KR101576892B1 - Contents recommending system and contents recommending method based on eeg/ecg using wireless communication - Google Patents
Contents recommending system and contents recommending method based on eeg/ecg using wireless communication Download PDFInfo
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Abstract
A content recommendation system based on brain waves / heart rate using wireless communication, and a content recommendation method. The EEG based content recommendation system according to the present invention includes a brain wave / heart rate sensing headset and a content reproduction device interconnected via wireless communication; The EEG / heart rate sensing headset includes an EEG sensing part for sensing EEG, a heart rate sensing part for sensing a heart rate, an EEG signal sensed by the EEG sensing part, and a heart rate sensed by the heart rate sensing part A headset wireless communication unit for transmitting a signal via wireless communication; Wherein the content reproducing device comprises: a device wireless communication unit for receiving the brain wave signal and the heart rate signal transmitted from the brain wave / heart rate sensing headset through wireless communication; and a controller for receiving at least one measurement brain wave signal from the brain wave signal and the heart rate signal, And a plurality of registration state data sets each corresponding to a plurality of person states, wherein each of the plurality of registration state data sets includes: A registration data set storage unit that stores a plurality of registration variable sets each including at least one registered EEG variable and at least one registered heart rate parameter; and a comparison unit that compares the measured state data with the plurality of registered state data sets, A state determination unit for determining a current state, Characterized in that it comprises a unit for providing the like can be determined by extracting the registered content group appropriate for the current state is determined by the.
Description
The present invention relates to a content recommendation system and a content recommendation method based on brain waves / heart rate using wireless communication, and more particularly, to a system and method for recommending and reproducing contents suitable for a user's current state by measuring a brain wave and a heart rate of a user A content recommendation system based on brain waves / heart rate using wireless communication, and a content recommendation method.
Human brain has the most resilience and adaptability in nature such as sensitivity, cognition, thinking, and action. The human brain is made up of hundreds of billions of nerve cells. Each neuron is connected to other neurons in various ways. This phenomenon is called synapse.
These interactions are the key to the mental activity of everyone, including learning, memory, cognition, behavior, and decision, and are responsible for the physical control of the body to maintain health. These synapses are formed by chemical action, which is converted into the electric current of the scalp to form an electroencephalogram. In other words, hundreds of billions of nerve cells interact with other neurons in the vicinity to transmit information, which in turn generates electrical signals. Therefore, when an electrode is inserted into the scalp and the electrical change is measured, the electrical change is displayed as a wave, which is an EEG.
These brain waves have various shapes depending on the degree of brain activity, and the more the brain is actively active, the higher the frequency of the brain waves, and the lower the frequency of the brain becomes. These brain waves include gamma waves, beta waves, alpha waves, theta waves, and delta waves.
Gamma waves have a center frequency of 40 Hz and range from 38 to 45 Hz, the fastest of the brain activity waves, and appear when performing complex mental functions with tension and active altitude. The beta wave has a center frequency of 17.3 Hz and its range is from 15 to 38 Hz. It appears when the active brain function is performed in the cerebrum, and when it is subjected to stress and stress.
The alpha frequency is about 10.3Hz in the center frequency, 8 ~ 12Hz in the range, and occurs conspicuously in the occipital occipital lobe in consciousness state, which is neither latent nor unconscious, mainly in relaxation of tension, appear.
The center frequency of the cetapha is about 6.3Hz and its range is 4 ~ 8Hz. It is dominant in the region of the goiters involved in emotion and emotion in the brain region. In other words, since it is mainly dominant in the field of emotions and emotions, it has a great impact on artistic endeavors, heart injuries, joyful and joyful tasks and play.
The delta wave has a center frequency of about 1.3 Hz and a range of 0.5 to 4 Hz. It occurs mainly in the areas of training related to life, pons, and midbrain. It is dominant in the area of the gofferm involved in emotion, in the input and output of information, and in the sleep of the neocortex (cerebrum) involved in the judgment of the accident .
Recently, SMR (Sensory Motor Rhythm) para between beta wave and alpha wave has been actively studied for a new type of important brain wave. The SMR wave has a center frequency of 12.7 Hz and a range of 12 to 15 Hz. It occurs predominantly in the cerebral (neocortical) area from below the ear to the center of the brain.
The SMR wave is related when solving the problem requiring simple concentration, and also when the relaxation is required in the state of consciousness. In other words, it appears to be in a state where concentration is made in the state of not being tense, and it is easy, simple and precise to perform without being stressed. The SMR wave was found to be a focused attention brain in that it had the ability to easily solve all tasks with a very low energy compared to the beta wave.
Using the measurement values of the EEG as described above, a human condition such as psychological state or mental state of a person may be used as an indicator. For example, a method of calculating a concentration index, a relaxation index, a stress index, and the like using each of the characteristic waves constituting the EEG is proposed as shown in Equation (1).
[Equation 1]
Concentration index = (SMR wave + M beta wave) / theta wave
Relaxation index = Alfa wave / H beta wave
Stress index = H beta wave
On the other hand, the field using EEG is not only a medical field, but also trying to use EEG in various fields. For example, Korean Patent No. 10-1002751 proposes a learning diagnostic apparatus using brain waves, which includes an electrode unit for detecting an EEG signal and an EEG signal detected at an electrode unit, An EEG processing and calculation unit for generating information related to the concentration of learning and concentration of time of the poem, and a learning unit for receiving and storing learning plan information established by an external device by the user, A storage unit for storing information related to the concentration and concentration holding time, and a transmission / reception unit for transmitting information related to the concentration of learning and the concentration holding time generated in the actual learning interval of the user to an external device and receiving learning plan information from an external device And is generated using at least one of learning concentration information and concentration holding time information from an external apparatus The change learning plan information is received, and the received change learning plan information is updated in the storage unit.
Accordingly, the technique disclosed in Korean Patent No. 10-1002751 provides feedback in real time based on the result of analysis of the brain waves during the actual learning period of the user, so that the user is continuously immersed in learning In addition, it provides concentration-strengthening contents linked to the results of EEG analysis in the actual learning section, and systematic learning is performed in conjunction with the EEG analysis result.
Meanwhile, the technology disclosed in Korean Patent No. 10-0947639 relates to a method for controlling a computer through brain waves to enable multimedia contents such as music and images to be output and output according to brain waves. Specifically, A brain wave measuring unit, a database storing a brain wave corresponding signal for outputting a multimedia signal corresponding to each of the emotion characteristics of brain waves, a brain wave corresponding signal output unit for extracting brain wave corresponding signals corresponding to brain waves measured by the brain wave measuring unit from the database, And a multimedia signal output unit for outputting a multimedia signal according to an emotional state of the subject according to the extracted brainwave correspondence signal. According to the brain wave generated according to the emotional state of the subject, various contents And the user can immediately see his / her emotional state And it is possible to maximize the sensitivity development of each individual.
However, the above-described conventional technologies including the Korean registered patent disclose that when an emotional state of the subject is measured using the measured EEG, the existing registered data, for example, The present inventors have found that there is a problem that the state of the brain waves of the subject is not reflected at present.
For example, the magnitude of the SMR wave when focusing on a person is different. If only the average value of a plurality of people measured in advance is used, even if the accuracy of the EEG measurement for the current subject is guaranteed, There is a big problem in the judgment of the state that error occurs.
In addition, judging only the emotional state of a person by only an EEG signal may cause a larger error due to a difference in EEG measurement or a difference in each person described above, so that other vital signs, for example, heart rate, It would be appropriate to know the current state.
Accordingly, the present invention has been made in order to solve the above-described problems, and it is an object of the present invention to provide a method and apparatus for measuring an EEG and a heart rate using a measuring device that simultaneously measures an EEG and heart rate of a subject, The present invention provides a content recommendation system and a content recommendation method based on brain waves / heart rate based on wireless communication that can grasp a current state of a subject and recommend a content suitable for the subject.
The present invention also relates to a method of registering data measured for a subject on a criterion to be compared and using a wireless communication capable of storing comparison data suitable for a subject through learning of registered data, Another object is to provide a content recommendation system and a content recommendation method.
According to the present invention, said object is achieved by a headphone system comprising a brain-wave / heart-rate sensing headset and a content reproduction device interconnected via wireless communication; The EEG / heart rate sensing headset includes an EEG sensing part for sensing EEG, a heart rate sensing part for sensing a heart rate, an EEG signal sensed by the EEG sensing part, and a heart rate sensed by the heart rate sensing part A headset wireless communication unit for transmitting a signal via wireless communication; Wherein the content reproducing device comprises: a device wireless communication unit for receiving the brain wave signal and the heart rate signal transmitted from the brain wave / heart rate sensing headset through wireless communication; and a controller for receiving at least one measurement brain wave signal from the brain wave signal and the heart rate signal, And a plurality of registration state data sets each corresponding to a plurality of person states, wherein each of the plurality of registration state data sets includes: A registration data set storage unit that stores a plurality of registration variable sets each including at least one registered EEG variable and at least one registered heart rate parameter; and a comparison unit that compares the measured state data with the plurality of registered state data sets, A state determination unit for determining a current state, EEG / heart rate using a wireless communication terminal characterized in that it comprises an extraction of the registered content group appropriate for the current state determined by the determination unit recommendations provided by may also be achieved by the content-based recommendation system.
And a pattern learning module that learns a new combination of variables using the plurality of registration state data sets registered in the registration data set storage unit; Wherein the pattern learning module randomly extracts a variable from the set of registration state data to generate a new registered number of combinations of variables and compares each new variable combination with a combination of the registered variables, Extracts at least one combination of registration variables matching with the combination, increases the weight of the new combination of variables when the mutually matched new combination of variables and the combination of the registered variables have the same person status, The weight of the new combination of variables may be reduced if the state of the combination of the registration variables is different and a plurality of new combinations of variables of the new combination of variables may be updated to the registration state data set.
A user log storage unit; And a recommendation determining unit that determines whether or not the recommendation content provided by the recommendation content determining unit is reproduced based on the measurement status data generated by the measurement status data generator and the person status based on the determination result of the status determination unit, And a user log feedback unit for storing the user log in the storage unit.
The pattern learning module may register the measurement state data and the person state stored in the user log storage unit as a new variable combination of the registration state data set.
The state determination unit compares each combination of the plurality of registration variable constituting each of the registration state data sets with a combination of variables constituting the measurement state data, and assigns a weight according to the degree of similarity; Summing the weights for each person state to calculate a state probability for each person state; The human condition can be determined based on the state probability.
According to another aspect of the present invention, there is provided a method of recommending contents based on brain waves / heart rate using wireless communication, the method comprising the steps of: (a) Wherein each said set of enrollment state data is registered including a plurality of enrollment variable combinations each comprising at least one enrollment EEG variable and at least one enrollment heart rate variable; (b) detecting brain waves and heart rate through an EEG / heart rate sensing headset; (c) transmitting an electroencephalogram signal and a heart rate signal sensed by the brainwave / heart rate sensing headset via wireless communication to the content reproduction device; (d) extracting at least one measured EEG variable and at least one measured heart rate variability parameter from the EEG signal and the heart rate signal transmitted from the EEG / heart rate sensing headset in the contents reproducing device to generate measurement state data ; (e) comparing the measurement state data with the plurality of registration state data sets to determine a current state; (e) extracting and providing pre-registered content suitable for the current state determined in the step (e), and providing the pre-registered content to the user; have.
(A1) randomly extracting a variable from the registration state data set to generate a new registered variable combination; (a2) extracting at least one registered variable combination that matches each new variable combination through comparison of each new variable combination and the registered variable combination; (a3) when the mutual matching of the new variable and the human condition of the registered variable combination are the same, the weight of the new variable combination is increased, and when the mutually matching new variable combination is different from the human condition of the registered variable combination Decreasing the weight of the new variable combination; (a4) updating the plurality of new variable combinations having the higher weight among the new variable combinations to the registration state data set.
(A5) performing the steps (b), (c), (d), and (e) while the recommended content is played back; (a6) storing the measurement status data generated in the performing of the step (a5) and the human condition based on the result of the human condition determination in the performing of the step (a5) in the user log storage together with the recommended content Step < / RTI >
(A7) registering the measurement state data and the person state stored in the user log storage unit as a new variable combination of the corresponding registration state data set; (a8) The step (a1) to (a4) may be performed after the new variable combination is registered through the step (a7).
The step (e) includes the steps of: (e1) comparing each combination of the plurality of registration variables constituting each of the registration state data sets with a combination of variables constituting the measurement state data, and assigning weights according to the degree of similarity Wow; (e2) calculating a state probability for each human condition by summing the weights for each human condition; (e3) determining a human condition based on the state probability.
According to the present invention, according to the present invention, an EEG and a heart rate are measured using a measuring device simultaneously measuring an EEG and a heart rate of a subject, and the current state of the subject A content recommendation system and a content recommendation method based on brain waves / heart rate based on wireless communication are provided.
Further, according to the present invention, data measured for a subject is also registered in a criterion to be compared, and a brain wave / heart rate based on wireless communication capable of accumulating comparison data suitable for a subject through learning of registered data A content recommendation system and a content recommendation method of the present invention are provided.
FIG. 1 is a diagram illustrating a configuration of a content recommendation system based on brain waves / heart rate using wireless communication according to the present invention,
2 is a perspective view of an EEG / heart rate sensing headset according to the present invention,
3 is a diagram illustrating a configuration of an EEG / heart rate sensing headset according to the present invention,
4 is a diagram showing a configuration of a content reproducing device according to the present invention,
5 to 7 are views for explaining a method of recommending contents based on brain waves / heart rate using wireless communication according to the present invention.
Hereinafter, embodiments according to the present invention will be described in detail with reference to the accompanying drawings.
FIG. 1 is a diagram illustrating a configuration of a content recommendation system based on brain waves / heart rate using wireless communication according to the present invention. Referring to FIG. 1, a brain wave / heart rate-based content recommendation system according to the present invention includes a brain wave / heart
The brain wave / heart
1 and 2, the
2, a plurality of electrodes 120a for measuring brain waves are installed in a
Referring to FIG. 3, the brain-wave / heart-
The
Here, in the present invention, the
The headset
The
4 is a diagram showing a configuration of a
The device
The measurement
4, the measurement
On the other hand, in the registration data
Here, the measured EEG parameters and measured heart rate variability parameters extracted from the measurement
More specifically, the plurality of registration state data sets 341, 342, and 343 registered in the registration data
Each registration
5, registration state data sets 341, 342, and 343 corresponding to a normal state constitute a plurality of registration
Here, the registered EEG variable may include a central index variable, a relaxation index variable, and a stress index variable as shown in Equation (1), and the registered heart rate parameter may include a fatigue index variable, a physical stress index variable, a blood vessel elasticity index variable May be included. Here, it is a matter of course that a variety of indicators obtained through measurement of brain waves or heart rate can be used as the registered EEG variable and the registered heart rate parameter, and the number or kind thereof is not limited to the above example.
The values of the registered EEG variable and the registered heart rate parameter are stored in advance as numerical values measured for a plurality of persons. For example, when a person is recognized as a normal state by using data obtained from various clinical trials, examples of the values of the respective variables form a combination of
In a state where a plurality of registration state data sets 341, 342, and 343 including a plurality of registration
The
Hereinafter, with reference to FIG. 6, a content recommendation method of a content recommendation system based on EEG / heart rate according to the present invention will be described in detail.
First, when the EEG / heart
Then, the measured
The
The
The above process is performed until all the combinations of variables constituting the registration state data sets 341, 342, and 343 are performed (S53d), and then the weights are added to each state (S53e). Thereby, a sum value of weights for each registration
In the present invention, the
If the current user status is determined through the above process, the recommended
Referring again to FIG. 4, the
FIG. 7 is a diagram for explaining a process of learning a new variable combination by the
Then, the
The new variable combination extracted as described above is repeatedly executed in steps S72 and S73 until a predetermined number r is extracted to generate r new variable combinations in one registration
When the creation of a new variable combination for one registration
If a plurality of new variable combinations are generated through the above process, the comparison and matching process between the respective variable combinations and the initial variable combinations, that is, the registered
More specifically, by comparing the variables of one new variable combination and the registered
If the above process is performed on all extracted new variable combinations, the weight of each new variable combination is finally determined. In this case, a certain ratio or a certain number of variable combinations having a low weight is removed (S80) A new variable combination having a higher weight among the new variable combinations is registered in the registration state data sets 341, 342, 343 (S81), and the registration state data sets 341, 342, 343 are updated.
Through the above process, it is possible to perform a more accurate state determination using more reliable reference data by updating the new variable combination through self learning without using only the average data acquired through the existing clinical experiment.
4, the
FIG. 8 is a diagram for explaining a process in which relevant information is stored in the user
At this time, when the EEG / heart
Then, the measurement
The above process can be performed at a predetermined period T until the content is terminated (S65) (S68). If the content is terminated, related information measured during the content reproduction is generated as log data (S66 ). Here, the log data may be generated as log data together with the recommended content and the current state of the user based on the measurement state data generated through the process and the determination result determined by the
Also, the log data may be recorded together with the measurement status data of the user on which the recommendation content is determined. Thus, it is possible to confirm whether recommendation of the recommendation content based on the user's measurement state data is desirable or not and can be confirmed through the state change in the reproduction process of the recommendation content. In this case, It can be determined that the state judgment is appropriate for the user.
Accordingly, the
When the
It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to be exemplary and explanatory only and are not to be construed as limiting the scope of the inventive concept. And it is obvious that it is included in the technical idea of the present invention.
100: EEG / heart rate sensing headset 110: frame
120: EEG sensing unit 130: Heart rate sensing unit
140: Headset wireless communication unit 300: Content playback device
310: device wireless communication unit 320: measurement state data generation unit
330: status determination unit 340: registration data set storage unit
341,342,343: Registration state data set
341a, 341b, 341c: combination of registered variables
350: pattern learning module 360: recommended content determination unit
371: User log feedback unit 372: User log storage unit
Claims (10)
The EEG / heart rate sensing headset
An EEG sensing unit for sensing an EEG,
A heart rate monitor for sensing heart rate,
And a headset wireless communication unit for transmitting an EEG signal sensed by the EEG sensing unit and a heart rate signal sensed by the heart rate sensing unit via wireless communication;
The content reproduction device
A device wireless communication unit for receiving the brain wave signal and the heart rate signal transmitted from the brain wave / heart rate sensing headset via wireless communication;
A measurement state data generation unit for extracting at least one measured EEG variable and at least one measured heart rate variability from the EEG signal and the heart rate signal to generate measurement state data;
Wherein a plurality of sets of registration state data each corresponding to a plurality of person states are registered, wherein each said set of registration state data includes a plurality of registration variable combinations each comprising at least one registered EEG variable and at least one registered heart rate variable A registration data set storage unit for storing the registration data set,
A state determination unit for comparing the measurement state data with the plurality of registration state data sets to determine a current state;
And a recommended content determining unit for extracting and providing pre-registered content suitable for the current state determined by the status determining unit.
Further comprising: a pattern learning module that learns a new combination of variables using the plurality of registration state data sets registered in the registration data set storage section;
The pattern learning module
Randomly extracting variables from the registration state data sets to generate a new registered number of new variable combinations,
Extracting at least one registered variable combination matching each new variable combination through comparison of each new variable combination and the registered variable combination,
If the new combination of variables that are matched with each other and the human condition of the registered variable combination are the same, the weight of the new combination of variables is increased,
And decreasing the weight of the new variable combination when the new variable combination is matched with the mutually matching state of the registered variable combination,
And the plurality of new variable combinations having the higher weight among the new variable combinations are updated to the registration state data set.
A user log storage unit;
And a recommendation determining unit that determines whether or not the recommendation content provided by the recommendation content determining unit is reproduced based on the measurement status data generated by the measurement status data generator and the person status based on the determination result of the status determination unit, And a user log feedback unit for storing the user's log in a storage unit.
Wherein the pattern learning module registers the measurement state data and the person state stored in the user log storage unit as a new combination of variables of the corresponding registration state data set.
The state determiner
Comparing each combination of the plurality of registration variable constituting each of the registration state data sets with a combination of variables constituting the measurement state data, and assigning a weight according to the degree of similarity;
Summing the weights for each person state to calculate a state probability for each person state;
And determining a human condition on the basis of the state probability.
(a) a plurality of sets of registration state data corresponding respectively to a plurality of person states are registered in a content reproduction device, each of said registration state data sets comprising at least one registered EEG variable and at least one registered heart rate variable Registering a plurality of combinations of registration variables;
(b) detecting brain waves and heart rate through an EEG / heart rate sensing headset;
(c) transmitting an electroencephalogram signal and a heart rate signal sensed by the brainwave / heart rate sensing headset via wireless communication to the content reproduction device;
(d) extracting at least one measured EEG variable and at least one measured heart rate variability parameter from the EEG signal and the heart rate signal transmitted from the EEG / heart rate sensing headset in the contents reproducing device to generate measurement state data ;
(e) comparing the measurement state data with the plurality of registration state data sets to determine a current state;
(f) extracting and providing pre-registered contents suitable for the current state determined in step (e), and providing the extracted contents to the user.
(a1) randomly extracting a variable from the registration state data set to generate a new registered variable combination;
(a2) extracting at least one registered variable combination that matches each new variable combination through comparison of each new variable combination and the registered variable combination;
(a3) when the mutual matching of the new variable and the human condition of the registered variable combination are the same, the weight of the new variable combination is increased, and when the mutually matching new variable combination is different from the human condition of the registered variable combination Decreasing the weight of the new variable combination;
(a4) updating a plurality of new variable combinations having a high weight among the new variable combinations to a registration state data set.
(a5) performing the steps (b), (c), (d), and (e) while the recommended content is played back;
(a6) storing the measurement status data generated in the performing of the step (a5) and the human condition based on the result of the human condition determination in the performing of the step (a5) in the user log storage together with the recommended content The method of claim 1, further comprising the steps of:
(a7) registering the measurement state data and the person state stored in the user log storage unit as a new variable combination of the corresponding registration state data set;
(a8) performing the steps (a1) to (a4) after the new variable combination is registered through the step (a7). .
The step (e)
(e1) comparing each of the plurality of registration variable combinations constituting each of the registration state data sets with a combination of variables constituting the measurement state data, and assigning weights according to the degree of similarity;
(e2) summing the weights for each human condition and stating the status for each human condition;
and (e3) determining a human condition based on the state probability. The method of recommending contents based on EEG / heart rate using wireless communication.
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| Application Number | Priority Date | Filing Date | Title |
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| KR20140051843 | 2014-04-29 | ||
| KR1020140051843 | 2014-04-29 |
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| KR20150125599A KR20150125599A (en) | 2015-11-09 |
| KR101576892B1 true KR101576892B1 (en) | 2015-12-14 |
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| KR102459245B1 (en) | 2022-07-21 | 2022-10-26 | 이루미 | A system that transmits the detected EEG signal to enable EEG communication with the other party using a wireless communication network |
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| KR20190001081A (en) * | 2017-06-26 | 2019-01-04 | 서울대학교산학협력단 | APPARATUS AND METHOD FOR MEASURING BRAINWAVE AND electrocardiogram |
| KR102038997B1 (en) * | 2017-07-25 | 2019-11-01 | 유경진 | Eeg convergence-feedback system |
| KR102055554B1 (en) * | 2018-01-25 | 2019-12-13 | 유경진 | System for egg information bank and operation method thereof |
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| KR101002751B1 (en) | 2010-09-10 | 2010-12-21 | 주식회사 다이나믹플러스 | Device for education diagnosis using brain waves, education management system using the device and operating method thereof |
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