10-20 electrode placement system.[6]

B. EEG File

EEG file (.EEG File) is file in which different channels waveform are measured using 10-20 electrode placement system. The EEG files are having either 16 channel waveform or 32 channel waveform.The .EEG File is extantion of EEG taken by EEG amplifier NeuroScan

C. Read in Matlab

The .EEG file cannot read directly in matlab for that purpose Version 4.2.7 software is use in which EEG file is export to excel file and then excel file is differentiated into text document. The text document is then read in the matlab.

D. Power Spectral Density

Power spectral density, describes how the power of signal or time series is distributed with frequency. Power

2014 Fourth International Conference on Communication Systems and Network Technologies

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2014 Fourth International Conference on Communication Systems and Network Technologies

978-1-4799-3070-8/14 $31.00 2014 IEEEDOI 10.1109/CSNT.2014.181

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spectral density function shows the strength of the variations as a function of frequency. [5]That is, it shows that at which frequencies variations are strong and at which frequencies variations are weak. The unit of PSD is energy per frequency and you can obtain energy within a specific frequency range by integrating PSD within that frequency range. Figure 1. System Flow Chart

E. Welch Method

The power spectral density of the input signal vector using Welch's averaged modified method of spectral estimation. The power spectral density is calculated in units of power per radians per sample.

F. Periodogram Method

The power spectral density estimate the input signal of the sequence using a periodogram. The power spectral density is calculated in units of power per radians per sample. The corresponding vector of frequencies is computed in radians per sample, and has the same length as a input signal.

G. Coherence Estimation

The coherence analysis is a kind of study based on spectrum analysis, which can be describe the synchronization of brain electric activities of different frequencies between brain areas.[1] But the non stationary of EEG data made the classic coherence analysis not able to explore the dynamical properties of the brain rhythms. Hence, on the basis of classic coherence analysis and signals time-frequency representations, time-varying coherence methods had been developed and applied to certain cognitive tasks or pathology and healing researches.

H. Coherent / Non-coherent

When the phase difference and amplitude ratio between two signals remain unchanged, the coefficient equals 1, that is, two signals are more coherent, otherwise trends to 0, that is, two signals are non coherent. [3]Means, when two area of brain are more synchronous to each other the result is nearer to 1 that is, they are more coherent to each other, otherwise non coherent means nearer to 0.

III. MATERIALS AND METHODS

A. Subjects

All subjects are right handed according to a self-report, and free from neurological or psychiatric illness. All had normal or corrected to normal visual acuity, and normal color vision. Subjects were seated inside a dimly lit room at the distance of approximately 100 cm from the screen.

B. EEG recording

EEG activity was continuously recorded from scalp using EEG amplifier NeuroScan with a 16-channel electrode. All electrodes were referenced to linked electrode placed on the left and right hemispheres. Electro-oculogram (EOG) activity was recorded from four electrodes and used as a guide to removal of eye movement artifacts and blinks.

C. Power Spectral Density

Power spectral density (PSD), describes how to the power of a signal or time series is distributed with frequency. Since signal with nonzero average power is not square integrable, the Fourier transforms do not exist in this case. The PSD is the Fourier transform of the autocorrelation function of the signal. The power of a signal in a given frequency band can calculated by integrating over positive and negative frequencies. The definition of power spectral density generalizes in a straight manner to finite time series with 1nN,such as signal sampled at discrete times xn = x(nt) for a total measurement period T = Nt.

(1) Equation (1), gives the equation for both methods.In a

real-world application, one would typically average the single-measurement PSD on several repetitions of the measurement to obtain more accurate estimate of theoretical PSD of physical process underlying the individual measurements.[5] This computed PSD sometimes called periodogram. One can prove that the periodogram converges to the true PSD when averaging time interval T goes to infinity to approach the Power Spectral Density.

10-20 Placement Of Electrodes

EEG File

Read In Matlab

Power Spectral Density

Coherence Estimation

Result-Coherent / Non-coherent

Welch Method Periodogram Method

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D. Coherence Analysis

The coherence analysis is a kind of study based on spectrum analysis, which can be describe the synchronization of brain electric activities of different frequencies between brain areas. The coherence analysis is based on the power spectrum estimation.[2] The coherence between two signals x(t) and y(t) is a real-valued function that is defined as, magnitude squared value of the cross-power spectrum divided by the product of power of the spectra of both signals are completely correlated. Equation (2) is a equitation for analysis of coherence of EEG signals.

(2) Where, Gxy - Cross-spectral density between x and y, Gxx - Auto spectral density of x, Gyy - Auto spectral density of y.

IV. RESULT

A. Using Welch Method

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Channel C4-P4

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Channel F4 -C4

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PSD by pwelch of channel C4-P4

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PSD by pwelch of channel F4-C4

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Coherence between PSD by pwelch of channels C4-P4 and F4-C4

Figure 2. PSD by pwelch of channel C4-P4 and F4-C4, Coherence between PSD by welch of channel C4-P4 and F4-C4.

Fig 2 is gives the channel C4-P4 and channel F4-C4, PSD by welch method of channel C4-P4 and channel F4-C4 and Coherence between PSD by welch of channel C4-P4 and F4-C4. The channel C4-P4 and channel F4-C4 are used to check the feature extraction method, power spectral density using welch method. The average value of PSD by welch method of channel C4-P4 is 169.5701. The average value of PSD by welch method of channel F4-C4 is 157.7733. Also, the coherence is find out between PSD using welch method of channel C4-P4 and channel F4-C4. The average

value of the coherence between PSD by welch method of channel C4-P4 and channel F4-C4 is 0.9478..

B. Using Periodogram Method The channel C4-P4 and channel F4-C4 are used to check

the feature extraction method, power spectral density using periodogram method. The average value of PSD by periodogram method of channel C4-P4 is 178.0053. The average value of PSD by periodogram method of channel F4-C4 is 172.4291. Also, the coherence is find out between PSD using periodogram method of channel C4-P4 and channel F4-C4. The average value of the coherence between PSD by periodogram method of channel C4-P4 and channel F4-C4 is 0.9375. Fig 3 is gives the channel C4-P4 and channel F4-C4, PSD by Welch method of channel C4-P4 and channel F4-C4 and Coherence between PSD by periodogram of channel C4-P4 and F4-C4.

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Channel C4-P4

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Channel F4 -C4

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x 104 PSD by periodogram of channel C4-P4

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PSD by periodogram of channel F4-C4

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Coherence between PSD by periodogram of channels C4-P4 and F4-C4

Figure 3. PSD by periodogram of channel C4-P4 and F4-C4, Coherence between PSD by periodogram of channel C4-P4 and F4-C4.

C. Accuracy

For power spectral density of signal channel C4-P4 using Welchs averaged, the window is deside a bartlett window with 1000 length with overlapping 300 and nfft 600, the average value of PSD is 169.5701. The PSD estimate computed using the modified periodogram method, the window is desided a bartlett window with 2560 length and nfft as 600. Here signal of channel C4-P4 is used and the average value of PSD is 178.0053. From which both methods are gives nearly same result, that is both methods are more accurate methods for calculating the PSD for channel C4-P4.

For power spectral density of signal channel F4-C4 using Welchs averaged,the window is deside a Bartlett window with 1000 length with overlapping 300 and nfft 600. The average value of PSD is 157.7733.The PSD estimate computed using the modified periodogram method, the window is desided a bartlett window with 2560 length and nfft as 600. Here signal of channel F4-C4 is used and

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the average value of PSD is 172.4291. From which both methods are gives nearly same result, that is both methods are more accurate methods for calculating the PSD for channel F4-C4.

V. CONCLUSION

PSD can be calculate using by welch and periodogram and are more sincronus to each other. The coherence of welch between channel C4-P4 and channel F4-C4 and the coherence of periodogram channel C4-P4 and channel F4-C4 are more coherent to each other. The average value of the coherence between PSD by welch method of channel C4-P4 and channel F4-C4 is 0.9478 and the average value of the coherence between PSD by periodogram method of channel C4-P4 and channel F4-C4 is 0.9375, that is nearer to 1 means these areas are more synchronous to each other. EEG coherence analysis, an important tool for studying high-level processes, enables us to examine the intermediate sub-processes of interaction among different topographic areas and thus gives insights into the investigation of the functional networks cooperation during various processes.

Acknowledgment This work is supported by Prof. A.D.Gaikwad, HOD of

Instrumentation and control Department, CCOEW, Pune and Dr. Khambete, Principal, CCOEW, Pune. Last but not the least we would like to express our gratitude Dr.Shirbhate, Amravati for his full co-operation.

References

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[2] Xiaotong Wen, Kai Yin, Dongzhi Sun, Li Yao1, Xiaojie Zhao, ``Application of Time-varying Coherence to Coordinative Connectivity Based on Event Related EEG''.{IEEE} 2007.

[3] Xiaofeng Liu, Huan Qi, SupinWang, MingxiWan''Wavelet-based estimation of EEG coherence during Chinese Stroop task''Computers in Biology and Medicine 36 (2006).

[4] A book by Steven Pinker''How the Mind Works''. [5] Bahar Guntekin , Erol BasarA new interpretation of P300 responses

upon analysis of coherences(2010)..

[6] Valer Jurcak, Daisuke Tsuzuki, and Ippeita Dan''10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems.''(2007)

[7] Robert W. Thatcher, Ph.D., Carl J. Biver, Ph.D. and Duane M. North, MA.''EEG and Brain Connectivity: A Tutorial''2009.

[8] X. Wen, X. Zhao, and L. Yao, Time-Frequency analysis of EEG based on event related cognitive task, Lecture Notes in Computer Science, vol. 3973 , 2006, pp. 579- 585.

[9] C. Andrew, and G. Pfurtscheller, Event-related coherence as a tool for studying dynamic interaction of brain regions, Electroencephalography and clinical Neurophysiology, vol. 98, 1996, pp. 144-148.

[10] B. Schack, G. Grieszbach, H. Nowak, and W. Krause, The sensitivity of instantaneous coherence for considering elementary comparison processing. Part II: similarities and differences between EEG and MEG coherences, International Journal of Psychophysiology, vol. 31, 1999, pp. 241-259.

[1]. [2]. [3]. [4]. [5]. [6]. [7].

B. Schack, G. Seide, W. awe, F. Heinrich, U. Krause ``Coherence Analysis Of The Ongoing EEG By Means Of

Microstates Of Synchronous Oscillations'',IEEE(2001). Xiaotong Wen, Kai Yin, Dongzhi Sun, Li Yao1, Xiaojie

Zhao, ``Application of Time-varying Coherence to Coordinative Connectivity Based on Event Related

EEG''.{IEEE} 2007. Xiaofeng Liu, Huan Qi, SupinWang, MingxiWan''Wavelet-based estimation of EEG coherence during Chinese Stroop

task''Computers in Biology and Medicine 36 (2006).

A book by Steven Pinker''How the Mind Works''. Valer Jurcak, Daisuke Tsuzuki, and Ippeita Dan''10/20,

10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems.''(2007)

Robert W. Thatcher, Ph.D., Carl J. Biver, Ph.D. and Duane M. North, MA.''EEG and Brain Connectivity: A

Tutorial''2009.

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