KR20130129710A - Method for determining of emotion status by analysis of the brain function connectivity and system adopting the method - Google Patents

Abstract

Provided is a method for determining user feeling by analyzing brain function connection. The method for determining the user feeling comprises a step for providing a subject with stimulation to feel and calculating coherence by using electroencephalogram (EEG) signals for a plurality of measured points of the subject and a step for classifying the feeling of the subject by determining the brain function connection from the coherence.

Description

Method for determining of emotion status by analysis of the brain function connectivity and system adopting the method}

The present invention relates to a method for determining emotion using a brain function connectivity analysis and a system for applying the same, and more particularly, to a brain function connectivity analysis system using an electroencephalogram coherence.

Arousal and relaxation are important axes of dimensional emotion research. Physiological changes in response to arousal and relaxation are diverse [14]. In particular, recent studies have focused on changes in the central nervous system [3], [5], [8], and [9]. Comparison of alpha-2 (10.5 ~ 12Hz) of EEG after relaxation and arousal stimulation showed that it was active in the right frontal lobe when arousal [6]. A study of four classical sounds and measurement of EEG in the left and right frontal heads (F3, F4) and the left and right head (P3, P4) showed that EEG alpha waves were lower in the left hemisphere than in the right hemisphere. 11]). In most of these studies, the commonality tends to focus on the local area, for example, the response of the right frontal lobe.

But the brain has functional connectivity. This is because the information transmitted from the sensory neural tube is transferred to the sensory processing area of the cerebral cortex through the association area. The transmitted information is delivered along a unique path according to the type of information, and connectivity between brain regions occurs. Therefore, awakening and relaxation will respond according to functional connections. Some relevant studies are mentioned in this regard.

In a related study, arousal was categorized into three stages, followed by analysis of INTRA- and INTER-hemispheric coherences. As a result, the fronto-occipital and inter-frontal coherences were reduced in the alpha wave band during the awake state. Through this, the region corresponding to the alpha wave band of the fronto-frontal coherence was presented as an indicator of the arousal stage [2]. In the study, it was important that the prefrontal connectivity in the alpha wave band could be used as an indicator of arousal. However, the awakening and sleeping states were significant, so significant results were observed only in the frontal lobe of the alpha wave band. Therefore, it is not a general reaction of arousal and relaxation.

In another study, patients with Persistent Genital Arousal Disorder (PGAD) were treated with topiramate, an epileptic seizure inhibitor, and brain changes were observed. After the EEG / MEG and fMRI measurements, the functional connectivity was analyzed to confirm changes in left posterior insular gyrus, left middle frontal gyrus, left inferior and superior temporal gyrus and left inferior parietal lobe. This confirmed the functional connectivity mechanism of PGAD [1]. In the study, it is important to identify the functional connectivity mechanism between the frontal and temporal lobes during arousal. However, it is not a general emotional response because the analysis of the process of bringing non-normal sexually active patients into relaxation state through drug administration was analyzed.

Both studies have shown that common connectivity is an important physiological variable that changes during arousal. However, the emotional reactions caused by the sleep state or the drug were analyzed. Sleep states are generally close to relaxation, and drug response to patients with sexually transmitted disorders can be seen as a comparison between arousal and normal states. Therefore, further studies are needed to see the response to arousal and relaxation in steady state.

As described above, the brain has functional connectivity, and a system for analyzing such functional connectivity is required. However, studies related to brain function connectivity mainly use the method of analyzing measurement data after the experiment. Due to these research methods, research on brain functional connectivity is limited. Therefore, if brain functional connectivity can be analyzed in real time, it will be possible to induce various cognitive responses and observe brain functional connectivity immediately. It is expected that the cognitive response will be able to further identify the reactions occurring in the central nervous system.

Anzellotti, F., Franciotti, R., Bonanni, L., Tamburro, G., Perrucci, MG, Thomas, A., Pizzella, V., Romani, GL and Onofrj, M., "Persistent genital arousal disorder associated with functional hyperconnectivity of an epileptic focus ", Neuroscience, 167, 88-96, 2010.

Cantero, JL, Atienza, M., Salas, RM and G Mez, CM, "Alpha EEG coherence in different brain states: an electrophysiological index of the arousal level in human subjects", Neuroscience Letters, 271, 167-170, 1999.

Davidson, RJ, "What does the prefrontal cortex" do "in affect: perspectives on frontal EEG asymmetry research", Biological Psychology, 67, 219-234, 2004.

De Castelnau, P., Albaret, JM, Chaix, Y. and Zanone, PG, "A study of EEG coherence in DCD children during motor synchronization task", Human Movement Science, 27, 230-241, 2008.

Hall, EE, Ekkekakis, P. and Petruzzello, SJ, "Regional brain activity and strenuous exercise: Predicting affective responses using EEG asymmetry", Biological Psychology, 75, 194-200, 2007.

6. Isotani, T., Tanaka, H., Lehmann, D., Pascual-marqui, RD, Kochi, K., Saito, N., Yagyu, T., Kinoshita, T. and Sasada, K., "Source localization of EEG activity during hypnotically induced anxiety and relaxation ", International Journal of Psychophysiology 41, 143-153, 2001.

7.Kim, J.H., Whang, M.C., Kim, Y.J. and Woo, J.C., "The study on emotion recognition by time-dependent parameters of autonomic nervous response", Korean Journal of the Science of Emotion and Sensibility, 11 (4), 637-643, 2008.

8. Kim, JH, Whang, MC, Woo, JC, Kim, CJ, Kim, YJ, Kim. JH and Kim, DK, "A research on EEG coherence variation by relaxation", Korean Journal of the Science of Emotion and Sensibility, 13 (1), 121-128, 2010.

9. Passynkova, NR and Volf, NV, "Seasonal affective disorder: spatial organization of EEG power and coherence in the depressive state and in light-induced and summer remission", Psychiatry Research: Neuroimaging, 108, 169-185, 2001.

10. Petsche, H., "Approaches to verbal, visual and musical creativity by EEG coherence analysis", International Journal of Psychophysiology, 24, 145-159, 1996.

11. Schmidt, LA and Trainor, LJ, "Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions", Cognition & Emotion, 15 (4): p. 487-500, 2001.

12. Travis, F., Tecce, J., Arenander, A. and Wallace, RK, "Patterns of EEG coherence, power, and contingent negative variation characterize the integration of transcendental and waking states", Biological Psychology, 61, 293- 319, 2002.

13. Weiss, S. and Mueller, HM, "The contribution of EEG coherence to the investigation of language", Brain and Language, 85, 325-343, 2003.

14.Whang, M.C., Lim J.S., Kim, H.J. and Kim, S.Y., "Effect on Physiological Responses According to Different Arousals", Korean Journal of the Science of Emotion and Sensibility, 4 (2), 89-93, 2001.

The present invention provides a method for analyzing brain functional connectivity in real time using EEG and a system applying the same.

The present invention provides a method of performing cognitive analysis such as arousal / relaxation through brain functional connectivity analysis and a system applying the same.

Emotion determination method according to the present invention:

Calculating a coherence using an EEG signal for a plurality of measurement points of a subject obtained while presenting an emotional stimulus to the subject;

And classifying the emotional state of the subject by determining brain functional connectivity from the coherence.

Emotion determination system according to the present invention:

A stimulus source for presenting an emotional stimulus to a subject;

An EEG sensor detecting an EEG signal of a subject according to the emotional stimulation;

An analysis device for analyzing the EEG signal and determining arousal-relaxation according to the increase or decrease in connectivity between EEG measurement points; Respectively.

According to a specific embodiment of the present invention, the emotional stimulus may be an acoustic stimulus.

According to another specific embodiment of the present invention, the EEG signal may be detected in real time from a subject.

According to another specific embodiment of the present invention, when the connectivity is determined, the subject is awakened when the connectivity between the right frontal lobe and the right occipital lobe increases, and when the connectivity decreases, the subject is determined to be in a relaxed state.

1 is a view showing an EEG sensor attachment position to a subject.
2 is a flow chart illustrating brain functional connectivity analysis according to the present invention.
Figure 3 shows a graphical interface showing the analysis results of the emotion determination system using the brain functional connectivity analysis according to the present invention.
Figure 4 shows the result of the coherence change according to the emotional stimulation by the sound.
FIG. 5 shows connectivity that can be used as a marker for classifying arousal and relaxation among the analyzed results of FIG. 4.
6 is a schematic structural diagram of a system for performing an emotion determination method according to the present invention.

Hereinafter, with reference to the accompanying drawings, looks at an embodiment of the emotion determination method using the brain functional connectivity analysis according to the present invention and a system applying the same.

The present invention analyzes the brain functional connectivity that occurs upon arousal and relaxation induction in a steady state. In particular, we tried to elucidate the functional connectivity mechanism between the frontal and temporal lobes. Through this, the central nervous system mechanism in general emotional change is identified and presented as an indicator of emotional change of awakening-relaxation.

<Stimulation source>

Sound was used as a stimulus source for emotional stimulation. The sound used was summarized in Table 1, which used the non-emotional effect sound (NEsound, Non-Emotional effect sound) and the sound representing the effect (Esound, Emotional effect sound). The arousal effect on each sound received subjective response after the experiment (awakening: 1, relaxation: 7). As a result of subjective response analysis, arousal sound was NEsound (M = 5.16, SD = .21) and Esound (M = 4.53, SD = .25). Relaxation sound responded with NEsound (M = 5.25, SD = .18) and Esound (M = 5.74, SD = .16). Compared with arousal (M = 4.75, SD = .16) and relaxation (M = 4.39, SD = .18), the response result before the experiment was confirmed to have an emotional inducing effect. As the dependent variable, EEG was measured at 8 points as shown in FIG. 1 to measure the response of the central nervous system (10-20 method, F3, F4, T3, T4, P3, P4, O1, O2). The sampling rate of the EEG was 400 Hz.

Non-Emotional
effect sound Emotional
effect sound Arousal sound ANEsound AEsound Relaxation sound RNEsound REsound

<EEG Coherence Analysis Module>

In the case of coherence analysis, it is very useful for analyzing brain function connectivity because it is possible to know whether the connection between points has increased [3, 4]. This connectivity analysis can analyze in detail the brain activity that occurs during emotion induction [10, 12]. Coherence analyzed the EEG of two measurement points. In the system according to the present invention, the system is designed to analyze eight measurement points (F3, F4, T3, T4, P3, P4, O1, O2) as shown in FIG. However, the location of this measuring point can be changed according to the experimental purpose, and the analysis module was designed to adjust the number of measuring points.

Coherence expresses the degree of synchronization between two signals as a value between 0 and 1, and the closer to 1, the more connected two signals are. The measurement of coherence is shown in Equation 1.

In Equation 1, Rx (w) and Rx (w) are the spectral values of each of the two signals, and Rxy (w) is the cross-spectral value of the two signals. Spectral analysis was analyzed by the Fast Fourier Transform (FFT) method to apply the sliding window (sliding window). The FFT method used an auto power spectrum function. The slide size of the sliding window was 1600 (4 sec) samples, and the slide was 800 (2 sec) samples. FFT results were averaged at 2Hz intervals from 0Hz to 50Hz.

<Analysis method>

2 is a flow chart of the analysis method according to the present invention. The system applying this method receives an EEG from a Realtime EEG or a stored file using Biopac and performs analysis (21). When using real-time EEG as input, the subject is exposed to an emotional stimulus, for example an acoustic stimulus as described above, while wearing a biopack. The input EEG data is analyzed using the coherence analysis module (22) and then stored as a reference value (Reference) for analyzing the increase and decrease of the coherence (27). If the size of the stored reference value is greater than the specified value (24), the analysis is applied 25 by applying a coherence rule base (25) and the result is displayed on the display of the system (26). As shown in FIG. 3, analysis results of eight measurement points F3, F4, T3, T4, P3, P4, O1, and O2 are displayed, and connectivity between the measurement points is displayed on the lower side. At this time, the coherence can be displayed as a solid line when increasing and a dotted line when decreasing as compared with the stored reference value. The analysis results can be saved in the form of a plain text file, and later can be saved in the form of an XML file in consideration of extensibility.

<Perform task>

In the experiment of the present invention, 23 college students with an average age of 23.7 years participated. Subjects were instructed to sleep well the day before the experiment and drink intake was limited to prevent arousal effects caused by caffeine. The experiment began by giving the subjects a 10-minute break to adjust to their surroundings when they arrived at the test site and providing training on the experimental procedure. After rest, the EEG sensor was attached to the measuring point as shown in FIG. 1. The autonomic nervous system was attached to the left hand to allow subjective questionnaires (right hand for left-handed). The measurement test after attachment confirmed that the data was measured correctly. The measurement of the experimental data allowed the listening of the control sound and the experimental sound for 2 minutes and 30 seconds. After listening to one sound, I listened to another sound after one minute of rest. Listening order of sound was different for each subject.

<Sound effect comparison>

The results of EEG coherence analysis were divided into awakening (ANEsound, AEsound) and relaxation (RNEsound, REsound) stimuli. For statistical analysis, Spss was used to independently test the significance between RNEsound and REsound and between ANEsound and AEsound. As shown in Table 2, the value of significance less than 0.005 (marked with **) was defined as having a significant difference between the non-emotional effect sound and the emotional effect sound. In the spectrum, the spectrum band is divided into alpha (8-12 Hz), beta-1 (12-16 Hz), beta-2 (16-20 Hz), beta-3 (20-30 Hz), and gamma (30 Hz-50 Hz). Change was confirmed.

Compare Condition T-test Result Mean Difference sound Position Spectrum
(Hz) Non emotional
effectsound Emotional
effectsound Arousal F3-O1 24 ~ 26 t = -6.05, df = 6767, p = .000 *** 0.3160 0.3527 -0.0366 Arousal F3-O2 24 ~ 26 t = -5.07, df = 6767, p = .000 *** 0.5083 0.5326 -0.0244 Relaxation F3-F4 24 ~ 26 t = 5.76, df = 6767, p = .000 *** 0.2231 0.1982 0.0249 Relaxation F3-O2 24 ~ 26 t = 3.96, df = 6767., p = .000 *** 0.4626 0.4440 0.0186

<Result>

Based on the analysis results, the results with significant differences are shown in Figure 2. 4 shows the results of the coherence change according to the awakening sound effect, and the results of the bottom show the change according to the relaxation sound effect. The order of the coherence display bundles is indicated by alpha, beta-1, beta-2, beta-3, and gamma frequency bands from the left. As a result of the analysis, connectivity was increased in the right frontal lobe. However, in loose acoustic, the connectivity was decreased around the right frontal lobe and increased around the left frontal lobe. The pattern of increased connectivity toward the left frontal lobe was strong in the alpha wave and beta-2 bands.

5 is a result showing the connectivity that can be used as a marker for classifying awakening and relaxation among the analyzed results. FIG. 5 shows positions showing opposite results in the arousal-relaxation response. For example, the connectivity between the right frontal lobe and the right occipital lobe in the alpha-wave band decreases when arousing and increases pattern when relaxing. As shown in Figure 3, arousal connectivity in the right frontal-right occipital lobe was common in the alpha to gamma-wave bands during awakening, and in all bands except beta-3 in the right frontal-right parietal lobe. In addition, connectivity between the left and right frontal lobes, between the right and front temporal lobes, and between the left and right temporal lobes were observed in some frequency bands.

As described above, the present invention analyzed the central nervous system connectivity that occurs during arousal and relaxation in the normal state. Previous studies have only observed local responses to arousal or relaxation. However, the brain basically performs information processing through functional linkages, so it is difficult to explain the central nervous system's mechanism for emotional induction by analyzing only local linkages on emotional cognition. Recent studies have analyzed the brain functional connectivity from sleep to wake-up, or the brain functional connectivity by making drugs stable in patients with excitement disorders. However, these conventional methods measured the change of emotion in a special situation rather than a general state. Therefore, it is difficult to explain the mechanism of the central nervous system for the emotional changes that occur in general situations. Therefore, according to the present invention, it is possible to induce arousal and relaxation in general situations and analyze the connectivity of the central nervous system.

6 is a schematic diagram of an emotion determination system for performing an analysis method according to the present invention. Referring to FIG. 6, a number of EEG sensors 14 are attached to the head of the subject 20, which are connected to the analysis system 12. In addition, stimulators 11 and 11 which present an emotional stimulus to the subject are located in front of the subject 20, which are connected to and controlled by the analysis system 12. On the other hand, the display system 13 which displays the result of the analysis is connected to the analysis system 12. The analysis system 12 has a computer structure and may be a combination of one or more pieces of hardware. On the other hand, the EEG sensor 14 is part of the so-called biopack.

As described above, the acoustic stimulus, that is, the induction of arousal and relaxation, was used for the subject, and the stimulus was verified by the subjective questionnaire. The test subjects were 23 college students with an average age of 23.7 years. As described above, the positions of the EEG were attached to the frontal, temporal, parietal, and occcipital regions symmetrically (F3, F4, T3, T4, P3, P4, O1, O2). Coherence was used in the analysis of central nervous system connectivity, and as a result of the analysis, connectivity was increased during arousal and reversed in relaxation. The occipital lobe showed the opposite result. In particular, the connectivity was increased in the right frontal lobe, but in the loose acoustic, the connectivity was decreased in the right frontal lobe. In addition, we confirmed the connectivity that can be used as a marker to classify arousal and relaxation among the analyzed results. In awakening, increased connectivity between the right frontal lobe and right occipital lobe were common features from the alpha wave to gamma wave band. In addition, characteristic changes occurred in all bands except beta-3 in the right frontal lobe and right parietal lobe. This pattern is believed to be connected to the right frontal lobe, which is responsible for processing information on emotions, and to arouse the right parietal and right occipital lobes. Further studies on the activity of the right frontal lobe, right parietal lobe and right occipital lobe are needed. However, the present indicator of brain functional connectivity alone has high utility as a biomarker to classify certain arousal and relaxation.

On the other hand, although the acoustic stimulation was used in the above embodiment, according to another embodiment of the present invention, other forms of emotional stimulation may be used. For example, visual or image content using a display or lighting may be used as an emotional stimulus. That is, the present invention is not limited to the technical scope of the form of the stimulus, and any stimulus that can cause an emotional change, in particular, can change the subject's emotion to an awake or relaxed state.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the present invention. Therefore, the true scope of protection of the present invention should be defined only by the appended claims.

10: emotional judgment system
11: Stimulation source (acoustic stimulation)
12: analysis system
13: monitor
20: subject

Claims (7)

Calculating a coherence using an EEG signal for a plurality of measurement points of a subject obtained while presenting an emotional stimulus to the subject;
And classifying the emotional state of the subject by determining brain functional connectivity from the coherence. The method of claim 1,
The emotional stimulus is an emotional determination method, characterized in that the acoustic stimulation. The method of claim 1,
Detecting the EEG signal from a subject in real time; Emotion determination method further comprising. The method of claim 1,
In determining connectivity, when the connectivity between the right frontal lobe and the right occipital lobe increases, the subject is aroused, and when the connectivity decreases, it is determined that the patient is in a relaxed state. A stimulus source for presenting an emotional stimulus to a subject;
An EEG sensor detecting an EEG signal of a subject according to the emotional stimulation;
An analysis device for analyzing the EEG signal and determining arousal-relaxation according to the increase or decrease in connectivity between EEG measurement points; Emotion determination system having a. 6. The method of claim 5,
Wherein the stimulus source is an acoustic stimulus source. The method of claim 1,
And a display for displaying the connectivity between the measurement points obtained by said analysis device.

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