Treatment system using brainwave measurement

Abstract

The present invention relates to a treatment system using brainwaves, which comprises: a first module attached to the body of a user to measure brainwaves and generate a predetermined stimulus to the body of the user; and a second module communicating with the first module to receive biometric data including brainwaves and control the function of the first module by using the received biometric data, wherein the first module may comprise a measurement unit that obtains the biometric data by measuring brainwaves of a user and at least one biometric signal other than the brainwaves, a generation unit that generates a predetermined stimulus to the body of the user, and a communication unit that transmits the measured biometric data to the second module and receives control data for controlling the operation of the generation unit.

Description

Treatment system using brainwave measurement

[0001] The present invention relates to a treatment system using brain wave measurement, and more specifically, to a technical idea that allows an individual to easily measure brain waves whenever he or she wants through a brain wave measurement means that can be easily used by an individual, and that utilizes the pattern of the measured brain waves to distinguish between the individual's normal brain waves and the brain waves when a disease such as a headache occurs, and thereby identifies the precursors of the disease and provides the information to the user, thereby enabling a more rapid response to the symptoms of the user's disease.

[0002] Brain waves are natural electrical activity that occurs in the brain. They are electrical signals that are recorded in the cerebral cortex or scalp when signals are transmitted between brain nerves in the nervous system.

[0003] The measured brain waves can be utilized in various ways, and the most widely known uses are sleep measurement through brain wave patterns during sleep and identification of various neurological diseases (e.g., epilepsy, ADHD, common headaches, etc.).

[0004] Recently, a variety of EEG measuring devices have become widely available, enabling individuals to conveniently measure brain waves at a certain level, not just in specialized medical institutions. However, these conventional EEG measuring devices, designed for easy personal use, simply measure brain waves and provide the results.

[0005] Therefore, a technological idea is required that utilizes the measured brain wave patterns to distinguish between the user's normal brain waves and the brain waves when a disease such as a headache occurs, and thereby identify the warning signs of the disease and provide the information to the user, thereby enabling a more rapid response to the user's disease symptoms.

[0006] In addition, a technological idea is required to measure not only brain waves but also other bio-information (e.g., body temperature, pulse, blood pressure, etc.) that accompanies the disease, so that the relationship with the disease can be identified and utilized.

[0007] In addition, a technical idea is required that goes beyond simply identifying the occurrence of a disease and can provide treatment or alleviation of symptoms of the disease by generating a certain stimulus (e.g., light output, light wavelength, magnetic field, current, sound, etc.) to the user's body.

[0008] The challenge that the invention seeks to address is to provide a technical idea that utilizes the measured brainwave patterns to distinguish between the user's normal brainwaves and the brainwaves that occur when a disease such as a headache occurs, and thereby identify the warning signs of the disease and provide the information to the user, thereby enabling a more rapid response to the user's disease symptoms.

[0009] In addition, it provides a technical idea that allows for the measurement of not only brain waves but also other bio-information (e.g., body temperature, pulse, blood pressure, etc.) that accompanies a disease to identify and utilize the relationship with the disease.

[0010] In addition, it is to provide a technical idea that allows treatment of an existing disease or alleviation of symptoms by not simply determining whether a disease has occurred, but also generating a certain stimulus (e.g., light output, light wavelength magnetic field, current, sound, vibration, etc.) to the user's body.

[0011]

[0012] According to an embodiment of the present invention for achieving the above-described purpose, a treatment system using brain waves includes a first module that is attached to a user's body to measure brain waves and generate a predetermined stimulus to the user's body, and a second module that communicates with the first module to receive bio-data including the brain waves and controls the function of the first module using the received bio-data, wherein the first module comprises a measuring unit that measures the user's brain waves and at least one bio-signal other than the brain waves to obtain bio-data, a generating unit that generates a predetermined stimulus to the user's body, and

[0013] It may include a communication unit that transmits the biometric data measured by the second module and receives control data for controlling the operation of the generator.

[0014] Additionally, the biometric data may include biometric signals such as brain waves, body temperature, pulse, oxygen saturation, and blood pressure measured from the user's body.

[0015] Additionally, the second module can generate control data for controlling the generation unit based on the reference biometric data when the measurement period of the biometric data is less than or equal to a reference value.

[0016] Additionally, the second module can input the biometric data into a control model to produce control data.

[0017] Additionally, the control model can be trained to produce control data by analyzing the correlation between past control data and biosignals corresponding to the past control data.

[0018] In addition, the second module inputs biometric data received in a time series into a prediction model to produce prediction data, and the prediction data may include prognostic symptoms related to the user's disease.

[0019] Additionally, the above prediction model can be trained to predict diseases through changes in biosignals within a time series of biodata and produce prediction data.

[0020] In addition, the second module takes into account the user parameters of the user.

[0021] Control data can be generated.

[0022] Additionally, the second module can calculate a weight based on the attachment location of the first module within the user's body and reflect the weight in the control data.

[0023] Meanwhile, a treatment method using brain waves may include a step of obtaining bio-data including brain waves through a first module attached to a user's body, a step of generating control data for controlling the first module using the bio-data, and a step of generating a predetermined stimulus to the user's body based on the control data.

[0024] Meanwhile, a computer-readable recording medium according to an embodiment of the present invention for achieving the above-described purpose may store a program for performing the above-described method.

[0025] In addition, a computer program according to an embodiment of the present invention for achieving the above-described purpose may have a program code recorded therein for executing the above-described method.

[0026] According to the present invention, by utilizing the measured brain wave pattern, the user's normal brain waves and the brain waves when a disease such as a headache occurs are distinguished, and by using this, the user can be provided with the warning signs of the disease, thereby enabling a more rapid response to the user's disease symptoms.

[0027] In addition, by measuring not only brain waves but also other biometric information (e.g., body temperature, pulse, blood pressure, etc.) that accompanies the disease and using it to determine the relationship with the disease, it has the effect of allowing for more accurate identification of the occurrence of the disease.

[0028] In addition, it is effective in not only identifying the occurrence of a disease, but also in promoting treatment of the disease or alleviation of symptoms by generating a certain stimulus (e.g., light output, light wavelength, magnetic field, current, sound, vibration, etc.) to the user's body.

[0029] In addition, by accumulating and learning changes in brain waves and / or other bio-information according to the occurrence of a specific disease, it is possible to determine whether a disease occurs in a personalized manner for each user, and to provide more suitable stimulation to each user, thereby enabling personalized disease treatment or symptom relief.

[0030]

[0031] Figure 1 is a conceptual diagram illustrating a treatment system utilizing brain wave measurement according to one embodiment of the present invention. Figure 2 is a diagram illustrating an example of use of the treatment system according to one embodiment of the present invention.

[0032] Figure 3 is a block diagram showing the configuration of a treatment system according to one embodiment of the present invention.

[0033] Figure 4 is a flowchart showing a treatment method of a treatment system according to one embodiment of the present invention.

[0034] It's Tao.

[0035] The following merely exemplifies the principles of the invention. Therefore, those skilled in the art will be able to implement the principles of the invention and invent various devices within the scope and spirit of the invention, even if not explicitly described or illustrated herein. Furthermore, all conditional terms and embodiments listed herein are expressly intended, in principle, to facilitate understanding of the invention, and should be understood as being in no way limiting to the specifically enumerated embodiments and conditions.

[0036] The above-described purposes, features and advantages will become clearer through the following detailed description with reference to the attached drawings, so that a person having ordinary skill in the art to which the invention pertains can easily practice the technical idea of ​​the invention.

[0037] Furthermore, when describing the invention, detailed descriptions of known technologies related to the invention will be omitted if they are deemed to unnecessarily obscure the gist of the invention. Below, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0038] FIG. 1 is a conceptual diagram illustrating a treatment system (1000) using brain wave measurement according to one embodiment of the present invention.

[0039] Referring to FIG. 1, the treatment system (1000) can measure bio-information from the user's body and provide various functions to the user using the measured bio-information.

[0040] there is.

[0041] Such a treatment system (1000) may be composed of a first module (100) attached to one side of the user's body and a second module (200) that controls the operation of the first module.

[0042] Specifically, the first module (100) can be attached to the user's body to measure brain waves and generate a predetermined stimulus to the user's body based on the control data. Here, the first module (100) can be implemented in the form of a disk having a predetermined thickness and diameter, but is not limited thereto, and can be formed in various forms as long as it can be easily attached to a specific body part of the user as needed and can acquire the user's bio-information, including brain waves.

[0043] At this time, one side of the first module (100) has an attachment surface (101) that is attached to the user's body, and the attachment surface (101) can be formed of a material whose adhesive strength is restored when it is wiped with water when contaminants are present.

[0044] In addition, the attachment surface (101) of the first module (100) may be modified in position and size depending on the shape of the first module. In addition, the first module (100) may be attached to one side of the user's body through the attachment surface (101) described above, and, if necessary, the first module (100) may be formed in multiple pieces and each may be attached to the user's body.

[0045] Additionally, the first module (100) may transmit biometric data including measured biometric information to the second module (200) or may transmit and receive messages, signals, data and / or information.

[0046] For example, the first module (100) is low on battery, biometric data measurement is complete

[0047] Messages or signals such as these may also be transmitted to the second module (200).

[0048] In addition, the second module (200) can communicate with the first module (100) to receive biometric data including the user's brain waves, and control the function of the first module (100) using the received biometric data. Here, the second module (200) can be implemented as an application of a user terminal and connected to the first module (100), and depending on an implementation example, the first module (100) and the second module (200) can be implemented in one form.

[0049] At this time, the second module (200) can provide the received biometric data through a user interface.

[0050] Additionally, the second module (200) transmits messages, signals, data and / or

[0051] Or you can send and receive information.

[0052] For example, the second module (200) can communicate with the first module (100) to transmit biometric data and control data or transmit location notifications, etc.

[0053] Next, an example of use of the treatment system (1000) will be described with reference to FIG. 2.

[0054] Figure 2 is an example of use of a treatment system (1000) according to one embodiment of the present invention.

[0055] This is a diagram showing .

[0056] Referring to FIG. 2, the first module (100: 100-1, 100-2, 100-3) of the treatment system (1000) can be implemented in multiple units as needed.

[0057] In this example, the first module (100-1) is attached to the temple of the user (20).

[0058] It can measure the user's bio-signals such as brain waves, body temperature, pulse, and blood pressure.

[0059] In addition, the first module (100-2, 100-3) can be attached to the neck and hand of the user (20) to measure the user's bio-signals such as body temperature, pulse, blood pressure, etc. In this case, if the first module (100) is attached to the user's temple, forehead, nape of the neck, etc., it can be easy to measure the user's body temperature, pulse, etc.

[0060] And, bio-data including bio-signals measured in the first module (100: 100-1, 100-2, 100-3) are transmitted to the second module (200), and the second module (200) can provide a user interface based on the bio-data. At this time, the user interface can visualize and display the user's current bio-data, time-series bio-data, current health status, disease precursor symptoms, etc.

[0061] Additionally, the second module (200) can generate control data based on biometric data and transmit it to the first module (100: 100-1, 100-2, 100-3).

[0062] Meanwhile, in this example, three first modules (100) are shown, but if necessary,

[0063] It can be implemented with more first modules (100).

[0064] In this way, the first module (100) can be implemented in multiple units, and the width of the biosignal measurement can be increased through the biosignal of the user obtained from each of the multiple first modules (100).

[0065] This widening and increasing accuracy can lead to improved diagnostic accuracy.

[0066] Next, referring to FIG. 3, each configuration and configuration of the treatment system (1000)

[0067] Describe the movement.

[0068] Figure 3 is a block diagram showing the configuration of a treatment system (1000) according to one embodiment of the present invention.

[0069] Referring to FIG. 3, the first module (100) of the treatment system (1000) has a first communication unit

[0070] (110), a measuring unit (120), and a generating unit (130), and the second module (200) is a second communication

[0071] It can be composed of a unit (210), a control data generation unit (220), and a database (230).

[0072] First, let's explain the configuration of the first module (100). The first communication unit (110) is the second

[0073] A device for transmitting biometric data from a module (200) and controlling the operation of a generator (130)

[0074] Oh, you can receive data.

[0075] In addition, the measuring unit (120) can measure the user's bio-signal to obtain bio-data containing various bio-information.

[0076] According to an implementation example, the measuring unit (120) can acquire biometric data by measuring at least one biometric signal other than the user's brain waves and brain waves. Here, the biometric signals other than brain waves may include body temperature, pulse, oxygen saturation, sound, and blood pressure. In this case, the biometric signals measured by the measuring unit (120) may vary depending on the attachment location.

[0077] This measuring unit (120) can be implemented with various sensors such as an electrode-type EEG sensor, an infrared sensor, a Markov sensor, an oxygen saturation sensor, a magnetic field sensor, an optical sensor, an illuminance sensor, etc. to measure various biosignals.

[0078] In addition, when implemented with a plurality of first modules (100), the user's bio-signal is measured in each measuring unit (120) of the first modules (100), and each measured bio-signal is

[0079] Biometric data can be obtained through the neural network model. At this time, each measured

[0080] Biometric data can be generated from biometric signals.

[0081] At this time, the neural network model generates bio data by considering the inconsistency or noise between bio signals measured from multiple measurement units (120) and the characteristics between measurement sensors.

[0082] It may be learned.

[0083] This allows us to expand the range of signal measurements and improve accuracy.

[0084] This can improve the accuracy of diagnosis of the user's disease.

[0085] The occurrence part (130) is used to treat a specific disease or a specific disease depending on the occurrence of a specific disease.

[0086] It can cause certain stimulation to the user's body to alleviate the symptoms of the disease.

[0087] Specifically, the generator (130) can change the intensity, wavelength, etc. of the output based on the control data according to the type of stimulus (e.g., magnetic field, current, light, etc.) and determine whether the brain waves and / or bio-information in a state where a specific disease has occurred are close to the brain waves and / or bio-information in normal conditions, thereby enabling treatment or alleviation of symptoms for a specific disease.

[0088] For example, the generator (130) of the first module (100) can generate a stimulus to the user's body by outputting light of a specific wavelength, a magnetic field, and / or a certain level of current. In this way, at least one type of stimulus that can be generated by the generator (130) can be selectively generated as needed.

[0089] In addition, when implemented with multiple first modules (100), each generating unit (130) can provide stimulation to the user based on control data. Through this,

[0090] It can provide effective treatment to users.

[0091] Next, the configuration of the second module (200) will be described. The second communication unit (120) can receive biometric data from the first module (100) and transmit control data for controlling the operation of the generation unit (130).

[0092] In addition, the control data generation unit (220) can generate control data for controlling the operation of the generation unit (130) based on the biometric data. At this time, biometric data measured before and after stimulation through the generation unit (130) can be used as the biometric data.

[0093] Specifically, the control data generation unit (220) can generate control data based on reference biometric data when the measurement period of the biometric data is less than or equal to a reference value. Here, the reference biometric data may be the average biometric data of other users with similar physical conditions to the user.

[0094] Furthermore, the reference value here can be variably determined depending on the type of biometric information. Furthermore, if the measurement period is below the reference value, the control data generation unit (220) can generate control data with maximum output within the possible range for all possible stimuli or use initial control data. Here, the initial control data can be a setting value (e.g., intensity) determined through past statistics or papers.

[0095] That is, the control data generation unit (220) can generate control data based on the average user's biometric data or use initial control data when individual biometric data has not been accumulated to a certain extent (e.g., at the beginning after attachment).

[0096] Additionally, the control data generation unit (220) can input biometric data into a control model to produce control data. Here, the control model is trained to produce control data by analyzing the correlation between past control data and biometric signals corresponding to the past control data, and a deep learning model such as an autoencoder can be used as the control model.

[0097] At this time, the control model continuously learns through the continuous biometric data of the user, thereby learning which type of stimulation and in which form among the stimulations of the above-described generating unit (130) is generated to cure the disease or alleviate the symptoms, and can generate control data to selectively generate a stimulation suitable for the treatment or alleviation of the symptoms of the disease that has occurred in the user.

[0098] Additionally, the control data generation unit (220) can generate control data by considering the user parameters of the user. Here, the user parameters may include the user's personal preferences, environment, and settings.

[0099] In addition, the control data generation unit (220) can calculate a weight according to the attachment location of the first module (100) within the user's body and reflect the weight in the control data.

[0100] In addition, the control data generation unit (220) can calculate weights according to the user's behavioral situation (walking situation, exercising situation, lying down situation, etc.) and reflect the weights in the control data.

[0101] Additionally, the control data generation unit (220) can calculate a weight based on the attachment status of the first module (100) and reflect the weight in the control data. Here, the attachment status refers to a state in which the first module (100) is attached, and can be determined through multiple sensors included in the first module (100).

[0102] For example, attachment situations may include attachment to bare skin, attachment over clothing, and specific situations where attachment is to a hairy area.

[0103] In addition, the control data generation unit (220) can calculate a weight according to the operating status of the first module (100) and reflect the weight in the control data. Here, the operating status means the operating status of the first module (100), and the operating status can include the battery status of the first module (100), the communication status, and the availability status of the generation unit (130) (whether it is broken, maximum strength, etc.).

[0104] That is, the control data generation unit (220) can correct the generated control data by generating weights according to various situations. In addition, the control data generation unit (220) can also generate control data by considering the user's control input. For example, if a control input for lowering the intensity is received from the user, the control data generation unit (220) can generate control data so that the generation unit (130) generates a stimulus at the corresponding intensity.

[0105] Additionally, the control data generation unit (220) can use biometric data to determine the user's disease symptoms and generate prediction data. At this time, the prediction data may include the user's disease symptoms, probability, etc.

[0106] Specifically, the control data generation unit (220) can input biometric data received in a time series into a prediction model to produce prediction data. At this time, the prediction model is trained to predict diseases through changes in biometric signals within the time series of biometric data and produce prediction data, and a long short-term memory (LSTM), a recurrent neural network (RNN) for time series prediction, etc. can be used.

[0107] For example, when a user experiences a headache, the prediction model learns how brain waves change at the time of headache occurrence (e.g., the time when the user perceives a headache) compared to normal brain waves based on brain waves measured in a time series, and can determine whether the user experiences a headache through changes in brain waves measured by the first module (100).

[0108] Next, the operation method of the treatment system (1000) will be described with additional reference to FIG. 4.

[0109] Figure 4 is a flowchart showing a treatment method of a treatment system (1000) according to one embodiment of the present invention.

[0110] Referring to FIG. 4, the treatment system (1000) can acquire bio-data by measuring at least one of the user's brain waves and other bio-signals other than brain waves (S100). Here, the bio-signals other than brain waves may include body temperature, pulse, oxygen saturation, and blood pressure. Next, the treatment system (1000) can generate control data using the bio-data (S200). At this time, if individual bio-data is not accumulated (for example, at the beginning after attachment), the treatment system (1000) can generate control data based on the average user's bio-data.

[0111] You can generate control data or use initial control data.

[0112] And, the treatment system (1000) is based on the generated control data.

[0113] A stimulus can be generated (S300). At this time, the treatment system (1000) is based on the control data.

[0114] It can provide the user with stimuli such as light output, magnetic field, current sound, etc.

[0115] Thereafter, the treatment system (1000) can obtain biometric data corresponding to the stimulus and generate control data based on the biometric data to generate a stimulus to the user.

[0116] That is, the treatment system (1000) learns what type of stimulus and in what form causes a disease to be cured or symptoms to be alleviated, and can provide the user with a stimulus suitable for the treatment or alleviation of symptoms of the disease.

[0117] According to the treatment system (1000) described above, the brainwave patterns measured are utilized to distinguish between the user's normal brainwaves and the brainwaves when a disease such as a headache occurs, and by identifying the warning signs of the disease and providing them to the user, there is an effect of being able to respond to the user's disease symptoms more quickly.

[0118] In addition, the treatment system (1000) has the effect of more accurately determining whether a disease has occurred by measuring not only brain waves but also other bio-information (e.g., body temperature, pulse, blood pressure, etc.) that accompanies the disease to determine and utilize the relationship with the disease.

[0119] In addition, the treatment system (1000) not only simply determines whether a disease has occurred, but also has the effect of promoting treatment of the disease or alleviation of symptoms by generating a certain stimulus (e.g., light output, light wavelength, magnetic field, current, sound, vibration, etc.) to the user's body.

[0120] In addition, the treatment system (1000) accumulates and learns changes in brain waves and / or other bio-information according to the occurrence of a specific disease, thereby enabling the user to determine whether a disease has occurred in a personalized manner and to apply a more suitable stimulus to the user, thereby enabling personalized treatment of the disease or alleviation of symptoms.

[0121] Meanwhile, the treatment method of the treatment system (1000) according to an embodiment of the present invention may be implemented in the form of a computer-readable program command and stored in a computer-readable recording medium, and the control program and target program according to an embodiment of the present invention may also be stored in a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system.

[0122] In terms of hardware implementation, the embodiments described herein are ASICs

[0123] (application specific integrated circuits), DSPs (digital signal processors),

[0124] DSPDs (digital signal processing devices), PLDs (programmable logic devices),

[0125] FPGAs (field programmable gate arrays, processors, controllers)

[0126] (controllers), microcontrollers, microprocessors

[0127] (microprocessors), and at least one electrical unit for performing other functions. In some cases, the embodiments described herein may be implemented as a control module itself.

[0128] In a software implementation, the procedures and functions described herein, as well as other embodiments, may be implemented as separate software modules. Each of these software modules may perform one or more of the functions and operations described herein. The software code may be implemented as a software application written in a suitable programming language. The software code may be stored in a memory module and executed by a control module.

[0129]

[0130] The above description is merely an example of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications, changes, and substitutions can be made without departing from the essential characteristics of the present invention.

[0131] Accordingly, the embodiments disclosed in the present invention and the accompanying drawings are intended to illustrate, rather than limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments and the accompanying drawings. The scope of protection of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included within the scope of the rights of the present invention.

[0132] A personalized health management service can be provided through a treatment system using brain wave measurement.

Claims

1. In a treatment system using brain waves, It is attached to the user's body to measure brain waves and send a certain amount of signals to the user's body. A first module that generates a pole; and Communicate with the above first module to receive biometric data including brain waves, and A second module that controls the function of the first module using the received biometric data; And, The above first module records the user's brain waves and other biosignals other than the brain waves. A measuring unit for obtaining biometric data by measuring one or more degrees; A generating unit that generates a predetermined stimulus to the user's body; and Transmits the biometric data measured by the second module and controls the operation of the generator. A treatment system comprising a communication unit for receiving control data for performing the treatment.

2. In paragraph 1, The above biometric data includes brain waves, body temperature, pulse, and oxygen saturation measured from the user's body. A treatment system characterized by including biosignals of saturation and blood pressure.

3. In the first paragraph, the second module measures the biometric data when the measurement period is less than or equal to the reference value. Generating control data for controlling the above-mentioned generating unit based on quasi-biometric data A treatment system featuring:

4. In paragraph 1, The second module inputs the biometric data into the control model to generate control data. A treatment system characterized by producing.

5. In paragraph 4, The above control model is based on past control data and the generation corresponding to the past control data. It is characterized by being trained to produce control data by analyzing the correlation between body signals. A treatment system that uses 6. In paragraph 4, The second module above inputs the biometric data received in time series into the prediction model and makes a prediction. Produce data, The above prediction data includes prognostic symptoms related to the user's disease. A treatment system featuring:

7. In paragraph 6, The above prediction model is based on changes in biosignals within a time series of biodata. A therapeutic system characterized by being trained to predict a disease and produce predictive data. Temp. In paragraph 8.1, The second module controls data by considering the user parameters of the user. A treatment system characterized by generating.

9. In paragraph 1, The above second module is weighted according to the attachment location of the first module within the user's body. A treatment method characterized by calculating the weight and reflecting the weight in the control data. Stem.

10. In the treatment method using brain waves, Obtaining biometric data including brain waves through the first module attached to the user's body Steps to do; A step of generating control data for controlling the first module using the above biometric data; and Generates a predetermined stimulus to the user's body based on the above control data. A treatment method comprising:

11. A computer-readable program storing a program for performing the treatment method described in Article 10. A recording medium.

12. The treatment method described in Article 10 is stored in a computer-readable recording medium. A computer program containing program code for performing a task.

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