KR102239430B1 - Method and apparatus for determining emotion using interoception-related brainwave - Google Patents

Abstract

A method and apparatus for reading emotional stimulation using internal EEG according to various embodiments includes storing heart rate-induced EEG information in response to emotional stimulation, detecting heart rate-induced EEG information based on the detected EEG signal, and detecting heart rate-induced EEG. In response to the information, it may be configured to read an emotional stimulus.

Description

Emotional stimulation reading method and device using EEG for domestic use {METHOD AND APPARATUS FOR DETERMINING EMOTION USING INTEROCEPTION-RELATED BRAINWAVE}

Various embodiments relate to an electronic device and a method of operating the same, and more particularly, to a method and apparatus for reading emotional stimulation using internal brain waves.

As technologies capable of measuring brain activity are developed, research is being conducted to read the mental state of humans. In general, research is being conducted to read the mental state of humans based on brain activity according to visual stimuli. These findings are being used to identify or identify speech, based on the brain's response to visual stimuli.

However, according to the above research results, it is difficult to read emotional stimuli from brain activity. Therefore, a method of reading emotional stimuli based on brain activity is required.

According to various embodiments of the present disclosure, a method of reading emotional stimulation of an electronic device includes an operation of storing heartbeat evoked potential (HEP) information in response to the emotional stimulation, and based on the detected EEG signal, the heartbeat-induced EEG information is stored. The detection operation may include an operation of reading the emotional stimulus in response to the heartbeat-induced EEG information.

An electronic device according to various embodiments of the present disclosure is a device for reading emotional stimuli, and may include a memory and a processor connected to the memory. According to various embodiments, the processor stores heart rate-induced EEG information in the memory in response to emotional stimulation, detects the heart rate-induced EEG information based on the detected EEG signal, and determines the heart rate-induced EEG information. Correspondingly, it may be configured to read the emotional stimulus.

According to various embodiments, the electronic device may improve the reading performance of the emotional stimulus by using the heartbeat-induced brainwave information to read the emotional stimulus. Through this, accuracy and efficiency can be increased in precise diagnosis and determination of treatment progress for emotion-related psychiatric disorders such as depression, anxiety disorder, borderline personality disorder, and the like.

1 is a diagram illustrating an electronic device according to various embodiments.
2 is a diagram illustrating a method of operating an electronic device according to various embodiments.
3 is a diagram illustrating a database storage operation of FIG. 2.
FIG. 4 is a diagram for describing an operation of generating emotional stimulation of FIG. 3.
5 is a diagram illustrating an operation of detecting heartbeat-induced brainwave information of FIG. 3.
6, 7, 8, 9, and 10 are diagrams for explaining an operation of detecting heartbeat-induced EEG information of FIG. 2.
11 is a diagram illustrating an emotional stimulus reading operation of FIG. 2.
12 is a diagram for explaining an emotional stimulus reading operation of FIG. 2.

Hereinafter, various embodiments of the present document will be described with reference to the accompanying drawings.

Various embodiments of the present document and terms used therein are not intended to limit the technology described in this document to a specific embodiment, and should be understood to include various modifications, equivalents, and/or substitutes of the corresponding embodiment. In connection with the description of the drawings, similar reference numerals may be used for similar elements. Singular expressions may include plural expressions unless the context clearly indicates otherwise. In this document, expressions such as "A or B", "at least one of A and/or B", "A, B or C" or "at least one of A, B and/or C" are all of the items listed together. It can include possible combinations. Expressions such as "first", "second", "first" or "second" can modify the corresponding elements regardless of their order or importance, and are only used to distinguish one element from another. It does not limit the components. When any (eg, first) component is referred to as being “(functionally or communicatively) connected” or “connected” to another (eg, second) component, the component is It may be directly connected to the component, or may be connected through another component (eg, a third component).

The term "module" used in this document includes a unit composed of hardware, software, or firmware, and may be used interchangeably with terms such as, for example, logic, logic blocks, parts, or circuits. The module may be an integrally configured component or a minimum unit that performs one or more functions, or a part thereof. For example, the module may be configured as an application-specific integrated circuit (ASIC).

According to the somatic marker hypothesis, a person's subjective emotional experience is closely related to the processing of peripheral nerve signals generated by the internal organs (viscera) in the brain, especially in the cerebral cortex. At this time, signals generated from internal organs are expressed as interoceptive signals, and detecting these signals in the brain can be expressed as interoception. Sensory signals for internal acceptance are processed and processed in the brain through several stages, and subjective emotional experiences may vary depending on how the internal sensory signals are interpreted in the cerebral cortex. Therefore, if the internal sensory signals are not properly processed, various psychiatric diseases, especially emotional psychiatric diseases, may be caused, and representative examples include depression, anxiety disorder, borderline personality disorder, and the like.

For the above reasons, it is no exaggeration to say that processing and processing of sensory signals for domestic use is the most essential in the emotional processing process. However, in general, based on an autonomic nervous system response occurring in the body, for example, heart rate variability or skin resistance, or a brain response related to a visual or auditory stimulus, an emotion processing process is being read. However, the autonomic nervous system response is not specific to an emotional state, and when an emotion processing process is read by a brain response related to a visual or auditory stimulus, the reading performance may be low depending on the type of stimulus. Therefore, reading the emotion processing process based on the processing and processing of sensory signals for domestic use will enable reading the emotion processing process irrespective of the type of emotional stimulus, using an intrinsic mechanism of emotion processing.

According to various embodiments, heartbeat evoked potential information may be used to read an emotion processing process based on processing and processing of sensory signals for domestic use. Heart rate-induced EEG information is an EEG signal generated in a time range of 200 ms to 600 ms after the heart rate signal is generated, and is derived from the EEG signal that appears when the heart rate stimulates the cerebral cortex in the central nervous system through the vagus nerve. Can be detected. These EEG signals are known to reflect the process of processing heartbeat signals in the brain, and are known to change sensitively in emotion-related psychiatric disorders such as depression, anxiety disorder, and borderline personality disorder. Heart rate-induced EEG information may be detected from changes in spatiotemporal patterns of EEG signals according to emotional stimulation and neutral stimulation.

1 is a diagram illustrating an electronic device according to various embodiments.

Referring to FIG. 1, an electronic device 100 according to various embodiments is a device for reading an emotional stimulus, and includes at least one of a sensing unit 110, a memory 120, a display unit 130, or a processor 140. It can contain either.

The sensing unit 110 may detect a biosignal of an object. Here, the object may include a person. For example, the sensing unit 110 may detect a biosignal by contacting a human body. In this case, the biosignal may include an electrocardiogram signal and an EEG signal.

The memory 120 may store data used by at least one component of the electronic device 100. The memory 120 may store at least one of input data or output data for software such as a program and a command related thereto. The program may include at least one of an operating system, middleware, and application. For example, the memory 120 may include at least one of a volatile memory or a nonvolatile memory. According to an embodiment, the memory 120 may include a database related to emotional stimulation. For example, the database may store a plurality of coded models, and the coded models may represent heartbeat evoked potential (HEP) information related to each emotional stimulus.

The display unit 130 may visually provide data to the outside of the electronic device 100. For example, the display unit 130 may include at least one of a display, a hologram device, and a projector.

The processor 140 may control at least one component of the electronic device 100 based on a program, and may perform data processing and operation. The processor 140 may store heartbeat-induced brainwave information in the memory 120 in response to the emotional stimulation. To this end, the processor 140 may detect a cardiac degree signal and an EEG signal related to emotional stimulation through the sensing unit 110, and detect heartbeat-induced EEG information from the EKG signal and the EEG signal. According to an embodiment, the processor 140 may code heart rate-induced EEG information, associate emotion stimulus with heart rate-induced EEG information, and store it in a database. In addition, the processor 140 may read the emotional stimulus by using the heartbeat-induced brainwave information of the memory 120. The processor 140 may detect heart rate-induced EEG information based on the EEG signal detected through the sensing unit 110 and read emotional stimuli in response to the heart rate-induced EEG information. According to an embodiment, the processor 140 compares the EEG signal extracted by decoding the EEG information from the database and the EEG signal detected through the sensing unit 110, and compares the EEG information and the EEG information from the database. You can choose the corresponding emotional stimulus.

The electronic device 100 according to various embodiments may include a memory 120 and a processor 140 connected to the memory 120 as a device for reading emotional stimuli.

According to various embodiments, the processor 140 stores heartbeat-induced EEG information in the memory 120 in response to emotional stimulation, and detects the heartbeat-induced EEG information based on the detected EEG signal, In response to the heart rate-induced brain wave information, it may be configured to read the emotional stimulus.

According to various embodiments, the electronic device 100 may further include a sensing unit 110 configured to detect an electrocardiogram signal and an EEG signal.

According to various embodiments, the processor 140, through the sensing unit 110, detects an electrocardiogram signal and an EEG signal related to the emotional stimulation, analyzes the electrocardiogram signal and the EEG signal, and causes the heartbeat. It may be configured to detect EEG information and store the heart rate-induced EEG information in the memory 120 in response to the emotional stimulation.

According to various embodiments, the processor 140 detects an R-peak in the electrocardiogram signal, detects a partial region in which a predetermined time has elapsed from the R-peak in the EEG signal, and uses the partial region. Thus, it may be configured to detect the heart rate-induced brain wave information.

According to various embodiments, the partial region starts from a point where the predetermined time has elapsed from the R-peak, and may be formed at predetermined time intervals.

According to various embodiments, the memory 120 may include a database in which the emotional stimulation and heartbeat-induced brainwave information are correlated and stored.

According to various embodiments, the processor 140 may be configured to code the heartbeat-induced EEG information, associate the emotional stimulus with the heartbeat-induced EEG information, and store the data in the database.

According to various embodiments, the processor 140 may be configured to detect the heartbeat-induced EEG information from the database based on the detected EEG signal.

According to various embodiments, the processor 140, based on the database, decodes the heartbeat-induced EEG information, extracts an EEG signal, and compares the detected EEG signal with the extracted EEG signal. , It may be configured to select the heart rate-induced EEG information from the database.

According to various embodiments, the processor 140 may be configured to generate the emotional stimulation and detect the ECG signal and the EEG signal through the sensing unit 110.

According to various embodiments, the processor 140 may be configured to generate an emotional condition related to the emotional stimulation and a pre-neutral condition at predetermined time intervals.

2 is a diagram illustrating a method of operating an electronic device 100 according to various embodiments.

Referring to FIG. 2, in operation 210, the electronic device 100 may store heartbeat-induced brainwave information in response to an emotional stimulus. To this end, the electronic device 100 may learn about heartbeat-induced brainwave information related to emotional stimulation. Here, the electronic device 100 may repeatedly learn a plurality of objects and various emotional stimuli. In this case, the processor 140 may associate the emotional stimulus with the heartbeat-induced EEG information and store it in a database related to the emotional stimulus of the memory 120. The processor 140 may detect heartbeat-induced brainwave information in response to an emotional stimulus.

3 is a diagram illustrating a database storage operation of FIG. 2. FIG. 4 is a diagram for describing an operation of generating emotional stimulation of FIG. 3.

Referring to FIG. 3, the electronic device 100 may generate emotional stimulation in operation 310. The processor 140 may generate an emotional stimulus by at least one of visual or auditory stimuli. According to an embodiment, the processor 140 may visually generate emotional stimulation through the display unit 130 as illustrated in FIG. 4. According to another embodiment, the processor 140 may generate emotional stimulation aurally as an audio signal. In this case, the processor 140 may generate an emotional condition and a neutral condition related to the emotional stimulation at predetermined time intervals.

For example, the emotional stimulus may include a happiness stimulus and a sadness stimulus, and the emotional condition may include a happiness condition related to the happiness stimulus and a sadness condition related to the sadness stimulus. For example, the processor 140 generates a sadness condition as shown in FIG. 4(a) and maintains the sadness condition for 0.5 s, and then generates a neutral condition as shown in FIG. 4(b). And maintain a neutral condition for 1 s. As another example, the processor 140 generates a sad condition as shown in FIG. 4(c) and maintains the happy condition for 0.5 s, and then generates a neutral condition as shown in FIG. 4(b). And maintain a neutral condition for 1 s. Here, in order to maintain the continuous interest of the object, the processor 140 may maintain a certain neutral condition and then provide an indicator arbitrarily designated as shown in (d) of FIG. 4.

The electronic device 100 may detect an electrocardiogram signal and an EEG signal related to emotional stimulation in operation 320. While the emotional stimulation is generated, the processor 140 may detect the ECG signal and the EEG signal of the object through the sensing unit 110. In this case, the ECG signal and the EEG signal may be expressed as a result of the object's response to the emotional stimulus. In some embodiments, the processor 140 may continuously collect the ECG signal and the EEG signal of the object before generating the emotional stimulation. For example, the processor 140 may collect an electrocardiogram signal and an EEG signal of the object for a time period from 700 ms before to 1300 ms after the start of the emotional stimulation.

In operation 330, the electronic device 100 may detect heartbeat-induced EEG information from the electrocardiogram signal and the EEG signal. The processor 140 may analyze the electrocardiogram signal and the EEG signal to detect heartbeat-induced EEG information. In this case, the processor 140 may detect a partial region of the EEG signal based on the R-peak of the ECG signal. Through this, the processor 140 may detect heartbeat-induced EEG information from a partial region of the EEG signal.

5 is a diagram illustrating an operation of detecting heartbeat-induced brainwave information of FIG. 3. 6, 7, 8, 9, and 10 are diagrams for explaining an operation of detecting heartbeat-induced EEG information of FIG. 2.

Referring to FIG. 5, in operation 510, the electronic device 100 may analyze an electrocardiogram signal in relation to emotional stimulation. In this case, the processor 140 may detect an R-peak from the ECG signal. For example, as shown in FIG. 6, an R-peak may appear in the electrocardiogram signal. In humans, the visual impulse is transmitted to the central nervous system immediately through the retina, and the heartbeat is transmitted to the central nervous system approximately 200 ms after the R-peak by the vagus nerve impulse. For this reason, the processor 140 may ignore the R-peak generated 200 ms before the start of the emotional stimulation.

The electronic device 100 may analyze the EEG signal based on the electrocardiogram signal in operation 520. The processor 140 may detect a partial region of the EEG signal based on the R-peak. For example, the processor 140 may detect a partial region of the EEG signal corresponding to a time from 500 ms before to 600 ms after the R-peak. According to an embodiment, the processor 140 may detect a partial region in which a predetermined time has elapsed from the R-peak in the EEG signal as shown in FIGS. 7 and 8. For example, the processor 140 may detect a partial region from the EEG signal of the right frontal lobe as shown in FIG. 7, and as shown in FIG. 8, the right globus pallidus (RGP), the right anterior insula (RAI) ), a right anterior cingulated cortex (RACC), or a right superior frontal gyrus (RSFG). Here, some regions of the EEG signal start from a point where a predetermined time has elapsed from the R-peak, and may be formed at predetermined time intervals. For example, the predetermined time may include at least one of 488 ms to 515 ms. For example, the predetermined time is 488 ms, and the predetermined time interval may be from 488 ms to 515 ms from the R-peak.

The electronic device 100 may analyze a causal relationship between the emotional stimulus and the EEG signal in operation 530. The processor 140 may analyze a causal relationship between the emotional stimulation and the EEG signal based on a partial region of the EEG signal. In this case, the processor 140 may analyze a granger causality (GC) to analyze an EEG signal according to an emotional stimulus. For example, the processor 140 may compare the EEG signal of RAI and the EEG signal of RACC. Meanwhile, the processor 140 may compare a causal relationship according to an emotional condition related to the emotional stimulation and a causal relationship according to the neutral condition.

In operation 540, the electronic device 100 may detect heartbeat-induced brainwave information. The processor 140 may detect heartbeat-induced EEG information by using a partial region of the EEG signal. In this case, the processor 140 may code the heartbeat-induced brainwave information. For example, the processor 140 may learn heartbeat-induced EEG information based on a convolution neural network (CNN) structure as shown in FIG. 9. The convolutional neural network structure may include five hidden layers, for example, two convolution layers, two pooling layers, and one softmax layer and an output layer. According to the structure of a convolutional neural network, as illustrated in FIG. 10, as learning is repeated, the accuracy of the learning result may be improved. After that, the electronic device 100 may return to FIG. 3.

The electronic device 100 may associate an emotional stimulus with a heart rate inducing potential in operation 340. The processor 140 may associate emotional stimulation with heartbeat-induced EEG information and store it in a database related to emotional stimulation in the memory 120. For example, the database may store a plurality of coded models, and the coded models may represent heartbeat-induced brainwave information related to each emotional stimulus. For example, the processor 140 may update any one of the coding models and may generate a new coding model. After that, the electronic device 100 may return to FIG. 2.

The electronic device 100 may read an emotional stimulus based on an EEG signal in operation 220. In this case, the processor 140 may read the emotional stimulus by using a database related to the emotional stimulus of the memory 120. The processor 140 may detect heart rate-induced EEG information from a database based on the EEG signal detected through the sensing unit 110 and read emotional stimuli in response to the heart rate-induced EEG information. Here, the processor 140 may read an emotional stimulus corresponding to an EEG signal of a specific object. Through this, the electronic device 100 may read an emotion processing process of an object.

11 is a diagram illustrating an emotional stimulus reading operation of FIG. 2. 12 is a diagram for explaining an emotional stimulus reading operation of FIG. 2.

Referring to FIG. 11, the electronic device 100 may detect an EEG signal in operation 1110. The processor 140 may detect an EEG signal of an object through the detection unit 110. Here, the processor 140 may detect the EEG signal of the object for a predetermined time.

In operation 1120, the electronic device 100 may detect heartbeat-induced EEG information based on the EEG signal. The processor 140 may select heartbeat-induced brainwave information from the database 1210. For example, the processor 140 may extract each EEG signal (dotted line) by decoding heart rate-induced EEG information stored in the coded models of the database 1210 as shown in FIG. 12. In addition, the processor 140 may compare the EEG signal (solid line) detected through the sensing unit 110 with the EEG signal (dotted line) extracted from the database 1210. In this case, the processor 140 may check the similarity between the EEG signal (solid line) detected through the sensing unit 110 and the EEG signal (dotted line) extracted from the database 1210. Through this, the processor 140 may select any one of the coded models of the database 1210 based on the similarity to the EEG signal (solid line) detected through the sensing unit 110, and the EEG information that causes the heart rate.

In operation 1130, the electronic device 100 may read an emotional stimulus corresponding to brain wave information that causes heartbeat. The processor 140 may read an emotional stimulus corresponding to the heartbeat-induced brainwave information from the database 1210 of the memory 120. Through this, the electronic device 100 may read an emotional stimulus corresponding to the EEG signal of the object.

The method of reading emotional stimulation of the electronic device 100 according to various embodiments includes an operation of storing heartbeat-induced EEG information in response to an emotional stimulation, an operation of detecting the heartbeat-induced EEG information based on a detected EEG signal, And reading the emotional stimulus in response to the heartbeat-induced brainwave information.

According to various embodiments, the storing of the heartbeat-induced EEG information in response to the emotional stimulation includes an operation of detecting an electrocardiogram signal and an EEG signal related to the emotional stimulation, analyzing the electrocardiogram signal and the EEG signal, An operation of detecting heartbeat-induced EEG information, and an operation of storing the heartbeat-induced EEG information in response to the emotional stimulation.

According to various embodiments, the operation of analyzing the electrocardiogram signal and the EEG signal to detect the heartbeat-induced EEG information includes an operation of detecting an R-peak from the EEG signal, and determined from the R-peak in the EEG signal. An operation of detecting a partial region that has elapsed with time, and an operation of detecting the heartbeat-induced EEG information by using the partial region.

According to various embodiments, the partial region starts from a point where the predetermined time has elapsed from the R-peak, and may be formed at predetermined time intervals.

According to various embodiments, the storing of the heart rate-induced EEG information in response to the emotional stimulus includes an operation of coding the heart rate-induced EEG information, and associating the emotional stimulus with the heart rate-induced EEG information, and a database It may include an operation of saving to.

According to various embodiments, the detecting of the heartbeat-induced EEG information based on the detected EEG signal may include detecting the heartbeat-induced EEG information from the database.

According to various embodiments, the operation of detecting the heart rate-induced EEG information from the database includes an operation of extracting an EEG signal by decoding the heart rate-induced EEG information based on the database, and the detected EEG. Comparing the signal and the extracted EEG signal, the operation of selecting the heart rate-induced EEG information from the database may be included.

According to various embodiments, the operation of detecting the electrocardiogram signal and the EEG signal related to the emotional stimulation may include an operation of generating the emotional stimulation and an operation of detecting the electrocardiogram signal and the EEG signal.

According to various embodiments, the operation of visually generating the emotional stimulation may include an operation of generating an emotional condition and a neutral condition related to the emotional stimulation at predetermined time intervals.

According to various embodiments, the predetermined time may include at least one of 488 ms to 515 ms.

According to various embodiments, the electronic device 100 may improve the reading performance of the emotional stimulus by using the heartbeat-induced brainwave information to read the emotional stimulus. Through this, accuracy and efficiency can be increased in precise diagnosis and determination of treatment progress for emotion-related psychiatric disorders such as depression, anxiety disorder, borderline personality disorder, and the like.

Although various embodiments of the present document have been described, various modifications may be made without departing from the scope of the various embodiments of the present document. Therefore, the scope of the various embodiments of the present document is limited to the described embodiments and should not be defined by the scope of the claims to be described later, as well as the scope and equivalents of the claims.

Claims (20)

In the method for reading emotional stimuli of an electronic device,
Storing heartbeat-induced brainwave information in response to emotional stimulation;
Detecting the heartbeat-induced brainwave information based on the detected brainwave signal; And
In response to the heart rate-induced brain wave information, including an operation of reading the emotional stimulus,
The operation of storing the heartbeat-induced brainwave information in response to the emotional stimulation,
Detecting an electrocardiogram signal and an EEG signal related to the emotional stimulation;
Analyzing the ECG signal and the EEG signal to detect the heartbeat-induced EEG information; And
And storing the heartbeat-induced brainwave information in response to the emotional stimulation,
Analyzing the ECG signal and the EEG signal to detect the heart rate-induced EEG information,
Detecting an R-peak from the ECG signal;
Detecting a partial region of the brainwave signal in which a predetermined time has elapsed from the R-peak; And
And detecting the heartbeat-induced brainwave information by using the partial region,
The partial region starts at a point where the predetermined time has elapsed from the R-peak in the EEG signal, and is formed at a predetermined time interval,
The operation of storing the heartbeat-induced brainwave information in response to the emotional stimulation,
Generating a coded model by coding the heartbeat-induced brainwave information; And
Associating the emotional stimulus with the coded model, and storing the coded model in a database,
Based on the detected EEG signal, the operation of detecting the heartbeat-induced EEG information,
Decoding a plurality of coded models stored in the database and extracting EEG signals of the coded models, respectively; And
And detecting the heart rate-induced EEG information from one of the coding models based on the similarity between each of the extracted EEG signals and the detected EEG signal.
delete delete delete delete delete delete The method of claim 1, wherein the detecting of the ECG signal and the EEG signal related to the emotional stimulation comprises:
Generating the emotional stimulation; And
A method comprising the operation of detecting the ECG signal and the EEG signal.
The method of claim 8, wherein the operation of visually generating the emotional stimulation,
And generating an emotional condition and a neutral condition related to the emotional stimulation at predetermined time intervals.
The method of claim 1,
The predetermined time includes at least one of 488 ms to 515 ms.
In the electronic device for reading emotional stimulus,
Memory;
A processor connected to the memory; And
Including a sensing unit configured to detect an electrocardiogram signal and an EEG signal,
The processor,
In response to emotional stimulation, heart rate-induced brain wave information is stored in the memory,
Based on the detected EEG signal, detecting the heart rate-induced EEG information,
In response to the heart rate-induced brain wave information, configured to read the emotional stimulus,
The processor,
Through the sensing unit, detecting an electrocardiogram signal and an EEG signal related to the emotional stimulation,
By analyzing the ECG signal and the EEG signal, detecting the heart rate-induced EEG information,
In response to the emotional stimulation, configured to store the heartbeat-induced brainwave information in the memory,
The processor,
Detecting the R-peak in the ECG signal,
In the brainwave signal, a partial region in which a predetermined time has elapsed from the R-peak is detected,
Using the partial region, configured to detect the heartbeat-induced brainwave information,
The partial region starts at a point where the predetermined time has elapsed from the R-peak in the EEG signal, and is formed at a predetermined time interval,
The processor,
By coding the heart rate-induced brain wave information, a coding model is generated,
Associating the emotional stimulus with the coding model, and storing the coded model in a database of the memory,
The processor,
By decoding a plurality of coded models stored in the database, each of the EEG signals of the coded models is extracted,
An electronic device configured to detect the heartbeat-induced EEG information from one of the coded models based on a similarity between each of the extracted EEG signals and the detected EEG signal.
delete delete delete delete delete delete delete The method of claim 11, wherein the processor,
Generating the emotional stimulation,
An electronic device configured to detect the ECG signal and the EEG signal through the sensing unit.
The method of claim 19, wherein the processor,
An electronic device configured to generate an emotional condition and a neutral condition related to the emotional stimulation at predetermined time intervals.

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