Electronic device, method, and non-transitory computer-readable storage medium for amplifying signal resulting from brain wave measuring

Abstract

This electronic device may comprise: a communication circuit; a memory storing instructions; and at least one processor. The instructions, when executed individually or collectively by the at least one processor, may instruct the electronic device to: receive data acquired as a result of brain wave measuring performed by another electronic device; from the received data, identify first data resulting from the brain wave measuring performed in a first time interval; identify second data resulting from the brain wave measuring performed in a second time interval; by using the first data, identify third data which is related to at least one frequency band; by using the second data, identify fourth data which is related to the at least one frequency band; and, on the basis of the fourth data which is outside of a reference range, transmit, to the other electronic device, a request to increase a gain value for amplifying the magnitude of a signal acquired in the other electronic device as a result of the brain wave measuring.

Description

Electronic device, method, and non-transient computer-readable storage medium for amplifying signals based on brainwave measurement

[0001] The following descriptions relate to an electronic device, a method, and a non-transient computer-readable storage medium for amplifying a signal based on brainwave measurement.

[0002] Brain waves refer to electrical signals generated by the electrical activity of the neurons that make up the brain. Brain waves can be measured through various methods. For example, brain wave measurement can be performed using sensors. Brain wave measurement can be referred to as EEG (electroencephalography). For example, the measured brain waves can be used to analyze a user's biological state.

[0003] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure.

[0004] The electronic device may include a communication circuit. The electronic device may include a memory that stores instructions and includes one or more storage media. The electronic device may include at least one processor that includes a processing circuit. The instructions may cause the electronic device to receive data acquired according to an electroencephalogram (EEG) measurement performed by another electronic device when the at least one processor is executed individually or collectively. The instructions may cause the electronic device to identify first data according to the EEG measurement performed within a first time interval from the received data when the at least one processor is executed individually or collectively. The instructions may cause the electronic device to identify second data according to the EEG measurement performed within a second time interval following the electronic device when the instructions of the first time interval are executed individually or collectively by the at least one processor. The above instructions may cause the electronic device to identify third data related to at least one frequency band using the first data when the at least one processor is executed individually or collectively. The above instructions may cause the electronic device to identify fourth data related to at least one frequency band using the second data when the at least one processor is executed individually or collectively.The above instructions may cause the electronic device to transmit a request to the other electronic device through the communication circuit to increase a gain value for amplifying the magnitude of a signal acquired within the other electronic device according to the brainwave measurement, based on the fourth data which is outside the reference range in relation to the third data, when the at least one processor is executed individually or collectively. The above instructions may cause the electronic device to refrain from transmitting the request to the other electronic device through the communication circuit, based on the fourth data which is within the reference range in relation to the third data, when the at least one processor is executed individually or collectively.

[0005] A method performed by an electronic device having a communication circuit may include the operation of receiving data obtained according to brainwave measurements performed by said other electronic device from said other electronic device through said communication circuit. The method may include the operation of identifying first data according to said brainwave measurements performed within a first time interval and second data according to said brainwave measurements performed within a second time interval following said first time interval. The method may include the operation of identifying third data related to at least one frequency band using said first data and the operation of identifying fourth data related to said at least one frequency band using said second data. The method may include the operation of transmitting a request to said other electronic device through said communication circuit to increase a gain value for amplifying the magnitude of a signal obtained within said other electronic device according to said brainwave measurements, based on said fourth data which is outside a reference range in relation to said third data. The method may include the operation of refraining from transmitting said request to said other electronic device through said communication circuit based on said fourth data which is within the reference range in relation to said third data.

[0006] A non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by an electronic device having a communication circuit, cause the electronic device to receive data acquired according to a brainwave measurement performed by another electronic device through the communication circuit. The non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify from the data first data according to the brainwave measurement performed within a first time interval and second data according to the brainwave measurement performed within a second time interval following the first time interval. The non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify third data associated with at least one frequency band using the first data. The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify fourth data associated with the at least one frequency band using the second data. The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to transmit to the other electronic device through the communication circuit a request to increase a gain value for amplifying the magnitude of a signal acquired within the other electronic device according to the brainwave measurement, based on the fourth data which is outside the reference range in relation to the third data.The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to refrain from transmitting the request to the other electronic device through the communication circuit based on the fourth data within the reference range in relation to the third data.

[0007] Figure 1 illustrates the operation of processing an analog signal.

[0008] Figure 2 illustrates a graph showing data converted from an analog signal according to the gain value applied to the analog signal input to the amplifier based on brainwave measurement.

[0009] Figure 3 illustrates a graph showing the magnitude of data converted from an analog signal output from an amplifier based on applying a gain value to an analog signal input to an amplifier according to brainwave measurement.

[0010] FIG. 4 illustrates a simplified block diagram of an electronic device and a simplified block diagram of another electronic device.

[0011] Figure 5a illustrates an example of another electronic device used for measuring brain waves.

[0012] Figure 5b illustrates an example of a sensor circuit of another electronic device.

[0013] Figure 6 is a flowchart illustrating a method performed within an electronic device to adjust gain values.

[0014] FIG. 7 illustrates the operation flow of a method for an electronic device to identify third data using first data and a method for identifying fourth data using second data.

[0015] FIGS. 8A and FIGS. 8B illustrate graphs representing third and fourth data identified based on received data.

[0016] FIG. 9 illustrates the operation flow of a method for identifying whether the fourth data is within a reference range in relation to the third data.

[0017] FIG. 10a illustrates the operation flow of a method for displaying information that guides the user's condition in relation to brainwave measurement.

[0018] FIG. 10b illustrates a method for measuring a user's brainwaves performed by another electronic device and adjusting gain values ​​performed by an electronic device.

[0019] FIG. 11a illustrates user guide information displayed by an electronic device through a display in a meditation scenario.

[0020] FIG. 11b illustrates user guide information displayed by an electronic device through a display in a concentration scenario.

[0021] Figure 12 illustrates an example of a screen showing the analysis results of measured brain waves.

[0022] FIG. 13 is a block diagram of an electronic device in a network environment according to various embodiments.

[0023] The terms used in this disclosure are used merely to describe specific embodiments and are not intended to limit the scope of this disclosure. A singular expression may include a plural expression unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by those skilled in the art described in this disclosure. Terms used in this disclosure that are defined in a general dictionary may be interpreted as having the same or similar meaning as they have in the context of the relevant technology, and are not to be interpreted in an ideal or overly formal sense unless explicitly defined in this disclosure. In some cases, even terms defined in this disclosure are not to be interpreted to exclude the embodiments of this disclosure.

[0024] Additionally, in this disclosure, expressions such as "greater than" or "less than" may be used to determine whether a specific condition is satisfied or fulfilled; however, this is merely for the purpose of expressing an example and does not exclude descriptions such as "greater than" or "less than." Conditions described as "greater than" may be replaced with "greater than," conditions described as "less than" may be replaced with "less than," and conditions described as "greater than and less than" may be replaced with "greater than and less than."

[0025] Figure 1 illustrates the operation of processing an analog signal.

[0026] Referring to FIG. 1, an analog signal (101) may be obtained through or according to brainwave measurement. For example, the analog signal (101) may be described as a signal obtained through electrodes that are in contact (or attached, or separated) with a part of the user's body. Obtaining the analog signal (101) through attached electrodes may include obtaining the analog signal (101) through electrodes that are in direct contact with a part of the user's body. Obtaining the analog signal (101) through separated electrodes may include obtaining the analog signal (101) through electrodes that are not in contact with a part of the user's body. The analog signal (101) obtained through electrodes that are in contact with a part of the user's body may correspond to or represent the user's brainwaves.

[0027] For example, brain waves may refer to electrical signals generated by the electrical activity of the neurons constituting the brain. For example, the electrical activity of the neurons may include the electrical activity of the neurons when the user closes their eyes, and the electrical activity of the neurons when the user receives visual stimuli. By example, without limitation, the brain waves may be measured by the electrodes in contact with a part of the user's body. The measurement of brain waves may be referred to as electroencephalography (EEG). By example, without limitation, the part of the body may include the scalp, ears, and / or forehead.

[0028] An analog signal (101) may be input to an amplifier (102). The amplifier (102) may adjust the amplitude of the analog signal (101) input to the amplifier (102) and output an analog signal (105) which is an analog signal (101) having the adjusted amplitude. The amplifier (102) may include an amplification circuit. For example, the amplification circuit may include a programmable gain-amplifier (PGA). However, the amplification circuit of the present disclosure is not limited to a PGA. For example, the amplification circuit may include other types of amplification circuits distinct from a PGA. For example, the amplifier (102) may increase, decrease, and / or maintain the amplitude of the analog signal (101) based on a gain value. For example, the amplifier (102) can increase the amplitude of the analog signal (101) to a first amplitude based on a first gain value, and increase the amplitude of the analog signal (101) to a second amplitude lower than the first amplitude based on a second gain value lower than the first gain value.

[0029] For example, the analog signal (101) obtained from the user may have a relatively small amplitude. Since the amplitude of the analog signal (101) is relatively small, amplification of the measured brainwave through an amplifier (102) may be performed. For example, amplifying the amplitude of the measured brainwave through an amplifier (102) may be performed to recognize the state of the user.

[0030] An analog signal (105) output from an amplifier (102) can be input to an analog-to-digital converter (ADC) (103). The ADC (103) can convert the analog signal (105) input to the ADC (103) into data (104), which is a digital signal corresponding to the analog signal (105) input to the ADC (103). For example, if the analog signal (105) input to the ADC (103) represents a user's brainwave, the converted data (104) can represent information about the brainwave. For example, the information about the brainwave can represent the magnitude of the data (104) converted from the amplitude of the analog signal (105) amplified by the amplifier (102).

[0031] Data (104) output from the ADC (103) can be input to a processor (106). The processor (106) can perform processing (or computation) based on the data (104) input to the processor (106). Data (107) output from the processor (106) can be generated based on the data (104) according to the processing of the processor (106). The processing may include processing (or computation) to generate a value for recognizing the user's state. For example, the processor (106) can output data (107) corresponding to a defined value by processing the value of the input data (104). The defined value may be defined to recognize the user's state (or biological state) using the brainwaves. For example, if the input data (104) contains information about brainwaves, the processor (106) can output data (107) for recognizing the user's state (or biological state) using the brainwaves.

[0032] As described above, in order to recognize the user's state, it may be necessary to amplify the analog signal (101) through the amplifier (102). For example, the gain value of the PGA may affect the data (104) converted from the amplified analog signal (105). Specific details regarding the data (104) will be explained below with reference to FIGS. 2 and FIGS. 3.

[0033] Figure 2 illustrates a graph showing data converted from an analog signal according to the gain value applied to the analog signal input to the amplifier based on brainwave measurement.

[0034] Referring to FIG. 2, the horizontal axis of each of the graphs (210, 220, 230, 240) represents time, and the vertical axis of each of the graphs (210, 220, 230, 240) represents power spectrum density (PSD). Graph (210) may include a line (211). The line (211) may include a first line (211-1) representing a rest state and a second line (211-2) representing an action state. Graph (220) may include a line (221). The line (221) may include a first line (221-1) representing a rest state and a second line (221-2) representing an action state. Graph (230) may include a line (231). Line (231) may include a first line (231-1) indicating a rest state and a second line (231-2) indicating an action state. Graph (240) may include line (241). Line (241) may include a first line (241-1) indicating a rest state and a second line (241-2) indicating an action state.

[0035] The above rest state may include a default state of the user. For example, the default state of the user may include a state in which the user does not move while keeping their eyes open. The above action state may include a state in which the user performs a defined action. For example, the defined action may include the action of the user closing their eyes. The above rest state and the above action state are not limited to those exemplified. Specific details regarding the above rest state and the above action state are described below with reference to FIGS. 11a and FIGS. 11b.

[0036] Line (211) of graph (210) indicates the magnitude of data (104) converted by the ADC (103) from an analog signal (105) output based on a gain value (e.g., 3) set in the amplifier (102). Line (221) of graph (220) indicates the magnitude of data (104) converted by the ADC (103) from an analog signal (105) output based on a gain value (e.g., 5) set in the amplifier (102). Line (231) of graph (230) indicates the magnitude of data (104) converted by the ADC (103) from an analog signal (105) output based on a gain value (e.g., 6.5) set in the amplifier (102). Line (241) of the graph (240) represents the magnitude of the data (104) converted by the ADC (103) from the analog signal (105) output based on the gain value (e.g., 9) set in the amplifier (102).

[0037] Referring to line (221) of graph (220) and line (211) of graph (210), the difference between the first line (221-1) and the second line (221-2) represented by line (221) may be greater than the difference between the first line (211-1) and the second line (211-2) represented by line (211). For example, the difference between the maximum size of the first line (221-1) and the maximum size of the second line (221-2) may be greater than the difference between the maximum size of the first line (211-1) and the maximum size of the second line (211-2).

[0038] Since the difference between the first line (221-1) and the second line (221-2) represented by line (221) is greater than the difference between the first line (211-1) and the second line (211-2) represented by line (211), applying a gain value (e.g., 5) to the amplifier (102) may be more suitable for recognizing the user's state than applying a gain value (e.g., 3) to the amplifier (102).

[0039] Referring to line (231) of graph (230) and line (221) of graph (220), the difference between the first line (231-1) and the second line (231-2) represented by line (231) may be greater than the difference between the first line (221-1) and the second line (221-2) represented by line (221). For example, the difference between the maximum size of the first line (231-1) and the maximum size of the second line (231-2) may be greater than the difference between the maximum size of the first line (221-1) and the maximum size of the second line (221-2).

[0040] Since the difference between the first line (231-1) and the second line (231-2) represented by line (231) is greater than the difference between the first line (221-1) and the second line (221-2) represented by line (221), applying a gain value (e.g., 6.5) to the amplifier (102) may be more suitable for recognizing the user's state than applying a gain value (e.g., 5) to the amplifier (102).

[0041] Referring to line (241) of graph (240) and line (231) of graph (230), the difference between the first line (241-1) and the second line (241-2) represented by line (241) may be greater than the difference between the first line (231-1) and the second line (231-2) represented by line (231). For example, the difference between the maximum size of the first line (241-1) and the maximum size of the second line (241-2) may be greater than the difference between the maximum size of the first line (231-1) and the maximum size of the second line (231-2).

[0042] Since the difference between the first line (241-1) and the second line (241-2) represented by line (241) is greater than the difference between the first line (231-1) and the second line (231-2) represented by line (231), applying a gain value (e.g., 9) to the amplifier (102) may be more suitable for recognizing the user's state than applying a gain value (e.g., 6.5) to the amplifier (102).

[0043] In other words, the higher the gain value set in the amplifier (102), the more suitable an analog signal (105) can be obtained to recognize the state of the user.

[0044] Figure 3 illustrates a graph showing the magnitude of data converted from an analog signal output from an amplifier based on applying a gain value to an analog signal input to an amplifier according to brainwave measurement.

[0045] Referring to FIG. 3, the horizontal axis of the graph (300) represents time, and the vertical axis of the graph (300) represents voltage (unit: μV [micro voltage]).

[0046] The line (302) in the graph (300) represents the magnitude of the data (104) converted by the ADC (103) from the analog signal (105) output based on the first gain value (e.g., 1.6) set in the amplifier (102).

[0047] The line (304) in the graph (300) represents the magnitude of the data (104) converted by the ADC (103) from the analog signal (105) output based on the second gain value (e.g., 4) set in the amplifier (102).

[0048] The line (306) in the graph (300) represents the magnitude of the data (104) converted by the ADC (103) from the analog signal (105) output based on the third gain value (e.g., 6.5) set in the amplifier (102).

[0049] The line (308) in the graph (300) represents the threshold size of the data (104).

[0050] For example, the threshold size may be used to determine whether the data (104) converted by the ADC (103) is available. For example, the threshold size may be determined based on the range of the driving voltage of the ADC (103). For example, if the range of the driving voltage of the ADC (103) increases, the threshold size may increase. For example, if the size of the data (104) output from the ADC (103) is greater than the threshold size, the data (104) may become saturated. If the data (104) becomes saturated, the acquired data (104) may be unavailable based on the gain value applied to the analog signal (105) input to the ADC (103). When the size of the data (104) output from the ADC (103) is smaller than the threshold size, the data (104) is not saturated, so the data (104) obtained based on the gain value applied to the analog signal (105) input to the ADC (103) can be used.

[0051] For example, if the data (104) is larger than the threshold size, recognizing the user's state based on the data (104) may not be available. If the data (104) is smaller than the threshold size, recognizing the user's state based on the data (104) may be available.

[0052] For example, the change over time in the magnitude of the data represented by line (306) (e.g., data converted from an analog signal to which the third gain value is applied) may be greater than the change over time in the magnitude of the data represented by line (302) (e.g., data converted from an analog signal to which the first gain value is applied) and the change over time in the magnitude of the data represented by line (304) (e.g., data converted from an analog signal to which the second gain value is applied). The data represented by line (306) may be more suitable for recognizing the state of the user than the data represented by line (302) and the data represented by line (304). However, since the data represented by line (306) has a size closer to the threshold size than the data represented by line (302) and the data represented by line (304), the probability that recognizing the state of the user based on the data represented by line (306) is unavailable may be higher than the probability that recognizing the state of the user based on the data represented by line (302) and the data represented by line (304) is unavailable.

[0053] As described with reference to FIGS. 2 and 3, the higher the gain value set in the amplifier (102), the more suitable the analog signal (105) is obtained for recognizing the state of the user; however, as the gain value is higher, the probability of being unable to recognize the state of the user may increase as the size of the data (104) obtained from the analog signal (105) becomes saturated. Therefore, the data (104) needs to be obtained from the analog signal (105) to which the highest gain value is applied within the available range for recognizing the state of the user. The available range may represent a case where the size of the data (104) converted from the analog signal (105) is smaller than the threshold size. Hereinafter, the apparatus, method, and storage medium according to embodiments of the present disclosure may adjust the gain value set in the amplifier (102) to enable recognition of the state of the user within the available range by analyzing the measured brainwave (or analog signal (101)).

[0054] FIG. 4 illustrates a simplified block diagram of an electronic device and a simplified block diagram of another electronic device.

[0055] Referring to FIG. 4, the electronic device (400) may include at least one processor (401), a display (402), a communication circuit (403), and a memory (404). The components (e.g., at least one processor (401), a display (402), a communication circuit (403), and a memory (404) are merely exemplary. For example, the electronic device (400) may include other components (e.g., a PMIC (power management integrated circuitry)). For example, some components may be omitted from the electronic device (400). The electronic device (400) of FIG. 4 may be an example of the electronic device (1301) of FIG. 13.

[0056] At least one processor (401) may be implemented as one or more integrated circuitry (IC) chips and may perform various data processing operations. At least one processor (401) may include at least one electrical circuit and may process instructions (or programs, data) stored in memory (404) individually or collectively in a distributed manner. At least one processor (401) may include a processor assembly including one or more processing circuits. At least one processor (401) may include any processing circuit that is operational to control the performance and operations of one or more components of the electronic device (400) (e.g., memory (404) and / or display (402)). For example, at least one processor (401) (e.g., application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or a set of chips). For example, at least one processor (401) may be implemented with multiple cores (or multiple core circuits), multiple chips, or multiple sets of chips. For example, at least one processor (401) may include one or more processing circuits configured to perform the various functions of the present disclosure individually and / or collectively.

[0057] For example, at least one processor (401) may include a central processing unit (e.g., including processing circuits) and a graphic processing unit (e.g., including processing circuits). The components of at least one processor (401) (e.g., CPU and GPU) are merely exemplary. The GPU may be used for the execution of a trained model. For example, the trained model may be stored in memory (404) (or electronic device (400)). The at least one processor (401) of FIG. 4 may be substantially the same as the processor (1320) of FIG. 13.

[0058] At least one processor (401) can cause other components of the electronic device (400) to perform various operations by executing instructions stored in memory (404). For example, a CPU (or central processing circuit) may be configured to control other components of at least one processor (401) (e.g., GPU) based on the execution of instructions stored in memory (404).

[0059] According to one embodiment, a display (402) of an electronic device (400) can output visualized information to a user of the electronic device (400). For example, the display (402) can be controlled by at least one processor (401) including circuits such as a CPU and / or a GPU (graphic processing unit) to output visualized information to a user. Specific details regarding the display (402) of FIG. 4 may be an example of the display module (1360) of FIG. 13.

[0060] According to one embodiment, a communication circuit (403) of an electronic device (400) may include hardware for supporting the transmission and / or reception of electrical signals between the electronic device (400) and another electronic device (410). The transmission and / or reception of electrical signals between the electronic device (400) and another electronic device (410) may be performed in the manner of wired communication (420) and / or wireless communication (430). The communication circuit (403) may include, for example, at least one of a modem (modulator and demodulator), an antenna, and an optic / electronic converter. The communication circuit (403) may support the transmission and / or reception of electrical signals based on various types of communication means such as Ethernet, Bluetooth, BLE (Bluetooth Low Energy), ZigBee, LTE (Long Term Evolution), and 5G NR (New Radio). Specific details regarding the communication circuit (403) of FIG. 4 may be an example of the communication module (1390) of FIG. 13.

[0061] According to one embodiment, a memory (404) of an electronic device (400) may include a hardware component for storing data and / or instructions that are input to or / or output from at least one processor (401). The memory may include, for example, a volatile memory such as RAM (random-access memory) and / or a non-volatile memory such as ROM (read-only memory). The volatile memory may include, for example, at least one of DRAM (dynamic RAM), SRAM (static RAM), Cache RAM, and PSRAM (pseudo SRAM). The non-volatile memory may include, for example, at least one of PROM (programmable ROM), EPROM (erasable PROM), EEPROM (electrically erasable PROM), flash memory, a hard disk, a compact disk, and an eMMC (embedded multimedia card).

[0062] According to one embodiment, within the memory (404) of the electronic device (400), one or more instructions (or commands) representing operations and / or operations to be performed on data by at least one processor (401) of the electronic device (400) may be stored. A set of one or more instructions may be referred to as a program, firmware, operating system, process, routine, sub-routine, and / or application. Hereinafter, the statement that an application is installed within the electronic device (e.g., electronic device (400)) may mean that one or more instructions provided in the form of an application are stored within the memory (404), and that said one or more applications are stored in an executable format (e.g., a file having an extension specified by the operating system of the electronic device (400)) by the processor of the electronic device. According to one embodiment, the electronic device (400) may execute one or more instructions stored in the memory (404) to perform the operations of FIGS. 6, FIGS. 7, FIGS. 9, and FIGS. 10a. For example, when executed by at least one processor (401), the above one or more instructions may cause the electronic device (400) to perform at least some of the operations of FIGS. 6, FIGS. 7, FIGS. 9, and FIGS. 10a. The specific details regarding the memory (404) of FIG. 4 may be substantially the same as the details regarding the memory (1330) of FIG. 13.

[0063] Another electronic device (410) may be worn on a part of the user's body. For example, another electronic device (410) may be worn on the ear part of the user's body. For example, another electronic device (410) may have the shape of an ear clip. For example, another electronic device (410) may be referred to as an ear clip or earbuds.

[0064] Another electronic device (410) may include at least one processor (411), a sensor circuit (412), a communication circuit (414), and a memory (415). The components (e.g., at least one processor (411), a sensor circuit (412), a communication circuit (414), and a memory (415) are merely exemplary. For example, the other electronic device (410) may include other components (e.g., a PMIC (power management integrated circuitry)). For example, some components may be omitted from the other electronic device (410). The other electronic device (410) of FIG. 4 may be an example of the electronic device (1302, or 1304) of FIG. 13.

[0065] At least one processor (411) may be implemented as one or more integrated circuitry (IC) chips and may perform various data processing operations. At least one processor (411) may include at least one electrical circuit and may process instructions (or programs, data) stored in memory (415) individually or collectively in a distributed manner. At least one processor (411) may include a processor assembly including one or more processing circuits. At least one processor (411) may include any processing circuit that is operational to control the performance and operations of one or more components of another electronic device (410) (e.g., memory (415) and / or communication circuit (414)). For example, at least one processor (411) (e.g., application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or a set of chips). For example, at least one processor (411) may be implemented with multiple cores (or multiple core circuits), multiple chips, or multiple sets of chips. For example, at least one processor (411) may include one or more processing circuits configured to perform the various functions of the present disclosure individually and / or collectively.

[0066] For example, at least one processor (411) may include a central processing unit (e.g., including processing circuits) and a graphic processing unit (e.g., including processing circuits). The components of at least one processor (411) (e.g., CPU and GPU) are merely exemplary. The GPU may be used for the execution of a trained model. At least one processor (411) of FIG. 4 may be an example of a processor (1320) of FIG. 13.

[0067] The sensor circuit (412) may include at least one electrode. For example, the at least one electrode may include a contact electrode and a non-contact electrode. For example, the contact electrode measures a biosignal by contacting a part of the user's body, and the non-contact electrode measures the user's biosignal without contact. For example, the user's biosignal includes brain waves. For example, the non-contact electrode may include an antenna. The sensor circuit (412) may include an ADC. The description of the ADC (103) may apply to the ADC included within the sensor circuit (412). The sensor circuit (412) of FIG. 4 may be an example of the sensor module (1376) of FIG. 13.

[0068] According to one embodiment, a communication circuit (414) of another electronic device (410) may include hardware for supporting the transmission and / or reception of electrical signals between the electronic device (400) and the other electronic device (410). The transmission and / or reception of electrical signals between the electronic device (400) and the other electronic device (410) may be performed in the manner of wired communication (420) and / or wireless communication (430). The communication circuit (414) may include, for example, at least one of a modem, an antenna, and an optic / electronic converter. The communication circuit (414) may support the transmission and / or reception of electrical signals based on various types of communication means such as Ethernet, Bluetooth, BLE (Bluetooth Low Energy), ZigBee, LTE (Long Term Evolution), and 5G NR (New Radio). The communication circuit (414) of FIG. 4 may be an example of the communication module (1390) of FIG. 13.

[0069] According to one embodiment, a memory (415) of another electronic device (410) may include a hardware component for storing data and / or instructions that are input to or / or output from at least one processor (411). The memory may include, for example, volatile memory such as RAM (random-access memory) and / or non-volatile memory such as ROM (read-only memory). The volatile memory may include, for example, at least one of DRAM (dynamic RAM), SRAM (static RAM), Cache RAM, and PSRAM (pseudo SRAM). The non-volatile memory may include, for example, at least one of PROM (programmable ROM), EPROM (erasable PROM), EEPROM (electrically erasable PROM), flash memory, hard disk, compact disk, and eMMC (embedded multimedia card).

[0070] According to one embodiment, within the memory (415) of another electronic device (410), one or more instructions (or commands) representing operations and / or operations to be performed on data by at least one processor (411) of the other electronic device (410) may be stored. A set of one or more instructions may be referred to as a program, firmware, operating system, process, routine, sub-routine, and / or application. Hereinafter, the statement that an application is installed within another electronic device (e.g., another electronic device (410)) may mean that one or more instructions provided in the form of an application are stored in the memory (415), and that said one or more applications are stored in an executable format (e.g., a file having an extension specified by the operating system of the other electronic device (410)) by the processor of the electronic device. According to one embodiment, the other electronic device (410) may perform operations by executing one or more instructions stored in the memory (415). For example, when one or more of the above instructions are executed by at least one processor (411), they may cause another electronic device (410) to perform at least some of the operations. The memory (415) of FIG. 4 may be an example of the memory (1330) of FIG. 13.

[0071] Another electronic device (410) may be included within the electronic device (400). For example, the electronic device (400) and the other electronic device (410) may be implemented as a single device. The implementation of the electronic device (400) and the other electronic device (410) as a single device may include the other electronic device (410) being included within the electronic device (400) or the other electronic device (410) being used as one of the components of the electronic device (400). When the other electronic device (410) is included within the electronic device (400), at least one processor (411) of the other electronic device (410) may be described as a sensor hub included within at least one processor (401) of the electronic device (400). When another electronic device (410) is included within the electronic device (400), the communication circuit (414) of the other electronic device (410) may be referred to as an interface connected to the communication circuit (403) of the electronic device (400).

[0072] Figure 5a illustrates an example of another electronic device used for measuring brain waves.

[0073] Another electronic device (410) used for measuring brain waves may include a sensor circuit (412). The sensor circuit (412) may include at least one electrode. For example, the at least one electrode may include a contact electrode. For example, the contact electrode may include an active electrode (501), a reference electrode (502), and a ground electrode (503). The electrodes (501, 502, 503) may be composed of various materials. For example, the electrodes (501, 502, 503) may be composed of materials of gold, platinum, and / or silver chloride (AgCl). The shape of the other electronic device (410) is not limited to that shown in FIG. 5a. For example, the shape of the other electronic device (410) may include the shape of earbuds. Additionally, the material constituting the electrodes (501, 502, 503) within the other electronic device (410) is not limited to that illustrated in FIG. 5a. For example, the material may further include copper.

[0074] The measuring electrode (501) may include an electrode for measuring the user's brainwaves. For example, the measuring electrode (501) may include two electrodes (501-1, 501-2). The two electrodes (501-1, 501-2) included in the measuring electrode (501) may be used to measure the user's brainwaves by contacting the user's mastoid.

[0075] The reference electrode (502) may be used to measure a reference potential to be compared with the user's brainwave measured from the measurement electrode (501). For example, the reference electrode (502) may be in contact with the user's earlobe to measure a reference potential to be compared with the user's brainwave measured from the measurement electrode (501).

[0076] The grounding electrode (503) can be used to remove noise from the user's brainwaves measured by the measuring electrode (501) through grounding. For example, the grounding electrode can be placed behind the user's ear to remove noise from the user's brainwaves measured by the measuring electrode (501). Specific details regarding the method of removing the noise using the grounding electrode (503) are described with reference to FIG. 5b.

[0077] The contact positions of the electrodes (501, 502, 503) are not limited to those exemplified in FIG. 5a. For example, the measuring electrode (501) may be attached to the back of the ear, the reference electrode (502) may be in contact with the mastoid, and the ground electrode (503) may be in contact with the helix of the ear.

[0078] Figure 5b illustrates an example of a sensor circuit of another electronic device.

[0079] Referring to FIG. 5b, the sensor circuit (412) may include electrodes (501, 502, 503), an amplifier (102), and an ADC (103). For example, electrode (E1) (501-1) and electrode (E2) (501-2) are measurement electrodes (501), and the description of the measurement electrode (501) in FIG. 5a may be applied substantially the same way. Reference electrode (E3) (502) may be reference electrode (502) in FIG. 5a, and the description of the reference electrode (502) in FIG. 5a may be applied substantially the same way.

[0080] The ground electrode (E4) (503) may be connected (or electrically connected) to the RLD (right leg drive) circuit (504). For example, the ground electrode (E4) (503) and / or the RLD circuit (504) may be used to remove noise included in the acquired signal (e.g., analog signal (101)). For example, the ground electrode (503) may be used to identify a noise signal. As an example without limitation, the signal measured by the measurement electrode (501-1) may include a first noise signal, and the signal measured by the measurement electrode (501-2) may include a second noise signal. The ground electrode (503) may be used to detect a common noise signal between the first noise signal and the second noise signal. The RLD circuit (504) may be used to remove the detected common noise signal. For example, the RLD circuit (504) can generate a signal with a phase different from the phase of the common noise signal. As a non-limiting example, the difference between the phase of the generated signal and the phase of the common noise may be about 180°. For example, the signal generated from the RLD circuit (504) can be used to remove the common noise signal.

[0081] The analog signal (101) obtained through electrodes (501, 502, 503) according to brainwave measurement can be amplified through an amplifier (102). The amplified analog signal (105) can be input to an ADC (103) and converted into data (104). For example, the amplifier (102) can amplify the analog signal (101) based on a gain value stored in a memory (415) within another electronic device (410).

[0082] Data (104) output from the ADC (103) can be transmitted to the electronic device (400) through a communication circuit (414) within another electronic device (410). For example, the other electronic device (410) can transmit data (104) to the electronic device (400) in the manner of wired communication (420) and / or wireless communication (430) through a communication circuit (414) included within the other electronic device (410). The electronic device (400) can receive the data from the other electronic device (410) through a communication circuit (403) within the electronic device (400).

[0083] At least one processor (401) within the electronic device (400) can perform processing to acquire (or generate) data (107) for recognizing the state of a user based on the received data. Because the processing is performed by at least one processor (401) within the electronic device (400), the size of another electronic device (410) can be reduced. This may be because the components to be included in the other electronic device (410) are simplified as the processing is performed by at least one processor (401) within the electronic device (400).

[0084] Hereinafter, in the present disclosure, at least one processor (401) may acquire data (107) for recognizing the state of a user based on the received data. For example, at least one processor (401) may acquire the data (107) by performing an operation to classify the data in relation to a time interval and a frequency band. At least one processor (401) may adjust the gain value of an amplifier (102) using the acquired data (107). Specific details regarding the operations performed by at least one processor (401) are described below with reference to FIG. 6.

[0085] Figure 6 is a flowchart illustrating a method performed within an electronic device to adjust gain values.

[0086] At least some of the above methods of FIG. 6 may be performed by the electronic device (400) of FIG. 4. For example, at least some of the above methods may be controlled by at least one processor (401) of the electronic device (400). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0087] Referring to FIG. 6, in operation (600), at least one processor (401) can receive data. For example, at least one processor (401) can receive data obtained by another electronic device (410) through a communication circuit (403). For example, the data can be obtained by converting an analog signal (e.g., analog signal (105) of FIG. 1) output from an amplifier (e.g., amplifier (102)) of a sensor circuit (412) within another electronic device (410) by an ADC (e.g., ADC (103)) of the sensor circuit (412) within another electronic device (410). The electronic device (400) can receive data transmitted through a communication circuit (414) within another electronic device (410) (e.g., data (104) of FIG. 1). For example, the communication method between a communication circuit (403) in an electronic device (400) and a communication circuit (414) in another electronic device (410) may include a wired communication method (420) and / or a wireless communication method (430).

[0088] In operation (610), at least one processor (401) can identify whether the size of the received data is greater than a threshold size. For example, at least one processor (401) can identify whether the data is within an available range by identifying whether the size of the data is greater than a threshold size. Specific details regarding the threshold size may be referenced in FIG. 3.

[0089] In operation (610), at least one processor (401) may perform operation (615) if the received data is larger than the threshold size. In operation (610), at least one processor (401) may perform operation (620) if the received data is smaller than the threshold size.

[0090] In FIG. 6, operations (610) and operations (615) are shown to be performed by at least one processor (401), but the present disclosure is not limited thereto. For example, operations (610) and operations (615) may be omitted.

[0091] In operation (615), at least one processor (401) may transmit a request to reduce the gain value. For example, at least one processor (401) may generate a request to reduce the currently set gain value from the currently set gain value to a lower gain value. For example, at least one processor (401) may generate a request to reduce the currently set gain value from the currently set gain value to a lower gain value if the size of the received data is greater than the threshold size. For example, at least one processor (401) may transmit a request to reduce the gain value to another electronic device (410) via a communication circuit (403).

[0092] For example, if the gain value used to acquire the received data in operation (600) is a first gain value, the currently set gain value may be the first gain value. For example, in response to a request to reduce the gain value, a second gain value reduced from the first gain value may be used for brainwave measurement. Another electronic device (410) may measure brainwaves using the second gain value based on the received request.

[0093] In operation (620), at least one processor (401) can obtain first data corresponding to a brainwave measurement performed within a first time interval from the received data. For example, at least one processor (401) can identify the first time interval in which the brainwave measurement was performed when the size of the received data is smaller than a threshold size. For example, at least one processor (401) can identify the first time interval corresponding to a time interval for displaying information to guide the user's rest state. For example, the first time interval may be an example of the first time interval (801) of FIGS. 8a and FIGS. 8b below. For example, at least one processor (401) can obtain the first data corresponding to the first time interval identified from the data received from another electronic device (410).

[0094] In operation (625), at least one processor (401) can obtain second data corresponding to brainwave measurements performed within a second time interval from the received data. For example, at least one processor (401) can identify the second time interval in which brainwave measurements were performed when the size of the received data is smaller than a threshold size. For example, at least one processor (401) can identify the second time interval corresponding to a time interval for displaying information to guide the user's action state. For example, the second time interval may be an example of the second time interval (802) of FIGS. 8a and FIGS. 8b below. For example, at least one processor (401) can obtain the second data corresponding to the second time interval identified from the data received from another electronic device (410).

[0095] In operation (630), at least one processor (401) can identify third data using first data. For example, the first data may include components of a plurality of frequency bands. For example, the third data may be associated with a component of at least one frequency band. The at least one frequency band may be included in the plurality of frequency bands. For example, the third data may be an example of data for recognizing a user's state (e.g., data (107) of FIG. 1). Specific details regarding the operation (630) of identifying the third data using the first data are described with reference to FIG. 7.

[0096] In operation (635), at least one processor (401) can identify the fourth data using the second data. For example, the second data may include components of the plurality of frequency bands. For example, the fourth data may be associated with components of at least one frequency band. The at least one frequency band may be included in the plurality of frequency bands. For example, the fourth data may be an example of data for recognizing a user's state (e.g., data (107) of FIG. 1). Specific details regarding the operation (630) of identifying the fourth data using the second data are described below with reference to FIG. 7.

[0097] In operation (640), at least one processor (401) can identify whether the fourth data is within a reference range in relation to the third data. For example, at least one processor (401) can compare a size corresponding to the third data with a size corresponding to the fourth data. For example, identifying whether the fourth data is within the reference range in relation to the third data can be performed by comparing the size corresponding to the third data and the size corresponding to the fourth data. For example, the reference range can be used to determine whether to increase or maintain a gain value using the fourth data, which is distinct from the third data. Specific details regarding operation (640) are described below with reference to FIG. 9.

[0098] In operation (640), at least one processor (401) may perform operation (650) if it identifies that the fourth data is outside the reference range in relation to the third data. Alternatively, in operation (640), if the electronic device (400) identifies that the fourth data is within the reference range in relation to the third data, it may perform operation (660).

[0099] In operation (650), at least one processor (401) may transmit a request to increase the gain value. For example, if at least one processor (401) identifies that the fourth data is outside the reference range in relation to the third data, it may generate a request to increase the gain value that amplifies the analog signal (e.g., the analog signal (101) of FIG. 1). For example, at least one processor (401) may generate a request to increase the gain value to a gain value greater than the currently set gain value. For example, if the gain value used to amplify the analog signal in the amplifier (102) within another electronic device (410) is the first gain value, the currently set gain value may be the first gain value. For example, in accordance with the request to increase the gain value, a third gain value increased from the first gain value may be used for brainwave measurement. For example, at least one processor (401) can transmit a request to another electronic device (410) to increase the gain value through a communication circuit (403).

[0100] For example, another electronic device (410) may increase (or change, adjust) the first gain value stored in the memory (415) included in the other electronic device (410) to the third gain value in response to the request received through the communication circuit (414) within the other electronic device (410). For example, the other electronic device (410) may measure brain waves based on the third gain value.

[0101] In operation (660), at least one processor (401) may refrain from transmitting a request to increase the gain value. For example, if at least one processor (401) identifies that the fourth data is within the reference range of the third data, it may refrain from transmitting a request to increase the gain value. As an example without limitation, at least one processor (401) may refrain from generating a request to increase the gain value. Or, as an example without limitation, at least one processor (401) may refrain from transmitting the generated request after generating a request to increase the gain value. Or, as an example without limitation, at least one processor (401) may generate a request to maintain the currently set gain value and transmit the generated request to another electronic device (410) through the communication circuit (403). For example, if the gain value used to amplify an analog signal (e.g., analog signal (101) of FIG. 1) in an amplifier (102) within another electronic device (410) is the first gain value, the currently set gain value may be the first gain value. For example, the first gain value may be used for brainwave measurement in response to a request to maintain the gain value. For example, the other electronic device (410) may maintain the first gain value stored in a memory (415) included within the other electronic device (410) in response to the request received through a communication circuit (414) within the other electronic device (410). For example, the other electronic device (410) may measure brainwaves based on the first gain value.

[0102] As illustrated in FIG. 6, at least one processor (401) can identify data converted from an analog signal (e.g., data received from an operation (600)) as data associated with at least one frequency band (e.g., the third data or the fourth data). For example, at least one processor (401) can adjust a gain value based on the data associated with the at least one frequency band. The present disclosure can adjust the gain value to obtain data within an available range to recognize the state of the user by using the data identified in relation to the at least one frequency band.

[0103] FIG. 7 illustrates the operation flow of a method for an electronic device to identify third data using first data and a method for identifying fourth data using second data.

[0104] At least some of the above methods of FIG. 7 may be performed by the electronic device (400) of FIG. 4. For example, at least some of the above methods may be controlled by at least one processor (401) of the electronic device (400). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. For example, the above method of FIG. 7 may represent specific examples of operations (630) and operations (635) of the above method of FIG. 6.

[0105] In operation (620), at least one processor (401) can identify first data based on brainwave measurements performed within a first time interval from the received data. In operation (625), at least one processor (401) can identify second data based on brainwave measurements performed within a second time interval from the received data.

[0106] In operation (710), at least one processor (401) can identify components of a plurality of frequency bands from the first data. For example, at least one processor (401) can identify components of the plurality of frequency bands from the first data by performing a mathematical calculation. As an example not limited to, at least one processor (401) can identify the first data as components of the plurality of frequency bands by performing a fast Fourier transform (FFT).

[0107] For example, the components of the plurality of frequency bands may include a component representing a delta wave, a component representing a theta wave, a component representing an alpha wave, a component representing a beta wave, a component representing a beta_smr (beta_sensorimotor rhythm) wave, and a component representing a gamma wave. The frequency band of the beta_smr wave may be included in the frequency band of the beta wave. For example, the delta wave may represent a component of a frequency band of about 1 to about 4 Hertz (Hz). The theta wave may represent a component of a frequency band of about 4 to about 8 Hertz. The alpha wave may represent a component of a frequency band of about 8 to about 13 Hertz. The beta wave may represent a component of a frequency band of about 13 to about 30 Hertz. The above gamma wave may exhibit a component in a frequency band of about 30 to about 45 Hertz. The above beta_smr wave may exhibit a component in a frequency band of about 13 to about 15 Hertz.

[0108] In operation (720), at least one processor (401) can identify components of the plurality of frequency bands from the second data. For example, at least one processor (401) can identify components of the plurality of frequency bands from the second data by performing the mathematical calculation. As an example not limited to, at least one processor (401) can identify the second data as components of the plurality of frequency bands by performing a fast Fourier transform (FFT).

[0109] For example, the components of the plurality of frequency bands may include a component representing the delta wave, a component representing the theta wave, a component representing the alpha wave, a component representing the beta wave, a component representing the beta_smr (beta_sensorimotor rhythm) wave, and a component representing the gamma wave. The frequency band of the beta_smr wave may be included in the frequency band of the beta wave. For example, the delta wave may represent a component of a frequency band of about 1 to about 4 Hertz (Hz). The theta wave may represent a component of a frequency band of about 4 to about 8 Hertz. The alpha wave may represent a component of a frequency band of about 8 to about 13 Hertz. The beta wave may represent a component of a frequency band of about 13 to about 30 Hertz. The above gamma wave may exhibit a component in a frequency band of about 30 to about 45 Hertz. The above beta_smr wave may exhibit a component in a frequency band of about 13 to about 15 Hertz.

[0110] In operation (730), at least one processor (401) can identify at least one component of a frequency band among the components of the plurality of frequency bands identified from the first data. For example, at least one processor (401) can select at least one component of a frequency band among the components of the plurality of frequency bands identified from the first data to be used to identify the third data. For example, at least one processor (401) can select the component of the at least one frequency band among the components of the plurality of frequency bands based on a scenario selected by the user. As an example not limited to, if the scenario selected by the user is a meditation scenario, at least one processor (401) can select the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave among the components of the plurality of frequency bands identified from the first data to identify the third data.

[0111] In the above example, at least one processor (401) is exemplified as selecting the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave to identify the third data, but the present disclosure is not limited thereto. For example, if the scenario selected by the user is a concentration scenario, at least one processor (401) may select the component representing the beta_smr and the component representing the gamma wave among the components of the plurality of frequency bands identified from the first data to identify the third data.

[0112] In operation (735), at least one processor (401) can identify at least one component of a frequency band among the components of the plurality of frequency bands identified from the second data. For example, at least one processor (401) can select at least one component of a frequency band among the components of the plurality of frequency bands identified from the second data to be used to identify the fourth data. For example, at least one processor (401) can select the component of the at least one frequency band among the components of the plurality of frequency bands based on a scenario selected by the user. As an example not limited to, if the scenario selected by the user is a meditation scenario, at least one processor (401) can select the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave among the components of the plurality of frequency bands identified from the second data to identify the fourth data.

[0113] In the above example, at least one processor (401) is exemplified as selecting the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave to identify the fourth data, but the present disclosure is not limited thereto. For example, if the scenario selected by the user is a concentration scenario, at least one processor (401) may select the component representing the beta_smr and the component representing the gamma wave among the components of the plurality of frequency bands identified from the second data to identify the fourth data.

[0114] In operation (740), at least one processor (401) can identify third data based on the selected component of the at least one frequency band. For example, at least one processor (401) can identify the third data using the magnitude of the selected component of the at least one frequency band (e.g., the score in FIG. 8a and / or FIG. 8b). For example, at least one processor (401) can calculate (or identify) the average magnitude of the component of the at least one frequency band in the first time interval (e.g., the average score in FIG. 8a and / or FIG. 8b) from the magnitude of the selected component of the at least one frequency band. The third data can be calculated from the average magnitude. In an example, not limited to, if the scenario selected by the user is a meditation scenario, the selected component of the at least one frequency band may include a component representing the alpha wave, a component representing the beta wave, and a component representing the theta wave. At least one processor (401) can calculate the average size of the component representing the alpha wave in the first time interval, the average size of the component representing the beta wave in the first time interval, and the average size of the component representing the theta wave in the first time interval. For example, at least one processor (401) can calculate third data from the average size of the component representing the alpha wave in the first time interval, the average size of the component representing the beta wave in the first time interval, and the average size of the component representing the theta wave in the first time interval. The third data can be calculated according to the following mathematical formula.

[0115]

[0116] The above mathematical formula 1 is merely an example to aid understanding, and embodiments of the present disclosure may not be limited thereto. For example, the above mathematical formula 1 may be modified, applied, or extended in various ways.

[0117]

[0118] In a non-limiting example, at least one processor (401) may identify a score (e.g., the score in FIG. 8a and / or FIG. 8b) based on the component of the selected at least one frequency band. At least one processor (401) may identify third data using the identified score. For example, at least one processor (401) may calculate a first score in the first time interval from the magnitude of the component of the selected at least one frequency band. For example, at least one processor (401) may calculate a first average score from the first score. For example, the third data may correspond to the first average score. In a non-limiting example, if the scenario selected by the user is a meditation scenario, the component of the selected at least one frequency band may include a component representing the alpha wave, a component representing the beta wave, and a component representing the theta wave. At least one processor (401) can calculate the first score from the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave. The first score can be calculated according to the following mathematical formula.

[0119]

[0120] The above mathematical formula 2 is merely an example to aid understanding, and embodiments of the present disclosure may not be limited thereto. For example, the above mathematical formula 2 may be modified, applied, or extended in various ways.

[0121]

[0122] At least one processor (401) can calculate a first average score by calculating the average of the first scores in the first time interval. The third data may correspond to the first average score.

[0123] In operation (750), at least one processor (401) can identify the fourth data based on the selected component of the at least one frequency band. For example, at least one processor (401) can identify the fourth data using the magnitude of the selected component of the at least one frequency band. For example, at least one processor (401) can calculate (or identify) the average magnitude of the component of the at least one frequency band in the second time interval from the magnitude of the selected component of the at least one frequency band. The fourth data can be calculated from the average magnitude. As an example not limited to, if the scenario selected by the user is a meditation scenario, the selected component of the at least one frequency band may include a component representing the alpha wave, a component representing the beta wave, and a component representing the theta wave. At least one processor (401) can calculate the average size of the component representing the alpha wave in the second time interval, the average size of the component representing the beta wave in the second time interval, and the average size of the component representing the theta wave in the second time interval. For example, at least one processor (401) can calculate a fourth data from the average size of the component representing the alpha wave in the second time interval, the average size of the component representing the beta wave in the second time interval, and the average size of the component representing the theta wave in the second time interval. The fourth data can be calculated according to the following mathematical formula.

[0124]

[0125] The above mathematical formula 3 is merely an example to aid understanding, and embodiments of the present disclosure may not be limited thereto. For example, the above mathematical formula 3 may be modified, applied, or extended in various ways.

[0126]

[0127] In a non-limiting example, at least one processor (401) may identify a score (e.g., the score in FIG. 8a and / or FIG. 8b) based on the component of the selected at least one frequency band. At least one processor (401) may identify fourth data using the identified score. For example, at least one processor (401) may calculate a second score in the second time interval from the magnitude of the component of the selected at least one frequency band. For example, at least one processor (401) may calculate a second average score (e.g., the average score in FIG. 8a and / or FIG. 8b) from the second score. For example, the fourth data may correspond to the second average score. In a non-limiting example, if the scenario selected by the user is a meditation scenario, the component of the selected at least one frequency band may include a component representing the alpha wave, a component representing the beta wave, and a component representing the theta wave. At least one processor (401) can calculate the second score from the component representing the alpha wave, the component representing the beta wave, and the component representing the theta wave. The second score can be calculated according to the following mathematical formula.

[0128]

[0129] The above mathematical formula 4 is merely an example to aid understanding, and embodiments of the present disclosure are not limited thereto. For example, the above mathematical formula 4 may be modified, applied, or extended in various ways.

[0130]

[0131] At least one processor (401) can calculate a second average score by calculating the average of the second scores in the second time interval. The fourth data may correspond to the second average score.

[0132] As illustrated in FIG. 7, a method for identifying the third data (or the fourth data) using the first data (or the second data) can be performed based on a trained model. For example, an electronic device (400) can identify the third data by providing the component of the at least one frequency band identified using the first data to the trained model. Additionally, for example, an electronic device (400) can identify the fourth data by providing the component of the at least one frequency band identified using the second data to the trained model.

[0133] FIGS. 8A and FIGS. 8B illustrate graphs representing third and fourth data identified based on received data.

[0134] FIG. 8a illustrates a method in which, in a meditation scenario, at least one processor (401) identifies third data and fourth data based on data received from another electronic device (410) (e.g., data (104) of FIG. 1).

[0135] The horizontal axis of the graph (800) in FIG. 8a represents time, and the vertical axis represents the size of the data. The line of the graph (800) in FIG. 8a represents the size of the received data when the electronic device (400) receives data converted from an analog signal obtained by another electronic device (410).

[0136] Lines (805) can be distinguished according to each time interval of the graph (800). The time intervals of the graph (800) may include a first time interval (801), a second time interval (802), a third time interval (803), and a fourth time interval (804). For example, the first time interval (801) may correspond to a first rest time interval. The second time interval (802) may correspond to a first action time interval that is immediately subsequent to (or consecutive to) the first rest time interval. The third time interval may correspond to a second rest time interval that is immediately subsequent to (or consecutive to) the first action time interval. The fourth time interval may correspond to the second action time interval following the second rest time interval (or immediately subsequent to) and consecutive.

[0137] In FIG. 8a, the rest time interval is illustrated as including a first time interval (801) and a third time interval (803), but the present disclosure is not limited thereto. For example, the rest time interval may include a single time interval (e.g., a first time interval (801)). For example, if the rest time interval includes a first time interval (801), the rest time interval may correspond to the first time interval (801). For example, if the rest time interval includes a first time interval (801) and a third time interval (803), the rest time interval may include both the first rest time interval and the second rest time interval. Additionally, in FIG. 8a, the action time interval is illustrated as including a second time interval (802) and a fourth time interval (804), but the present disclosure is not limited thereto. For example, the action time interval may include one time interval (e.g., a second time interval (802)). For example, if the action time interval includes a second time interval (802), the action time interval may correspond to the second time interval (802). For example, if the action time interval includes a second time interval (802) and a fourth time interval (804), the action time interval may include both the first action time interval and the second action time interval.

[0138] Specific details regarding the first rest time interval, the first action time interval, the second rest time interval, and the second action time interval are described below with reference to FIGS. 11a and FIGS. 11b.

[0139] Line (805) may include the size of data converted from an analog signal obtained as the user guide is displayed. For example, the display of the user guide may include information for guiding the user's rest state and information for guiding the user's action state. For example, in FIG. 8a, the user guide may include the user guide according to the progress of the meditation scenario. As a non-limiting example, displaying information for guiding the user's rest state as the meditation scenario progresses may include information for guiding the user's state for data comparison performed to adjust gain values. For example, the data comparison may include comparing the third data and the fourth data. For example, the third data may be identified using the first data according to the brainwave measurement performed within the first time interval. For example, the first time interval may correspond to the first rest time in which information for guiding the user's rest state is displayed. As a non-limiting example, displaying information to guide the action state of the user may include displaying information to guide the state of the user for obtaining the user's biometric information. For example, the biometric information may be related to fourth data used for adjusting the gain value. For example, the fourth data may be identified using the second data based on brainwave measurements performed within the second time interval. For example, the second time interval may correspond to the first action time in which information to guide the action state of the user is displayed.

[0140] For example, in the first time interval (801) and the third time interval (803), the line (805) may indicate the size of data converted from an analog signal obtained as information for guiding the user's rest state is displayed. In the second time interval (802) and the fourth time interval (804), the line (805) may indicate the size of data converted from an analog signal obtained as information for guiding the user's action state is displayed.

[0141] The line (805) of the first time interval (801) may correspond to the first data. The line (805) of the second time interval (802) may correspond to the second data. The line (805) of the third time interval (803) may correspond to the fifth data. The line (805) of the fourth time interval (804) may correspond to the sixth data. For example, the fifth data corresponds to data converted from an analog signal obtained from another electronic device (410) during the third time interval corresponding to the time interval for displaying information for guiding the user's rest state. For example, the sixth data corresponds to data converted from an analog signal obtained from another electronic device (410) during the fourth time interval corresponding to the time interval for displaying information for guiding the user's action state.

[0142] Data represented by line (805) (e.g., the first data, the second data, the fifth data, and the sixth data) can be identified by at least one processor (401) as components of a plurality of frequency bands. For example, the first data, the second data, the fifth data, and the sixth data represented by line (805) can be identified as a component representing a delta wave, a component representing a theta wave, a component representing an alpha wave, a component representing a beta wave, a component representing a beta_smr wave, and a component representing a gamma wave.

[0143] The graph (810) represents components of multiple frequency bands to be identified from the data represented by the line (805). The horizontal axis of the graph (810) in FIG. 8a represents time, and the vertical axis represents magnitude. For example, the graph (810) may include lines (811), (812), and (813). For example, line (811) may correspond to a component representing alpha waves. Line (812) may correspond to a component representing theta waves. Line (813) may correspond to a component representing beta waves.

[0144] For example, referring to graph (810), in the meditation scenario, line (811) may represent a component of a first frequency band corresponding to the frequency band of the alpha wave. For example, line (811) may represent a first component, which is a component of the first frequency band during the rest time interval, and a third component, which is a component of the first frequency band during the action time interval. Line (812) may represent a component of a second frequency band corresponding to the frequency band of the theta wave. For example, line (812) may represent a second component, which is a component of the second frequency band during the rest time interval, and a fourth component, which is a component of the second frequency band during the action time interval. Line (813) may represent a component of a third frequency band corresponding to the frequency band of the beta wave. For example, line (813) may represent a fifth component, which is a component in the rest time interval of the third frequency band, and a sixth component, which is a component in the action time interval of the third frequency band.

[0145] The graph (820) represents a score for recognizing the user's state from the first to sixth components. The horizontal axis of the graph (820) in FIG. 8a represents time, and the vertical axis represents the score.

[0146] Lines (821), (822), (823), and (824) represent scores for recognizing the user's state. For example, in the case of a meditation scenario, the user's level of meditation can be determined through the scores. Specific details regarding the meditation scenario may be referenced in FIG. 11a.

[0147] At least one processor (401) can calculate lines (821) and lines (823) from the first component represented by line (811), the second component represented by line (812), and the fifth component represented by line (813). Lines (821) and lines (823) can be calculated according to the following mathematical formula.

[0148]

[0149] The above mathematical formula 5 is merely an example to aid understanding, and embodiments of the present disclosure may not be limited thereto. For example, the above mathematical formula 5 may be modified, applied, or extended in various ways.

[0150]

[0151] At least one processor (401) can calculate a first average score from lines (825) and lines (827). For example, at least one processor (401) can calculate the first average score (e.g., the first average score of FIG. 7) using the average of lines (825) and lines (827). The first average score may represent third data. As a non-limiting example, if the rest time interval includes a first time interval (801) which is a single time interval, line (825) may represent the third data.

[0152] At least one processor (401) can calculate lines (822) and lines (824) from the third component represented by line (811), the fourth component represented by line (812), and the sixth component represented by line (813). Lines (822) and lines (824) can be calculated according to the following mathematical formula.

[0153]

[0154] The above mathematical formula 6 is merely an example to aid understanding, and embodiments of the present disclosure are not limited thereto. For example, the above mathematical formula 6 may be modified, applied, or extended in various ways.

[0155]

[0156] At least one processor (401) can calculate the second average score from lines (826) and lines (828). For example, at least one processor (401) can calculate the second average score (e.g., the second average score of FIG. 7) using the average of lines (826) and lines (828). The second average score may represent the fourth data. As a non-limiting example, if the action time interval includes a second time interval (802) which is a single time interval, line (826) may represent the fourth data.

[0157] FIG. 8b illustrates a method in which, in a concentrated scenario, at least one processor (401) identifies third data and fourth data based on data received from another electronic device (410) (e.g., data (104) of FIG. 1).

[0158] The horizontal axis of the graph (830) in FIG. 8b represents time, and the vertical axis represents the size of the data. The line of the graph (830) in FIG. 8a represents the size of the received data when the electronic device (400) receives data converted from an analog signal obtained by another electronic device (410).

[0159] Line (835) can be distinguished according to each time interval of the graph (830). The time intervals of the graph (830) may include a first time interval (801), a second time interval (802), a third time interval (803), and a fourth time interval (804). For example, the first time interval (801) may correspond to a first rest time interval. The second time interval (802) may correspond to a first action time interval that is immediately subsequent to (or consecutive to) the first rest time interval. The third time interval may correspond to a second rest time interval that is immediately subsequent to (or consecutive to) the first action time interval. The fourth time interval may correspond to the second action time interval following the second rest time interval (or immediately subsequent to) and consecutive.

[0160] In FIG. 8b, the rest time interval is illustrated as including a first time interval (801) and a third time interval (803), but the present disclosure is not limited thereto. For example, the rest time interval may include a single time interval (e.g., a first time interval (801)). For example, if the rest time interval includes a first time interval (801), the rest time interval may correspond to the first time interval (801). For example, if the rest time interval includes a first time interval (801) and a third time interval (803), the rest time interval may include both the first rest time interval and the second rest time interval. Additionally, in FIG. 8b, the action time interval is illustrated as including a second time interval (802) and a fourth time interval (804), but the present disclosure is not limited thereto. For example, the action time interval may include one time interval (e.g., a second time interval (802)). For example, if the action time interval includes a second time interval (802), the action time interval may correspond to the second time interval (802). For example, if the action time interval includes a second time interval (802) and a fourth time interval (804), the action time interval may include both the first action time interval and the second action time interval.

[0161] Specific details regarding the first rest time interval, the first action time interval, the second rest time interval, and the second action time interval are described below with reference to FIGS. 11a and FIGS. 11b.

[0162] Line (835) may include the size of data converted from an analog signal obtained as the user guide is displayed. For example, the display of the user guide may include displaying information for guiding the user's rest state and displaying information for guiding the user's action state. For example, in FIG. 8b, the user guide may include the user guide according to the progress of the concentration scenario. As a non-limiting example, displaying information for guiding the user's rest state as the concentration scenario progresses may include displaying information for guiding the user's state for data comparison performed to adjust gain values. For example, the data comparison may include comparing the third data and the fourth data. For example, the third data may be identified using the first data according to the brainwave measurement performed within the first time interval. For example, the first time interval may correspond to the first rest time in which information for guiding the user's rest state is displayed. As a non-limiting example, displaying information to guide the action state of the user may include displaying information to guide the state of the user for obtaining the user's biometric information. For example, the biometric information may be related to fourth data used for adjusting the gain value. For example, the fourth data may be identified using the second data based on brainwave measurements performed within the second time interval. For example, the second time interval may correspond to the first action time in which information to guide the action state of the user is displayed.

[0163] For example, the line (835) in the first time interval (801) and the third time interval (803) may indicate the size of the data converted from the analog signal obtained as information is displayed to guide the user's rest state. The line (835) in the second time interval (802) and the fourth time interval (804) may indicate the size of the data converted from the analog signal obtained as information is displayed to guide the user's action state.

[0164] The line (835) of the first time interval (801) may correspond to the first data. The line (835) of the second time interval (802) may correspond to the second data. The line (835) of the third time interval (803) may correspond to the fifth data. The line (835) of the fourth time interval (804) may correspond to the sixth data. For example, the fifth data corresponds to data converted from an analog signal obtained from another electronic device (410) during the third time interval corresponding to the time interval for displaying information to guide the user's rest state. For example, the sixth data corresponds to data converted from an analog signal obtained from another electronic device (410) during the fourth time interval corresponding to the time interval for displaying information to guide the user's action state.

[0165] Data represented by line (835) (e.g., the first data, the second data, the fifth data, and the sixth data) can be identified by at least one processor (401) as components of a plurality of frequency bands. For example, the first data, the second data, the fifth data, and the sixth data represented by line (835) can be identified as components representing delta waves, components representing theta waves, components representing alpha waves, components representing beta waves, components representing beta_smr waves, and components representing gamma waves.

[0166] The graph (840) represents components of multiple frequency bands identified from the data represented by the line (835). The horizontal axis of the graph (840) in FIG. 8b represents time, and the vertical axis represents magnitude. For example, the graph (840) may include line (841) and line (842). For example, line (841) may correspond to a component representing a beta_smr wave. Line (842) may correspond to a component representing a gamma wave.

[0167] For example, referring to graph (840), in the concentration scenario, line (841) may represent a component of a fourth frequency band corresponding to the frequency band of the beta_smr wave. For example, line (841) may represent a first component, which is a component of the fourth frequency band during the rest time interval, and a third component, which is a component of the fourth frequency band during the action time interval. Line (842) may represent a component of a fifth frequency band corresponding to the frequency band of the gamma wave. For example, line (842) may represent a second component, which is a component of the fifth frequency band during the rest time interval, and a fourth component, which is a component of the fifth frequency band during the action time interval.

[0168] The graph (850) represents a score for recognizing the user's state from the first to fourth components. The horizontal axis of the graph (850) in FIG. 8b represents time, and the vertical axis represents the score.

[0169] Lines (851), (852), (853), and (854) represent scores for recognizing the user's state. For example, in the case of a meditation scenario, the user's level of meditation can be determined through the scores. Specific details regarding the meditation scenario may be referenced in FIG. 11a.

[0170] At least one processor (401) can produce lines (851) and lines (853) from the first component represented by line (841) and the second component represented by line (842). Lines (851) and lines (853) can be produced according to the following mathematical formula.

[0171]

[0172] The above mathematical formula 7 is merely an example to aid understanding, and embodiments of the present disclosure are not limited thereto. For example, the above mathematical formula 7 may be modified, applied, or extended in various ways.

[0173]

[0174] At least one processor (401) can calculate a first average score from lines (855) and lines (857). For example, at least one processor (401) can calculate the first average score (e.g., the first average score of FIG. 7) using the average of lines (855) and lines (857). The first average score may represent third data. In a non-limiting example, if the rest time interval includes a first time interval (801) which is a single time interval, line (855) may represent third data.

[0175] At least one processor (401) can produce lines (852) and (854) from the third component represented by line (841) and the fourth component represented by line (842). Lines (822) and (824) can be produced according to the following mathematical formula.

[0176]

[0177] The above mathematical formula 8 is merely an example to aid understanding, and embodiments of the present disclosure may not be limited thereto. For example, the above mathematical formula 8 may be modified, applied, or extended in various ways.

[0178]

[0179] At least one processor (401) can produce line (856) and line (858) from line (852) and line (854). For example, at least one processor (401) can produce line (856) using the average score in the second time interval (802) of line (852), and can produce line (858) using the average score in the fourth time interval (804) of line (854).

[0180] At least one processor (401) can calculate the second average score from lines (856) and lines (858). For example, at least one processor (401) can calculate the second average score (e.g., the second average score of FIG. 7) by calculating the average of lines (856) and lines (858). The second average score may represent the fourth data. As a non-limiting example, if the action time interval includes a second time interval (802) which is a single time interval, line (856) may represent the fourth data.

[0181] FIG. 9 illustrates the operation flow of a method for identifying whether the fourth data is within a reference range in relation to the third data.

[0182] At least some of the above methods of FIG. 9 may be performed by the electronic device (400) of FIG. 4. For example, at least some of the above methods may be controlled by at least one processor (401) of the electronic device (400). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. For example, the above method of FIG. 9 may represent a specific example of operation (640) of the above method of FIG. 6.

[0183] In operation (740), at least one processor (401) can identify third data based on components of at least one frequency band. In operation (750), at least one processor (401) can identify fourth data based on components of at least one frequency band.

[0184] In operation (910), at least one processor (401) can identify whether the size corresponding to the third data is larger than the size corresponding to the fourth data. In operation (910), at least one processor (401) can perform operation (920) if the size corresponding to the third data is larger than the size corresponding to the fourth data. Alternatively, in operation (910), at least one processor (401) can perform operation (930) if the size corresponding to the third data is smaller than the size corresponding to the fourth data.

[0185] For example, referring to FIGS. 8a and 8b, at least one processor (401) can identify whether the first average score in the rest time interval is greater than the second average score in the action time interval. If the first average score in the rest time interval is greater than the second average score in the action time interval, at least one processor (401) can perform an operation (920). If the first average score in the rest time interval is less than the second average score in the action time interval, at least one processor (401) can perform an operation (930).

[0186] In operation (920), at least one processor (401) can identify the fourth data within a reference range in relation to the third data. For example, at least one processor (401) can identify that the fourth data is within the reference range in relation to the third data if the value of the third data is greater than the value of the fourth data. In an example not limited to, at least one processor (401) can identify that the fourth data is within the reference range in relation to the third data if the value obtained by subtracting the fourth data from the third data is greater than a (constant).

[0187] At least one processor (401) may perform an operation (660) when it identifies fourth data within the reference range of third data. For example, at least one processor (401) may refrain from sending a request to increase the gain value.

[0188] In operation (930), at least one processor (401) can identify the fourth data outside the reference range in relation to the third data. For example, at least one processor (401) can identify that the fourth data is outside the reference range in relation to the third data if the value of the third data is smaller than the value of the fourth data. In an example not limited to, at least one processor (401) can identify that the fourth data is outside the reference range in relation to the third data if the value obtained by subtracting the fourth data from the third data is smaller than a (constant).

[0189] At least one processor (401) can perform an operation (650) when it identifies fourth data outside the reference range of third data. For example, at least one processor (401) can transmit a request to increase the gain value.

[0190] FIG. 10a illustrates the operation flow of a method for displaying information that guides the user's condition in relation to brainwave measurement.

[0191] At least some of the above methods of FIG. 10a may be performed by the electronic device (400) of FIG. 4. For example, at least some of the above methods may be controlled by at least one processor (401) of the electronic device (400). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. For example, the above method of FIG. 9 may represent a specific example of operation (640) of the above method of FIG. 6.

[0192] In operation (1000), at least one processor (401) can display information for selecting a scenario through a display (402). For example, at least one processor (401) can display information for selecting a meditation scenario and / or information for selecting a concentration scenario through the display (402). For example, at least one processor (401) can display information for selecting the meditation scenario and / or information for selecting the concentration scenario in the form of a user interface (UI) through the display (402).

[0193] Although not illustrated in FIG. 10a, at least one processor (401) may select a scenario based on an input received regarding the information. In an example without limitation, at least one processor (401) may select a scenario corresponding to a received touch input based on receiving a touch input (or hovering input) received regarding the information displayed through the display (402). Or, in an example without limitation, at least one processor (401) may receive a scenario corresponding to a received gesture based on receiving a gesture received regarding the information.

[0194] In operation (1001), at least one processor (401) can display information guiding the user's state through a display (402). For example, at least one processor (401) can display information guiding the user's state through the display (402) based on the selected scenario. For example, if the meditation scenario is selected, at least one processor (401) can display information guiding the user into a meditation state through the display (402).

[0195] Specific details regarding the information guiding the user's status displayed according to the selected scenario are explained with reference to FIG. 11a and FIG. 11b.

[0196] FIG. 10b illustrates a method for measuring a user's brainwaves performed by another electronic device and adjusting gain values ​​performed by an electronic device.

[0197] At least one processor (401) can display a screen (1010) through a display (402). As an example, without limitation, the screen (1010) may include a user interface (UI) of a scenario that a user (1013, 1014) can select. For example, the screen (1010) may include a UI for selecting a focus scenario and / or a UI for selecting a meditation scenario.

[0198] For example, at least one processor (401) may select (or determine) at least one frequency band component to be identified from the received data based on the scenario selected through the screen (1010). As an example without limitation, if a meditation scenario is selected through the screen (1010), at least one processor (401) may select (or determine) alpha waves, theta waves, and beta waves as at least one frequency band component.

[0199] At least one processor (401) can display a screen (1011) according to a scenario selected from a screen (1010) via a display (402). For example, the screen (1011) may include information that guides the state of a user (1013, 1014).

[0200] The operation of at least one processor (401) displaying the information guiding the state of the user (1013, 1014) through the display (402) is described by reference to the operation (1001). For example, if the user (1013, 1014) selects the meditation scenario, at least one processor (401) may display information guiding the user (1013, 1014) into a meditation state through the display (402). Specific details regarding the information guiding the state of the user are described by reference to FIGS. 11a and FIGS. 11b.

[0201] At least one processor (401) may transmit a command to another electronic device (410) to measure the brainwaves of the user (1013, 1014) when the screen (1011) begins to be displayed. For example, at least one processor (401) may transmit a command to another electronic device (410) to measure the brainwaves of the user (1013, 1014) via a communication circuit (403) when a meditation scenario begins. The other electronic device (410) may measure the brainwaves of the user (1013, 1014) based on the command received via the communication circuit (414) of the other electronic device (410). The brainwaves of the user (1013, 1014) may be measured according to the guide information displayed on the screen (1011).

[0202] Another electronic device (410) can amplify the measured brainwaves of the user (1013, 1014). Another electronic device (410) can convert the amplified brainwaves of the user (1013, 1014) into data. Another electronic device (410) can transmit the converted data to the electronic device (400).

[0203] In operation (1012), at least one processor (401) can identify data received from another electronic device (410) and adjust a gain value. At least one processor (401) can identify third data and fourth data using the received data. At least one processor (401) can generate a command for adjusting the gain value based on the identified third data and fourth data. At least one processor (401) can transmit the generated command to another electronic device. The other electronic device (410) can decrease, increase, and / or maintain the gain value based on the received command.

[0204] FIG. 11a illustrates user guide information displayed by an electronic device through a display in a meditation scenario.

[0205] FIG. 11b illustrates user guide information displayed by an electronic device through a display in a concentration scenario.

[0206] FIGS. 11a and FIGS. 11b illustrate user guide information displayed on a display (402) by at least one processor (401) in a meditation scenario and a concentration scenario, respectively. By example, the time interval (1100) of the meditation scenario and the concentration scenario may include a buffer time interval (1101), a first rest time interval (1102), a first action time interval (1103), a second rest time interval (1104), and a second action time interval (1105). However, the present disclosure is not limited thereto. For example, the time interval (1100) of the meditation scenario and the concentration scenario may include a buffer time interval (1101), a first rest time interval (1102), and a first action time interval (1103). In other words, the number of rest time intervals and the number of action time intervals included in the time interval (1100) may be changed.

[0207] The buffer time interval (1101) may correspond to a preparation time for measuring the user's brainwaves. For example, another electronic device (410) may refrain from (or bypass, stop) measuring the user's brainwaves during the buffer time interval (1101). The first rest time interval (1102) and the second rest time interval (1104) may correspond to a time interval for displaying information to guide the user's rest state. The first action time interval (1103) and the second action time interval (1105) may correspond to a time interval for displaying information to guide the user's action state.

[0208] The length of the buffer time interval (1101) of the time interval (1100) of the meditation scenario and the concentration scenario may be a first length (e.g., 5 seconds). The lengths of each of the first rest time interval (1102), first action time interval (1103), second rest time interval (1104), and second action time interval (1105) of the time interval (1100) of the meditation scenario and the concentration scenario may be a second length (e.g., 10 seconds). In the above example, the lengths of the first rest time interval (1102), first action time interval (1103), second rest time interval (1104), and second action time interval (1105) are exemplified as corresponding (or identical) to one another, but the present disclosure is not limited thereto. For example, the lengths of the first rest time interval (1102), the first action time interval (1103), the second rest time interval (1104), and the second action time interval (1105) may be different from each other.

[0209] For example, the first rest time interval (1102) may correspond to the first time interval (801) (or the first time interval (801) of FIG. 8B) with reference to FIG. 8A. The first action time interval (1103) may correspond to the second time interval (802) (or the second time interval (802) of FIG. 8B). The second rest time interval (1104) may correspond to the third time interval (803) (or the third time interval (803) of FIG. 8B). The second action time interval (1105) may correspond to the fourth time interval (804) (or the fourth time interval (804) of FIG. 8B).

[0210] Referring to FIG. 11a, at least one processor (401) may display a screen to guide the performance of brainwave measurement. For example, at least one processor (401) may display a screen (1111) through a display (402). For example, the screen (1111) may be displayed to guide a buffer time interval (1101). For example, the screen (1111) may include a visual object to guide the buffer time interval (1101). As an example without limitation, the visual object on the screen (1111) may include text (or characters) such as “Start meditation scenario.”

[0211] At least one processor (401) may refrain from sending a command to another electronic device (410) to measure brainwaves while the screen (1111) is displayed. For example, during a buffer time interval (1101), the other electronic device (410) may refrain from performing brainwave measurements. Accordingly, the analog signal may not be acquired by the other electronic device (410).

[0212] At least one processor (401) may display screen (1112) through a display (402) after displaying screen (1111). For example, at least one processor (401) may stop (or stop, bypass, refrain from) displaying screen (1111) through the display (402) and display screen (1112). For example, screen (1112) may be displayed to guide a first rest time interval (1102). For example, screen (1112) may include a visual object to guide the first rest time interval (1102). As an example without limitation, the visual object of screen (1112) may include text (or characters) such as “Keep your eyes open and do not move for 10 seconds.”

[0213] At least one processor (401) may transmit a command to another electronic device (410) to measure brain waves when the screen (1112) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brain waves during a first rest time interval (1102) based on receiving the command.

[0214] At least one processor (401) may display screen (1113) through the display (402) after displaying screen (1112). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1112) through the display (402) and display screen (1113). For example, screen (1113) may be displayed to guide a first action time interval (1103). For example, screen (1113) may include a visual object to guide the first action time interval (1103). As an example without limitation, the visual object of screen (1113) may include text (or characters) such as “Please close your eyes for 10 seconds.”

[0215] At least one processor (401) may transmit a command to another electronic device (410) to measure brainwaves when the screen (1113) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brainwaves during a first action time interval (1103) based on receiving the command.

[0216] At least one processor (401) may display screen (1114) via display (402) after displaying screen (1113). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1113) via display (402) and display screen (1114). For example, screen (1114) may be displayed to guide a second rest time interval (1104). For example, screen (1114) may include a visual object to guide the second rest time interval (1104). As an example without limitation, the visual object of screen (1114) may include text (or characters) such as “Keep your eyes open and do not move for 10 seconds.”

[0217] At least one processor (401) may transmit a command to another electronic device (410) to measure brain waves when the screen (1114) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brain waves during a second rest time interval (1104) based on receiving the command.

[0218] At least one processor (401) may display screen (1115) through the display (402) after displaying screen (1114). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1114) through the display (402) and display screen (1115). For example, screen (1115) may be displayed to guide a second action time interval (1105). For example, screen (1115) may include a visual object to guide the second action time interval (1105). As an example without limitation, the visual object of screen (1115) may include text (or characters) such as “Please close your eyes for 10 seconds.”

[0219] At least one processor (401) may transmit a command to another electronic device (410) to measure brainwaves when the screen (1115) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brainwaves during a second action time interval (1105) based on receiving the command.

[0220] At least one processor (401) may display screen (1116) via display (402) after displaying screen (1115). For example, the electronic device (400) may stop (or stop, bypass, refrain) the display of screen (1115) via display (402) and display screen (1116). For example, screen (1116) may be displayed to guide the end of a meditation scenario. As an example without limitation, the visual object of screen (1116) may include text (or characters) such as “Ending meditation scenario”.

[0221] The electronic device (400) may send a command to another electronic device (410) to stop the brainwave measurement when the screen (1116) begins to be displayed. The other electronic device (410) may stop the measurement of the user's brainwaves based on receiving the command.

[0222] FIG. 11b illustrates user guide information that an electronic device (400) displays on a display (402) in a concentration scenario.

[0223] Referring to FIG. 11b, at least one processor (401) may display a screen to guide the performance of brainwave measurement. For example, at least one processor (401) may display a screen (1121) through a display (402). For example, the screen (1121) may be displayed to guide a buffer time interval (1101). For example, the screen (1121) may include a visual object to guide the buffer time interval (1101). As an example without limitation, the visual object on the screen (1121) may include text (or characters) such as “Start concentration scenario.”

[0224] At least one processor (401) may refrain from sending a command to another electronic device (410) to measure brainwaves while the screen (1121) is displayed. For example, during a buffer time interval (1101), the other electronic device (410) may refrain from performing brainwave measurements. Accordingly, the analog signal may not be acquired by the other electronic device (410).

[0225] At least one processor (401) may display a screen (1122) through a display (402) after displaying a screen (1121). For example, at least one processor (401) may stop (or stop, bypass, refrain from) displaying the screen (1121) through the display (402) and display the screen (1122). For example, the screen (1122) may be displayed to guide a first rest time interval (1102). For example, the screen (1122) may include a visual object to guide the first rest time interval (1102). As an example without limitation, the visual object of the screen (1122) may include text (or characters) such as “Keep your eyes open and do not move for 10 seconds.”

[0226] At least one processor (401) may transmit a command to another electronic device (410) to measure brain waves when the screen (1122) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brain waves during a first rest time interval (1102) based on receiving the command.

[0227] At least one processor (401) may display screen (1123) through the display (402) after displaying screen (1122). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1122) through the display (402) and display screen (1123). For example, screen (1123) may be displayed to guide a first action time interval (1103). For example, screen (1123) may include a visual object to guide the first action time interval (1103). As an example without limitation, the visual object of screen (1123) may include text (or characters) such as “Please gaze at the dot displayed on the screen.”

[0228] At least one processor (401) may transmit a command to another electronic device (410) to measure brainwaves when the screen (1123) begins to be displayed. The other electronic device (410) may obtain an analog signal by measuring the user's brainwaves during a first action time interval (1103) based on receiving the command.

[0229] At least one processor (401) may display screen (1124) via display (402) after displaying screen (1123). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1123) via display (402) and display screen (1124). For example, screen (1124) may be displayed to guide a second rest time interval (1104). For example, screen (1124) may include a visual object to guide the second rest time interval (1104). As an example without limitation, the visual object of screen (1124) may include text (or characters) such as “Keep your eyes open and do not move for 10 seconds.”

[0230] At least one processor (401) may transmit a command to another electronic device (410) to measure brain waves when the screen (1124) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brain waves during a second rest time interval (1104) based on receiving the command.

[0231] At least one processor (401) may display screen (1125) via display (402) after displaying screen (1124). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1124) via display (402) and display screen (1125). For example, screen (1125) may be displayed to guide a second action time interval (1105). For example, screen (1125) may include a visual object to guide the second action time interval (1105). As an example without limitation, the visual object of screen (1125) may include text (or characters) such as “Please gaze at the dot displayed on the screen.”

[0232] At least one processor (401) may transmit a command to another electronic device (410) to measure brainwaves when the screen (1125) begins to be displayed. The other electronic device (410) may obtain the analog signal by measuring the user's brainwaves during a second action time interval (1105) based on receiving the command.

[0233] At least one processor (401) may display screen (1126) via display (402) after displaying screen (1125). For example, at least one processor (401) may stop (or stop, bypass, refrain) the display of screen (1125) via display (402) and display screen (1126). For example, screen (1126) may be displayed to guide the end of a meditation scenario. As an example without limitation, the visual object of screen (1125) may include text (or characters) such as “Ending meditation scenario”.

[0234] At least one processor (401) may send a command to another electronic device (410) to stop the brainwave measurement when the screen (1126) begins to be displayed. The other electronic device (410) may stop the measurement of the user's brainwaves based on receiving the command.

[0235] Figure 12 illustrates an example of a screen showing the analysis results of measured brain waves.

[0236] FIG. 12 illustrates an example in which User-Interface (UI) information regarding the results of processing brainwaves measured from another electronic device is displayed through the display of the electronic device (1200). The electronic device (1200) may be an example of the electronic device (400). In an embodiment that is not limiting, the electronic device (1200) may include a tablet and / or a foldable electronic device.

[0237] The first box (1210) illustrates a graph in which the user's brainwaves, measured from another electronic device (410), are converted into data. The graph may be an example of the graph (800) of FIG. 8a and the graph (830) of FIG. 8b.

[0238] The second box (1211) illustrates a graph in which the data is separated into multiple frequency bands through a mathematical technique that separates the data into multiple frequency bands. The mathematical technique may include an FFT.

[0239] The third box (1220) may include a menu (1221) displaying an indicator for brainwaves, and menus (1222, 1223, 1224, 1225) displaying scenarios for measuring brainwaves.

[0240] A menu (1221) displaying an indicator for brainwaves may include an indicator converted into a score after analyzing the brainwaves measured by the user in relation to frequency bands. For example, in a meditation scenario, the score may correspond to the value on the vertical axis of the graph (820) of FIG. 8a. As a non-limiting example, in a concentration scenario, the score may correspond to the value on the vertical axis of the graph (850) of FIG. 8b.

[0241] Menus (1222, 1223, 1224, 1225) displaying scenarios for measuring brainwaves may include a menu (1222) displaying a concentration scenario, a menu (1223) displaying a meditation scenario, a menu (1224) displaying a stress scenario, and a menu (1225) displaying a drowsiness scenario. For example, if the menu (1222) displaying a concentration scenario is selected, a scenario for measuring the user's level of concentration may be performed. For example, if the menu (1223) displaying a meditation scenario is selected, a scenario for measuring the user's level of meditation may be performed. For example, if the menu (1224) displaying a stress scenario is selected, a scenario for measuring the user's level of stress may be performed. For example, if the menu (1225) displaying a drowsiness scenario is selected, a scenario for measuring the user's level of drowsiness may be performed.

[0242] The fourth box (1230) may include an icon (1231) for connecting an external electronic device and an icon (1232) for indicating contact stability.

[0243] The icon (1231) for connecting an external electronic device may include a selection window for selecting a connectable external electronic device. For example, the external electronic device may include another electronic device (410).

[0244] An icon (1232) indicating contact stability may include information regarding contact stability between the electrodes of a connected external electronic device and the body. For example, if the other electronic device (410) is connected to the electronic device (1200), the information may include information indicating the degree of contact between the electrodes (501, 502, 503) contained within the other electronic device (410) and the body.

[0245] The fifth box (1240) may contain information measuring the movement of the user wearing the external electronic device when the connected external electronic device is worn by the user. For example, the movement may be measured through an accelerometer and / or gyroscope included in the external electronic device.

[0246] The sixth box (1250) may include information that quantifies and represents the magnitude of each data point of the graph shown in the second box (1211). For example, the information in the sixth box (1250) may include the magnitudes of the data points for each frequency band when the graph in the second box includes data separated by frequency bands through FFT. For example, the frequency bands may include the frequency band of delta waves, the frequency band of theta waves, the frequency band of alpha waves, the frequency band of beta waves, and the frequency band of gamma waves.

[0247] FIG. 13 is a block diagram of an electronic device in a network environment according to various embodiments.

[0248] Referring to FIG. 13, in a network environment (1300), an electronic device (1301) may communicate with an electronic device (1302) through a first network (1398) (e.g., a short-range wireless communication network) or with at least one of an electronic device (1304) or a server (1308) through a second network (1399) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (1301) may communicate with the electronic device (1304) through a server (1308). According to one embodiment, the electronic device (1301) may include a processor (1320), memory (1330), input module (1350), sound output module (1355), display module (1360), audio module (1370), sensor module (1376), interface (1377), connection terminal (1378), haptic module (1379), camera module (1380), power management module (1388), battery (1389), communication module (1390), subscriber identification module (1396), or antenna module (1397). In some embodiments, at least one of these components (e.g., connection terminal (1378)) may be omitted from the electronic device (1301), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (1376), camera module (1380), or antenna module (1397)) may be integrated into a single component (e.g., display module (1360)).

[0249] The processor (1320) can, for example, execute software (e.g., program (1340)) to control at least one other component (e.g., hardware or software component) of the electronic device (1301) connected to the processor (1320) and perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (1320) can store commands or data received from other components (e.g., sensor module (1376) or communication module (1390)) in volatile memory (1332), process the commands or data stored in volatile memory (1332), and store the resulting data in non-volatile memory (1334). According to one embodiment, the processor (1320) may include a main processor (1321) (e.g., a central processing unit or an application processor) or an auxiliary processor (1323) that can operate independently or together with it (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if the electronic device (1301) includes a main processor (1321) and an auxiliary processor (1323), the auxiliary processor (1323) may be configured to use less power than the main processor (1321) or to be specialized for a specified function. The auxiliary processor (1323) may be implemented separately from the main processor (1321) or as part thereof.

[0250] The auxiliary processor (1323) may control at least some of the functions or states associated with at least one component of the electronic device (1301) (e.g., display module (1360), sensor module (1376), or communication module (1390)) on behalf of the main processor (1321) while the main processor (1321) is in an inactive (e.g., sleep) state, or together with the main processor (1321) while the main processor (1321) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (1323) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (1380) or communication module (1390)). According to one embodiment, the auxiliary processor (1323) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (1301) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (1308)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0251] The memory (1330) can store various data used by at least one component of the electronic device (1301) (e.g., processor (1320) or sensor module (1376)). The data may include, for example, input data or output data for software (e.g., program (1340)) and related commands. The memory (1330) may include volatile memory (1332) or non-volatile memory (1334).

[0252] The program (1340) may be stored as software in memory (1330) and may include, for example, an operating system (1342), middleware (1344), or an application (1346).

[0253] The input module (1350) can receive commands or data to be used for a component of the electronic device (1301) (e.g., processor (1320)) from outside the electronic device (1301) (e.g., user). The input module (1350) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0254] The sound output module (1355) can output a sound signal to the outside of the electronic device (1301). The sound output module (1355) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0255] The display module (1360) can visually provide information to an external (e.g., user) of the electronic device (1301). The display module (1360) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (1360) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0256] The audio module (1370) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (1370) can acquire sound through the input module (1350) or output sound through the sound output module (1355) or an external electronic device (e.g., electronic device (1302)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (1301).

[0257] The sensor module (1376) can detect the operating state of the electronic device (1301) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (1376) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0258] The interface (1377) may support one or more specified protocols that can be used for the electronic device (1301) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (1302)). According to one embodiment, the interface (1377) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0259] The connection terminal (1378) may include a connector through which the electronic device (1301) can be physically connected to an external electronic device (e.g., electronic device (1302)). According to one embodiment, the connection terminal (1378) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0260] The haptic module (1379) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (1379) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0261] The camera module (1380) can capture still images and video. According to one embodiment, the camera module (1380) may include one or more lenses, image sensors, image signal processors, or flashes.

[0262] The power management module (1388) can manage the power supplied to the electronic device (1301). According to one embodiment, the power management module (1388) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0263] The battery (1389) can supply power to at least one component of the electronic device (1301). According to one embodiment, the battery (1389) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0264] The communication module (1390) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (1301) and an external electronic device (e.g., electronic device (1302), electronic device (1304), or server (1308)), and the performance of communication through the established communication channel. The communication module (1390) may include one or more communication processors that operate independently of the processor (1320) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1390) may include a wireless communication module (1392) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (1394) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (1304) via a first network (1398) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (1399) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (1392) can identify or authenticate the electronic device (1301) within a communication network such as the first network (1398) or the second network (1399) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (1396).

[0265] The wireless communication module (1392) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (1392) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (1392) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (1392) can support various requirements specified in the electronic device (1301), external electronic device (e.g., electronic device (1304)), or network system (e.g., second network (1399)). According to one embodiment, the wireless communication module (1392) can support a Peak data rate (e.g., 20 Gbps or more) for eMBB realization, loss coverage (e.g., 164 dB or less) for mMTC realization, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for URLLC realization.

[0266] An antenna module (1397) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (1397) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (1397) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (1398) or a second network (1399), may be selected from the plurality of antennas, for example, by a communication module (1390). A signal or power may be transmitted or received between the communication module (1390) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (1397).

[0267] According to various embodiments, the antenna module (1397) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0268] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0269] According to one embodiment, commands or data may be transmitted or received between the electronic device (1301) and an external electronic device (1304) through a server (1308) connected to a second network (1399). Each of the external electronic devices (1302, or 1304) may be the same or a different type of device as the electronic device (1301). According to one embodiment, all or part of the operations performed on the electronic device (1301) may be performed on one or more of the external electronic devices (1302, 1304, or 1308). For example, if the electronic device (1301) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (1301) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (1301). The electronic device (1301) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (1301) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (1304) may include an Internet of Things (IoT) device. The server (1308) may be an intelligent server using machine learning and / or neural networks.According to one embodiment, an external electronic device (1304) or server (1308) may be included within the second network (1399). The electronic device (1301) may be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0270] The technical problems to be solved in this disclosure are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which this disclosure pertains.

[0271] As described above, an electronic device (e.g., the electronic device (400) of FIG. 4) may include a communication circuit (e.g., the communication circuit (403) of FIG. 4). The electronic device may include a memory (e.g., the memory (404) of FIG. 4) that stores instructions and includes one or more storage media. The electronic device may include at least one processor (e.g., the processor (401) of FIG. 4) that includes a processing circuit. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to receive data obtained according to a brainwave measurement performed by another electronic device through the communication circuit from the other electronic device. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify first data according to the brainwave measurement performed within a first time interval from the data. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify, from the data, second data corresponding to the brainwave measurement performed within a second time interval following the first time interval. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify third data related to at least one frequency band using the first data. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify fourth data related to at least one frequency band using the second data.When the above instructions are executed individually or collectively by the at least one processor, they may cause the electronic device to transmit a request to the other electronic device through the communication circuit to increase a gain value for amplifying the magnitude of a signal acquired within the external electronic device according to the brainwave measurement, based on the fourth data which is outside the reference range in relation to the third data. When the above instructions are executed individually or collectively by the at least one processor, they may cause the electronic device to refrain from transmitting the request to the other electronic device through the communication circuit, based on the fourth data which is within the reference range in relation to the third data.

[0272] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify components of a plurality of frequency bands included in the signal obtained according to the brainwave measurement from the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify a component of at least one frequency band among the components of the plurality of frequency bands identified from the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify the third data based on the component of the at least one frequency band identified using the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify components of a plurality of frequency bands included in the signal obtained according to the brainwave measurement from the second data. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify a component of the at least one frequency band among the components of the plurality of frequency bands identified from the second data. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify the fourth data based on the component of the at least one frequency band identified using the second data.

[0273] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to obtain the components of the plurality of frequency bands included in the signal obtained according to the brainwave measurement by performing a fast Fourier transform (FFT) on the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to obtain the components of the plurality of frequency bands included in the signal obtained according to the brainwave measurement by performing an FFT on the second data.

[0274] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify the third data corresponding to the magnitude of the component of the at least one frequency band identified using the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify the fourth data corresponding to the magnitude of the component of the at least one frequency band identified using the second data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify whether the magnitude corresponding to the third data is greater than the magnitude corresponding to the fourth data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify the fourth data within the reference range in relation to the third data based on the magnitude corresponding to the fourth data which is greater than the magnitude corresponding to the third data. When the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify the fourth data outside the reference range in relation to the third data based on the size corresponding to the fourth data which is smaller than the size corresponding to the third data.

[0275] According to one embodiment, the magnitude of the component of the at least one frequency band identified using the first data may be defined based on the average magnitude of the component of the at least one frequency band identified using the first data over the first time interval. The magnitude of the component of the at least one frequency band identified using the second data may be defined based on the average magnitude of the component of the at least one frequency band identified using the second data over the second time interval.

[0276] According to one embodiment, the component of the at least one frequency band identified using the first data may include a first component of the first frequency band and a second component of the second frequency band. The magnitude of the component of the at least one frequency band identified using the first data may be defined as the value obtained by dividing the average magnitude of the first component by the average magnitude of the second component. The component of the at least one frequency band identified using the second data may include a third component of the first frequency band and a fourth component of the second frequency band. The magnitude of the component of the at least one frequency band identified using the second data may be defined as the value obtained by dividing the average magnitude of the third component by the average magnitude of the fourth component.

[0277] According to one embodiment, the component of the at least one frequency band identified using the first data may further include a fifth component of the third frequency band. The magnitude of the component of the at least one frequency band identified using the first data may be defined as the value obtained by dividing the average magnitude of the magnitude of the first component by the sum of the average magnitude of the magnitude of the second component and the average magnitude of the magnitude of the fifth component. The component of the at least one frequency band identified using the second data may further include a sixth component of the third frequency band. The magnitude of the component of the at least one frequency band identified using the second data may be defined as the value obtained by dividing the average magnitude of the magnitude of the third component by the sum of the average magnitude of the magnitude of the fourth component and the average magnitude of the magnitude of the sixth component.

[0278] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the training model to identify the third data corresponding to the magnitude of the component of the at least one frequency band identified using the first data by providing the training model with the component of the at least one frequency band identified using the first data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the training model to identify the fourth data corresponding to the magnitude of the component of the at least one frequency band identified using the second data by providing the training model with the component of the at least one frequency band identified using the second data.

[0279] According to one embodiment, the electronic device may further include a display. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the display to show information guiding the state of the user for a comparison of data performed to adjust the gain value within a time interval corresponding to the first time interval. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the display to show information guiding the state of the user for obtaining the user's biometric information within a time interval corresponding to the second time interval.

[0280] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to transmit a command to measure brain waves to the other electronic device through the communication circuit when the display of information guiding the state of the user for the comparison of the data performed to adjust the gain value begins. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to transmit the command to measure brain waves to the other electronic device through the communication circuit when the display of information guiding the state of the user for obtaining the user's bio-information begins.

[0281] According to one embodiment, the other electronic device may include a sensor circuit comprising an analog-to-digital converter (ADC) and at least one electrode. The at least one electrode may be in contact with a part of the user's body for brainwave measurement. The other electronic device may be included within the electronic device. The communication circuit may be used for communication between the other electronic device located within the electronic device and the at least one processor.

[0282] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify, from the data, fifth data according to the brainwave measurement performed within a third time interval following the second time interval. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify, from the data, sixth data according to the brainwave measurement performed within a fourth time interval following the third time interval. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify the third data related to the at least one frequency band using the first data and the fifth data. When the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the electronic device to identify the fourth data related to the at least one frequency band using the second data and the sixth data.

[0283] According to one embodiment, the length of the first time interval may correspond to the length of the second time interval. The length of the third time interval may correspond to the length of the fourth time interval.

[0284] A method performed by an electronic device having a communication circuit as described above may include the operation of receiving data obtained according to brainwave measurements performed by the other electronic device from the other electronic device through the communication circuit. The method may include the operation of identifying first data according to the brainwave measurements performed within a first time interval and second data according to the brainwave measurements performed within a second time interval following the first time interval. The method may include the operation of identifying third data related to at least one frequency band using the first data and the operation of identifying fourth data related to at least one frequency band using the second data. The method may include the operation of transmitting to the other electronic device through the communication circuit a request to increase a gain value for amplifying the magnitude of a signal obtained within the other electronic device according to the brainwave measurements, based on the fourth data which is outside the reference range in relation to the third data. The above method may include an operation of refraining from transmitting the request to the other electronic device through the communication circuit based on the fourth data within the reference range in relation to the third data.

[0285] According to one embodiment, the method may include an operation of identifying components of a plurality of frequency bands included in the signal obtained according to the brainwave measurement from the first data. It may include an operation of identifying a component of at least one frequency band among the components of the plurality of frequency bands identified from the first data. The method may include an operation of identifying the third data based on the component of the at least one frequency band identified using the first data. The method may include an operation of identifying components of a plurality of frequency bands included in the signal obtained according to the brainwave measurement from the second data. The method may include an operation of identifying a component of at least one frequency band among the components of the plurality of frequency bands identified from the second data. The method may include an operation of identifying the fourth data based on the component of the at least one frequency band identified using the second data.

[0286] According to one embodiment, the method may include an operation of obtaining components of the plurality of frequency bands included in the signal obtained according to the brainwave measurement by performing a fast Fourier transform (FFT) on the first data. The method may include an operation of obtaining components of the plurality of frequency bands included in the signal obtained according to the brainwave measurement by performing an FFT on the second data.

[0287] According to one embodiment, the method may include an operation of identifying the third data corresponding to the magnitude of the component of the at least one frequency band identified using the first data. The method may include an operation of identifying the fourth data corresponding to the magnitude of the component of the at least one frequency band identified using the second data. The method may include an operation of identifying whether the magnitude corresponding to the third data is greater than the magnitude corresponding to the fourth data. The method may include an operation of identifying the fourth data within the reference range in relation to the third data based on the magnitude corresponding to the fourth data which is greater than the magnitude corresponding to the third data. The method may include an operation of identifying the fourth data outside the reference range in relation to the third data based on the magnitude corresponding to the fourth data which is smaller than the magnitude corresponding to the third data.

[0288] According to one embodiment, the magnitude of the component of the at least one frequency band identified using the first data may be defined based on the average magnitude of the component of the at least one frequency band identified using the first data over the first time interval. The magnitude of the component of the at least one frequency band identified using the second data may be defined based on the average magnitude of the component of the at least one frequency band identified using the second data over the second time interval.

[0289] According to one embodiment, the component of the at least one frequency band identified using the first data may include a first component of the first frequency band and a second component of the second frequency band. The magnitude of the component of the at least one frequency band identified using the first data may be defined as the value obtained by dividing the average magnitude of the first component by the average magnitude of the second component. The component of the at least one frequency band identified using the second data may include a third component of the first frequency band and a fourth component of the second frequency band. The magnitude of the component of the at least one frequency band identified using the second data may be defined as the value obtained by dividing the average magnitude of the third component by the average magnitude of the fourth component.

[0290] A non-transient computer-readable storage medium as described above may store one or more programs including instructions that, when executed by an electronic device having a communication circuit, cause the electronic device to receive data acquired according to a brainwave measurement performed by another electronic device through the communication circuit. The non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify from the data first data according to the brainwave measurement performed within a first time interval and second data according to the brainwave measurement performed within a second time interval following the first time interval. The non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify third data related to at least one frequency band using the first data. The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to identify fourth data associated with the at least one frequency band using the second data. The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to transmit to the other electronic device through the communication circuit a request to increase a gain value for amplifying the magnitude of a signal acquired within the other electronic device according to the brainwave measurement, based on the fourth data which is outside the reference range in relation to the third data.The above non-transient computer-readable storage medium may store one or more programs including instructions that, when executed by the electronic device, cause the electronic device to refrain from transmitting the request to the other electronic device through the communication circuit based on the fourth data within the reference range in relation to the third data.

[0291] The effects obtainable from the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present disclosure belongs.

[0292] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0293] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B or C,” “at least one of A, B and C,” and “at least one of A, B, or C” may each include any one of the items listed together in the corresponding phrase, or any combination thereof. Terms such as “first,” “second,” or “first” or “second” may be used simply to distinguish a component from another corresponding component and do not limit the components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0294] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0295] Various embodiments of the present document may be implemented as software (e.g., program (1340)) comprising one or more instructions stored in a storage medium (e.g., internal memory (1336) or external memory (1338)) readable by a machine (e.g., electronic device (1301)). For example, a processor (e.g., processor (1320)) of the machine (e.g., electronic device (1301)) may call at least one of the one or more instructions stored from the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0296] According to one embodiment, the method according to the various embodiments disclosed herein may be provided as included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0297] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device, Communication circuit; Memory comprising one or more storage media for storing instructions; and It includes at least one processor comprising a processing circuit, and When the above instructions are executed individually or collectively by the at least one processor, the electronic device: Data obtained according to brainwave measurements performed by another electronic device is received from the other electronic device through the communication circuit; From the above data, identify first data according to the brainwave measurement performed within a first time interval and second data according to the brainwave measurement performed within a second time interval following the first time interval; Identifying third data related to at least one frequency band using the first data above; Identifying fourth data associated with at least one frequency band using the second data above; Based on the fourth data which is outside the reference range in relation to the third data, a request to increase a gain value for amplifying the magnitude of a signal acquired within the other electronic device according to the brainwave measurement is transmitted to the other electronic device through the communication circuit; and Based on the fourth data within the reference range in relation to the third data above, causing to refrain from transmitting the request to the other electronic device through the communication circuit, Electronic device.

2. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: Identifying components of a plurality of frequency bands included in the acquired signal according to the brainwave measurement from the first data; Identifying the component of at least one frequency band among the components of the plurality of frequency bands identified from the first data; Identifying the third data based on the component of the at least one frequency band identified using the first data; Identifying components of a plurality of frequency bands included in the acquired signal according to the brainwave measurement from the second data above; Identifying the component of at least one frequency band among the components of the plurality of frequency bands identified from the second data; and Causing to identify the fourth data based on the component of the at least one frequency band identified using the second data, Electronic device.

3. In Claim 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device; By performing a Fast Fourier Transform (FFT) on the first data above, components of the plurality of frequency bands included in the acquired signal according to the brainwave measurement are obtained; and By performing an FFT on the second data above, causing to obtain the components of the plurality of frequency bands included in the acquired signal according to the brainwave measurement, Electronic device.

4. In Claim 3, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: Identifying the third data corresponding to the magnitude of the component of the at least one frequency band identified using the first data; Identifying the fourth data corresponding to the magnitude of the component of the at least one frequency band identified using the second data; Identifying whether the size corresponding to the third data is larger than the size corresponding to the fourth data; Based on the size corresponding to the fourth data which is larger than the size corresponding to the third data, the fourth data within the reference range in relation to the third data is identified; and Causing to identify the fourth data outside the reference range in relation to the third data based on the size corresponding to the fourth data which is smaller than the size corresponding to the third data. Electronic device.

5. In Claim 4, The magnitude of the component of the at least one frequency band identified using the first data is defined based on the average magnitude of the component of the at least one frequency band identified using the first data over the first time interval, and The magnitude of the component of the at least one frequency band identified using the second data is defined based on the average magnitude of the component of the at least one frequency band identified using the second data over the second time interval. Electronic device.

6. In Claim 5, The component of the at least one frequency band identified using the above first data includes a first component of the first frequency band and a second component of the second frequency band, and The magnitude of the component of the at least one frequency band identified using the first data is defined as the value obtained by dividing the average magnitude of the first component by the average magnitude of the second component, and The component of the at least one frequency band identified using the second data comprises a third component of the first frequency band and a fourth component of the second frequency band, and The magnitude of the component of the at least one frequency band identified using the second data is defined as the value obtained by dividing the average magnitude of the third component by the average magnitude of the fourth component. Electronic device.

7. In Claim 6, The component of the at least one frequency band identified using the first data further includes a fifth component of the third frequency band, The magnitude of the component of the at least one frequency band identified using the first data is defined as the value obtained by dividing the average magnitude of the magnitude of the first component by the sum of the average magnitude of the magnitude of the second component and the average magnitude of the magnitude of the fifth component, and The component of the at least one frequency band identified using the second data further includes a sixth component of the third frequency band, and The magnitude of the component of the at least one frequency band identified using the second data is defined as the value obtained by dividing the average magnitude of the magnitude of the third component by the sum of the average magnitude of the magnitude of the fourth component and the average magnitude of the magnitude of the sixth component. Electronic device.

8. In Claim 3, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: By providing the component of the at least one frequency band identified using the first data to a trained model, the third data corresponding to the magnitude of the component of the at least one frequency band identified using the first data is identified; and By providing the component of the at least one frequency band identified using the second data to the trained model, the fourth data corresponding to the magnitude of the component of the at least one frequency band identified using the second data is identified. Electronic device.

9. In Claim 1, The above electronic device further includes a display, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: Information guiding the user's state for comparing data performed to adjust the gain value within a time interval corresponding to the first time interval above is displayed through the display; and Causing information that guides the state of the user for acquiring the user's biometric information to be displayed through the display within the time interval corresponding to the second time interval above. Electronic device.

10. In Claim 9, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: When the display of information guiding the state of the user for the comparison of the data performed to adjust the gain value begins, a command to measure brain waves is transmitted to the other electronic device through the communication circuit; and When the display of information guiding the state of the user for acquiring the biometric information of the user begins, causing the command to measure the brainwave to be transmitted to the other electronic device through the communication circuit, Electronic device.

11. In Claim 1, The other electronic device above includes an analog-to-digital converter (ADC) and a sensor circuit comprising at least one electrode, and The above at least one electrode is in contact with a part of the user's body for brainwave measurement, and The other electronic device mentioned above is included within the electronic device, and The above communication circuit is used for communication between the other electronic device located within the electronic device and the at least one processor. Electronic device.

12. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device: From the above data, identify the fifth data according to the brainwave measurement performed within the third time interval following the second time interval and the sixth data according to the brainwave measurement performed within the fourth time interval following the third time interval; Identifying the third data associated with the at least one frequency band using the first data and the fifth data; and Causing to identify the fourth data associated with the at least one frequency band using the second data and the sixth data, Electronic device.

13. In Claim 12, The length of the first time interval above corresponds to the length of the second time interval above, and The length of the third time interval above corresponds to the length of the fourth time interval above, Electronic device.

14. A method performed by an electronic device having a communication circuit, The operation of receiving data obtained according to brainwave measurements performed by another electronic device from said other electronic device through said communication circuit; An operation to identify, from the above data, first data according to the brainwave measurement performed within a first time interval and second data according to the brainwave measurement performed within a second time interval following the first time interval; An operation of identifying third data related to at least one frequency band using the first data above; An operation of identifying fourth data associated with at least one frequency band using the second data; The operation of transmitting to the other electronic device through the communication circuit a request to increase a gain value for amplifying the magnitude of a signal obtained within the other electronic device according to the brainwave measurement, based on the fourth data which is outside the reference range in relation to the third data; and Based on the fourth data within the reference range in relation to the third data, the operation of refraining from transmitting the request to the other electronic device through the communication circuit, method.

15. In a non-transient computer-readable storage medium, when executed by an electronic device having a communication circuit, said electronic device: Data obtained according to brainwave measurements performed by another electronic device is received from the other electronic device through the communication circuit; From the above data, identify first data according to the brainwave measurement performed within a first time interval and second data according to the brainwave measurement performed within a second time interval following the first time interval; Identifying third data related to at least one frequency band using the first data above; Identifying fourth data associated with at least one frequency band using the second data above; Based on the fourth data which is outside the reference range in relation to the third data, a request to increase a gain value for amplifying the magnitude of a signal acquired within the other electronic device according to the brainwave measurement is transmitted to the other electronic device through the communication circuit; and Storing one or more programs including instructions that cause to refrain from transmitting the request to the other electronic device through the communication circuit, based on the fourth data within the reference range in relation to the third data. Non-transient computer-readable storage media.

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