Electronic device for evaluating exercise of user and providing information about exercise, control method therefor, and non-transitory computer-readable storage medium

Abstract

An electronic device is disclosed. The electronic device comprises a memory for storing instructions, and one or more processors including processing circuitry, wherein, when individually or collectively executed by the one or more processors, the instructions enable first information about physical activity of a user and second information about an operation of the electronic device to be acquired while the user is exercising, a score for the physical activity to be acquired on the basis of the first information and the second information, and information related to the physical activity to be provided on the basis of the score.

Description

An electronic device for evaluating a user's exercise and providing information about the exercise, a method for controlling the same, and a non-transient computer-readable storage medium

[0001] The present disclosure relates to an electronic device that evaluates a user's exercise and provides information about the exercise, a method for controlling the same, and a non-transient computer-readable storage medium.

[0002] Driven by advancements in electronic technology, various types of electronic devices are being developed. In particular, following the recent social trend of users seeking well-being, the development of electronic devices that assist users with exercise is on the rise.

[0003] For example, an electronic device that assists a user's exercise stores data from a wearable device, a smartphone's IMU (inertial measurement unit) (a 6-axis sensor including accelerometer and gyroscope sensors), and a GPS (global positioning system) during the exercise, and can provide physical indicators such as exercise time, average speed, average heart rate, exercise calories, and steps at the end of the exercise. This aims to provide objective data regarding the user's exercise to enable the user to interpret the results of the exercise, and allows the user to evaluate their exercise based on the physical data and modify their exercise goals based on this.

[0004] 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.

[0005] According to one embodiment of the present disclosure for achieving the above objectives, an electronic device comprises one or more processors including a memory for storing instructions and a processing circuitry, and when the instructions are executed individually or collectively by the one or more processors, first information regarding the physical activity of the user and second information regarding the operation of the electronic device while the user is exercising are obtained, a score regarding the physical activity is obtained based on the first information and the second information, and information related to the physical activity is provided based on the score.

[0006] Additionally, when the above instructions are executed individually or collectively by the one or more processors, at least one of the following is obtained as the second information while the user is exercising: the user’s gaze at the electronic device, touch of the electronic device, frequency of operation of the electronic device, time of operation of the electronic device, application running on the electronic device, or usage pattern of the application; the number of times the physical activity is stopped, the time of the stop, and the second information are obtained as the first information, and the score is obtained based on the first information and the first sub-score.

[0007] And, when the above instructions are executed individually or collectively by the one or more processors, if the first sub-score is less than a preset score, a new path can be identified based on at least one of the first information, the user's location information, news, or the user's exercise goal, and the new path can be provided.

[0008] Additionally, the method further includes a communication interface, wherein the instructions, when executed individually or collectively by one or more processors, receive heart rate information of the user from a wearable device through the communication interface, obtain a second sub-score based on at least one of the first information, the heart rate information, or the user's exercise goal, and obtain a score based on the first information, the second information, and the second sub-score, and the heart rate information may include information on the maintenance rate and maintenance time for each heart rate zone.

[0009] And, when the above instructions are executed individually or collectively by the one or more processors, they may provide at least one of an essential message, a cheering message, or a warning message for increasing the second sub-score based on the second sub-score.

[0010] Here, when the instructions are executed individually or collectively by the one or more processors, if the maintenance ratio of a preset zone among the maintenance ratios by heart rate zone is above a threshold value, a message indicating the possibility of overwork may be provided.

[0011] Additionally, when the above instructions are executed individually or collectively by the one or more processors, the score can be obtained based on the user's physical information, the user's chronic disease information, the first information, and the second information.

[0012] And, the memory further stores an artificial intelligence model, and when the instructions are executed individually or collectively by the one or more processors, the user's physical information, the user's chronic disease information, the first information, and the second information can be input into the artificial intelligence model to obtain the score.

[0013] Additionally, when the above instructions are executed individually or collectively by the one or more processors, they may identify at least one comparison user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the user's physical activity with the at least one comparison user's physical activity as information related to the physical activity.

[0014] And, when the above instructions are executed individually or collectively by the one or more processors, they can identify a new goal that updates the exercise goal based on at least one of the first information, the user's exercise goal, or the user's feedback, and provide the new goal.

[0015] Meanwhile, according to one embodiment of the present disclosure, a control method for an electronic device may include the steps of obtaining first information regarding a user's physical activity and second information regarding the operation of the electronic device while the user is exercising, obtaining a score regarding the physical activity based on the first information and the second information, and providing information related to the physical activity based on the score.

[0016] Additionally, the step of acquiring the first information and the second information may acquire at least one of the user’s gaze at the electronic device, touch of the electronic device, frequency of operation of the electronic device, time of operation of the electronic device, application running on the electronic device, or usage pattern of the application as the second information while the user is exercising, and the step of acquiring the score may acquire a first sub-score based on the number of times the physical activity is stopped, the time of the stop, and the second information among the first information, and acquire the score based on the first information and the first sub-score.

[0017] And, if the first sub-score is less than a preset score, the method may further include the step of identifying a new path based on at least one of the first information, the user's location information, news, or the user's exercise goal, and the step of providing the new path.

[0018] Additionally, the method further includes the step of receiving heart rate information of the user from a wearable device, and the step of obtaining the score involves obtaining a second sub-score based on at least one of the first information, the heart rate information, or the user's exercise goal, and obtaining the score based on the first information, the second information, and the second sub-score, wherein the heart rate information may include information on the maintenance rate and maintenance time for each heart rate zone.

[0019] And, based on the second sub-score, it may further include the step of providing at least one of an essential message, a cheering message, or a warning message to increase the second sub-score.

[0020] Here, the method may further include a step of providing a message indicating the possibility of overwork if the maintenance ratio of a preset zone among the maintenance ratios by heart rate zone is above a threshold value.

[0021] In addition, the step of obtaining the score may be based on the user's physical information, the user's chronic illness information, the first information, and the second information.

[0022] In addition, the step of obtaining the above score can be performed by inputting the user's physical information, the user's chronic disease information, the first information, and the second information into an artificial intelligence model to obtain the above score.

[0023] Additionally, the step of providing the above may identify at least one comparison target user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the user's physical activity and the at least one comparison target user's physical activity as information related to the physical activity.

[0024] And, based on at least one of the first information, the user's exercise goal, or the user's feedback, the method may further include the step of identifying a new goal that updates the exercise goal and the step of providing the new goal.

[0025] Meanwhile, according to one embodiment of the present disclosure, in a non-transient computer-readable storage medium storing a program for executing a method of operating an electronic device, the method of operation may include the steps of obtaining first information regarding a user's physical activity and second information regarding the operation of the electronic device while the user is exercising, obtaining a score regarding the physical activity based on the first information and the second information, and providing information related to the physical activity based on the score.

[0026] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0027] FIG. 1 is a drawing illustrating an indicator related to movement to aid in understanding the present disclosure.

[0028] FIG. 2 is a block diagram showing the configuration of an electronic device according to one embodiment of the present disclosure.

[0029] FIG. 3 is a block diagram showing the detailed configuration of an electronic device according to one embodiment of the present disclosure.

[0030] FIG. 4 is a block diagram illustrating an electronic system according to one embodiment of the present disclosure.

[0031] FIG. 5 is a drawing for explaining a method of obtaining a passion score according to one embodiment of the present disclosure.

[0032] FIGS. 6 and FIGS. 7 are drawings for explaining a method of utilizing passion scores according to one embodiment of the present disclosure.

[0033] FIG. 8 is a drawing for explaining a method of obtaining a concentration score according to one embodiment of the present disclosure.

[0034] FIGS. 9 and FIGS. 10 are drawings for explaining the cause of a low concentration score and a method for identifying the same according to one embodiment of the present disclosure.

[0035] FIGS. 11 and FIGS. 12 are drawings for explaining an operation to propose a novel path to increase concentration scores according to one embodiment of the present disclosure.

[0036] FIG. 13 is a drawing for explaining a method of obtaining an immersion score according to one embodiment of the present disclosure.

[0037] FIGS. 14 and FIGS. 15 are drawings for explaining the operation when the immersion score is low according to one embodiment of the present disclosure.

[0038] FIG. 16 is a flowchart illustrating the provision of a message according to a heart rate zone according to one embodiment of the present disclosure.

[0039] FIG. 17 is a drawing for explaining a method of obtaining a novel goal according to one embodiment of the present disclosure.

[0040] FIG. 18 is a drawing for illustrating heart rate zone feedback according to one embodiment of the present disclosure.

[0041] FIG. 19 is a drawing for explaining an information providing screen according to one embodiment of the present disclosure.

[0042] FIG. 20 is a flowchart illustrating a method for controlling an electronic device according to one embodiment of the present disclosure.

[0043] The object of the present disclosure is to provide an electronic device for evaluating and motivating a user's exercise, a method for controlling the same, and a non-transient computer-readable storage medium.

[0044] The present disclosure will be described in detail below with reference to the attached drawings.

[0045] The terms used in the embodiments of this disclosure have been selected to be as widely used as possible, taking into account their functions within this disclosure; however, these terms may vary depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Additionally, in specific cases, terms have been arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the relevant explanatory section of this disclosure. Therefore, terms used in this disclosure should be defined not merely by their names, but based on their meanings and the overall content of this disclosure.

[0046] In this specification, expressions such as “have,” “may have,” “include,” or “may include” indicate the presence of such features (e.g., numerical values, functions, operations, or components such as parts) and do not exclude the presence of additional features.

[0047] The expression "at least one of A and / or B" should be understood as representing either "A" and "B" or "A or B".

[0048] Expressions such as "first," "second," "first," or "second" used in this specification may modify various components regardless of order and / or importance, and are used only to distinguish one component from another and do not limit said components.

[0049] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as "comprising" or "consisting of" are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0050] In this specification, the term "user" may refer to a person using an electronic device or a device using an electronic device (e.g., an artificial intelligence electronic device).

[0051] Various embodiments of the present disclosure will be described in more detail below with reference to the attached drawings.

[0052] FIG. 1 is a drawing illustrating an indicator related to movement to aid in understanding the present disclosure.

[0053] A device that assists a user's exercise can provide detailed exercise information. For example, as illustrated in FIG. 1, a device that assists a user's exercise stores data from a wearable device, an IMU (inertial measurement unit) sensor (a 6-axis sensor including accelerometer and gyroscope sensors) of a smartphone, and a GPS (global positioning system) during exercise, and can provide physical indicators such as exercise time, average speed, average heart rate, exercise calories, and step count at the end of exercise.

[0054] However, unless a user possesses professional knowledge, it is not easy to evaluate their exercise based on objective indicators provided by electronic devices and to receive feedback for the next workout. Furthermore, in the case of outdoor exercises such as running, walking, and cycling, accidents can occur due to various variables such as crosswalks, traffic lights, vehicles, and unexpected situations. Additionally, there may be instances where users fail to fully engage in the exercise and merely fill the time, such as when they intended to run but ended up walking instead. Generally, since conventional indicators are provided as numerical values ​​such as averages over the entire exercise period, there is a problem in that these indicators may be distorted by these variable situations.

[0055] FIG. 2 is a block diagram showing the configuration of an electronic device (100) according to one embodiment of the present disclosure.

[0056] The electronic device (100) may be a device that provides information related to the user's exercise. For example, the electronic device (100) may be implemented as a device such as a smartphone, a tablet PC (personal computer), smart glasses, a smart watch, or a smart ring. However, it is not limited to this, and the electronic device (100) may be any device that can provide information related to the user's exercise. For example, the electronic device (100) may be implemented as a device such as a server, a TV (television), or a projector.

[0057] Memory (110) may refer to hardware that stores information, such as data, in an electrical or magnetic form so that a processor (120) can access it. To this end, memory (110) may be implemented as at least one of non-volatile memory, volatile memory, flash memory, hard disk drive (HDD) or solid state drive (SSD), random access memory (RAM), or read only memory (ROM).

[0058] At least one instruction required for the operation of an electronic device (100) or a processor (120) may be stored in the memory (110). Here, the instruction is a unit of code that directs the operation of the electronic device (100) or the processor (120), and may be written in machine language, which is a language that a computer can understand. Alternatively, a plurality of instructions that perform a specific task of the electronic device (100) or the processor (120) may be stored in the memory (110) as an instruction set.

[0059] Data, which is information in bit or byte units capable of representing characters, numbers, or images, can be stored in the memory (110). For example, an artificial intelligence (AI) module, a score module, exercise history information, and user information can be stored in the memory (110).

[0060] The memory (110) is accessed by the processor (120), and the processor (120) can perform read / write / modify / delete / update on instructions, instruction sets, or data.

[0061] The processor (120) controls the overall operation of the electronic device (100). Specifically, the processor (120) is connected to each component of the electronic device (100) to control the overall operation of the electronic device (100). For example, the processor (120) is connected to a component such as memory (110) to control the operation of the electronic device (100).

[0062] One or more processors (120) may include one or more of a CPU (central processing unit), GPU (graphics processing unit), APU (accelerated processing unit), MIC (many integrated core), NPU (neural processing unit), hardware accelerator, or machine learning accelerator. One or more processors (120) may control one or any combination of other components of the electronic device (100) and may perform operations or data processing related to communication. One or more processors (120) may execute one or more programs or instructions stored in memory (110). For example, one or more processors (120) may perform a method according to one embodiment of the present disclosure by executing one or more instructions stored in memory (110).

[0063] When a method according to one embodiment of the present disclosure includes a plurality of operations, the plurality of operations may be performed by a single processor or by a plurality of processors. For example, when a first operation, a second operation, and a third operation are performed by a method according to one embodiment, the first operation, the second operation, and the third operation may all be performed by a first processor, or the first operation and the second operation may be performed by a first processor (e.g., a general-purpose processor) and the third operation may be performed by a second processor (e.g., an artificial intelligence dedicated processor).

[0064] One or more processors (120) may be implemented as a single-core processor including one core, or as one or more multicore processors including multiple cores (e.g., homogeneous multicore or heterogeneous multicore). When one or more processors (120) are implemented as multicore processors, each of the multiple cores included in the multicore processor may include internal processor memory such as cache memory or on-chip memory, and a common cache shared by the multiple cores may be included in the multicore processor. Additionally, each of the multiple cores included in the multicore processor (or some of the multiple cores) may independently read and execute program instructions for implementing a method according to one embodiment of the present disclosure, or all (or some) of the multiple cores may be linked together to read and execute program instructions for implementing a method according to one embodiment of the present disclosure.

[0065] When a method according to one embodiment of the present disclosure includes a plurality of operations, the plurality of operations may be performed by one of the plurality of cores included in a multi-core processor, or may be performed by a plurality of cores. For example, when a first operation, a second operation, and a third operation are performed by a method according to one embodiment, the first operation, the second operation, and the third operation may all be performed by a first core included in a multi-core processor, or the first operation and the second operation may be performed by a first core included in a multi-core processor and the third operation may be performed by a second core included in a multi-core processor.

[0066] In the embodiments of the present disclosure, one or more processors (120) may refer to a system on chip (SoC) in which one or more processors and other electronic components are integrated, a single-core processor, a multi-core processor, or a core included in a single-core processor or a multi-core processor, wherein the core may be implemented as a CPU, GPU, APU, MIC, NPU, hardware accelerator, or machine learning accelerator, but the embodiments of the present disclosure are not limited thereto. However, for convenience of explanation, the operation of the electronic device (100) is described below using the expression "processor (120)."

[0067] The processor (120) can obtain first information regarding the user's physical activity and second information regarding the operation of the electronic device (100) while the user is exercising. For example, the processor (120) can identify that the user is currently exercising based on at least one of posture information of the electronic device (100), location information of the electronic device (100), posture information received from a wearable device worn by the user, or operation information of the user's exercise application. When the processor (120) identifies that the user is exercising, it can obtain first information regarding the user's physical activity and second information regarding the operation of the electronic device (100). For example, the processor (120) may obtain information such as posture information of the electronic device (100), location information of the electronic device (100), posture information received from a wearable device worn by the user, duration of physical activity, number of times physical activity is stopped, and time of suspension of physical activity as first information, and may obtain at least one of the user's gaze at the electronic device (100), touch on the electronic device (100), frequency of operation on the electronic device (100), time of operation on the electronic device (100), application running on the electronic device (100), or usage pattern of the application as second information.

[0068] The processor (120) may obtain a score for physical activity based on the first information and the second information, and provide information related to physical activity through the display (155) or speaker (170) based on the score. For example, the processor (120) may obtain a score by inputting the first information and the second information into an artificial intelligence (AI) model, and provide information related to physical activity through the display (155) or speaker (170) based on the score. However, it is not limited thereto, and a score may be obtained by inputting any variety of information, not just the first information and the second information, into the AI ​​model. For example, the processor (120) may obtain a score by inputting not only the first information and the second information but also the user's physical information and the user's chronic illness information into the AI ​​model. Here, the score may be expressed as an enthusiasm score, serving as an evaluation indicator of how enthusiastically the user engaged in exercise.

[0069] The processor (120) may identify at least one comparison user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the user's physical activity with the physical activity of at least one comparison user through a display (155) or speaker (170) as information related to physical activity. For example, the processor (120) may identify a comparison user of the same age as the user and provide information comparing the user's physical activity with the physical activity of the comparison user through a display (155) or speaker (170) as information related to physical activity. Through this operation, the user can compare exercise results with comparison users who have similar physical conditions.

[0070] The processor (120) can identify a new goal that updates the exercise goal based on at least one of the first information, the user's exercise goal, or the user's feedback, and provide the new goal through the display (155) or speaker (170).

[0071] The processor (120) may acquire at least one of the following as second information: the user’s gaze at the user’s electronic device (100), touch of the electronic device (100), frequency of operation of the electronic device (100), time of operation of the electronic device (100), and application running on the electronic device (100) or usage pattern of the application while the user is exercising; acquire a first sub-score based on the number of times physical activity is paused, the time of pause, and the second information among the first information; and acquire a score based on the first information and the first sub-score. For example, the processor (120) may acquire a first sub-score by inputting the number of times physical activity is paused, the time of pause, and the second information among the first information into a first sub-artificial intelligence model, and acquire a score based on the first information and the first sub-score in an artificial intelligence model. However, it is not limited thereto, and the data input into the first sub-artificial intelligence model may be changed at any time. Here, the first sub-score is an evaluation indicator of how much the user is focused on exercise, and may be expressed as a focus score.

[0072] If the first sub-score is less than the preset score, the processor (120) may identify a new route based on at least one of the first information, the user's location information, news, or the user's exercise goal, and provide the new route through the display (155) or speaker (170). For example, if the first sub-score is less than the preset score, the processor (120) may identify that the user is not concentrating on the exercise and provide the new route to the user through the display (155) or speaker (170). However, it is not limited thereto, and if the processor (120) identifies that the first sub-score is less than the preset score but the user is not outside, it may provide a message through the display (155) or speaker (170) to induce the user to concentrate on the exercise.

[0073] The electronic device (100) further includes a communication interface (e.g., the communication interface (130) of FIG. 3), and the processor (120) receives heart rate information of a user from a wearable device through the communication interface, obtains a second sub-score based on at least one of the first information, heart rate information, or the user's exercise goal, and may obtain a score based on the first information, the second information, and the second sub-score. For example, the processor (120) may input the first information, heart rate information, and the user's exercise goal into a second sub-artificial intelligence model to obtain a second sub-score, and may obtain a score based on the first information, the second information, and the second sub-score in the artificial intelligence model. However, it is not limited thereto, and the data input into the second sub-artificial intelligence model may be changed at any time. Here, the second sub-score is an evaluation indicator of how much the user is immersed in exercise, and may be expressed as an immersion score. In addition, the heart rate information may include information on the maintenance rate and maintenance time by heart rate zone.

[0074] The processor (120) can provide at least one of an essential message, a cheering message, or a warning message to increase the second sub-score based on the second sub-score through the display (155) or speaker (170).

[0075] Here, the processor (120) can provide a message indicating that there is a possibility of overwork if the maintenance rate of a preset zone among the maintenance rates by heart rate zone is above a threshold value.

[0076] Meanwhile, the method of obtaining the score is not limited to that described above. For example, the processor (120) may obtain the score by inputting the first information, the first sub-score, and the second sub-score into an artificial intelligence model.

[0077] Meanwhile, the artificial intelligence-related functions according to the present disclosure can be operated through the processor (120) and memory (110).

[0078] The processor (120) may be composed of one or more processors. In this case, the one or more processors may be a general-purpose processor such as a CPU, an AP (application processor), or a DSP (digital signal processor), a graphics-dedicated processor such as a GPU or a VPU (vision processing unit), or an artificial intelligence-dedicated processor such as an NPU.

[0079] One or more processors control the processing of input data according to a predefined operation rule or artificial intelligence model (e.g., a neural network model) stored in memory (110). Alternatively, if one or more processors are dedicated artificial intelligence processors, the dedicated artificial intelligence processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model. The predefined operation rule or artificial intelligence model is characterized by being created through learning.

[0080] Here, "created through learning" means that a basic artificial intelligence model is trained using multiple learning data by a learning algorithm, thereby creating a predefined rule of operation or an artificial intelligence model configured to perform a desired characteristic (or objective). Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is executed, or it may be performed through a separate server and / or system. Examples of learning algorithms include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0081] An artificial intelligence model can be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values ​​and performs neural network operations through calculations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights can be updated during the learning process so that the loss or cost values ​​obtained by the artificial intelligence model are reduced or minimized.

[0082] Artificial neural networks may include deep neural networks (DNNs), such as, but are not limited to, convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), restricted Boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), generative adversarial networks (GANs), or deep Q-networks.

[0083] FIG. 3 is a block diagram showing the detailed configuration of an electronic device (100) according to one embodiment of the present disclosure. The electronic device (100) may include a memory (110) and a processor (120). Additionally, according to FIG. 3, the electronic device (100) may further include a communication interface (130), a sensor (140), a user interface (150), a display (155), a microphone (160), a speaker (170), and a camera (180). Detailed descriptions of parts of the components shown in FIG. 3 that overlap with the components shown in FIG. 2 are omitted.

[0084] The communication interface (130) is a configuration that performs communication with various types of external devices according to various types of communication methods. For example, an electronic device (100) can perform communication with a wearable device or a server through the communication interface (130). The processor (120) can obtain information about a user's physical activity received from a wearable device through the communication interface (130) as first information.

[0085] The communication interface (130) may include a Wi-Fi module, a Bluetooth module, an infrared communication module, and a wireless communication module. Here, each communication module may be implemented in the form of at least one hardware chip.

[0086] The Wi-Fi module and Bluetooth module perform communication using the Wi-Fi (wireless fidelity) and Bluetooth methods, respectively. When using a Wi-Fi or Bluetooth module, various connection information, such as the SSID (service set identification) and session key, is transmitted and received first; after establishing a communication connection using this information, various types of data can be transmitted and received. The infrared communication module performs communication based on infrared communication (IrDA, infrared data association) technology, which wirelessly transmits data over short distances using infrared rays that lie between visible light and millimeter waves.

[0087] In addition to the communication method described above, the wireless communication module may include at least one communication chip that performs communication according to various wireless communication standards such as Zigbee, 3G (3rd generation), 3GPP (3rd generation partnership project), LTE (long term evolution), LTE-A (LTE advanced), 4G (4th generation), and 5G (5th generation).

[0088] Alternatively, the communication interface (130) may further include a GPS (global positioning system) module. The GPS module receives signals transmitted from three or more GPS satellites, measures the time difference between the signals transmitted from the satellites and the signals received at the receiver to obtain the distance between the satellites and the receiver, and can identify the position of the electronic device (100) by a trilateration method based on the position of each satellite included in the transmitted signal and the distance to each satellite.

[0089] Alternatively, the communication interface (130) may further include wired communication interfaces such as HDMI (high definition multimedia interface), DP (display port), Thunderbolt, USB (universal serial bus), RGB (red green blue), D-SUB (D-subminiature), and DVI (digital visual interface).

[0090] In addition, the communication interface (130) may include at least one of a LAN (local area network) module, an Ethernet module, or a wired communication module that performs communication using a pair cable, a coaxial cable, or a fiber optic cable.

[0091] The sensor (140) may include a configuration for obtaining posture information of the electronic device (100). For example, the sensor (140) may include at least one of a gyroscope sensor, an accelerometer sensor, or a magnetometer sensor. The processor (130) may obtain first information regarding the user's physical activity based on the posture information of the electronic device (100) obtained through the sensor (140).

[0092] A gyro sensor is a sensor for detecting the rotation angle of an electronic device (100), and can measure changes in the orientation of an object by utilizing the property of always maintaining a constant direction initially set with high accuracy regardless of the rotation of the Earth. A gyro sensor is also called a gyroscope and can be implemented in a mechanical manner or an optical manner using light.

[0093] A gyroscope sensor can measure angular velocity. Angular velocity refers to the angle of rotation per unit of time, and the measurement principle of a gyroscope sensor is as follows. For example, in a horizontal state (stationary state), the angular velocity is 0 degrees / sec. If an object tilts by 50 degrees while moving for 10 seconds, the average angular velocity over those 10 seconds is 5 degrees / sec. If the tilt angle of 50 degrees is maintained while stationary, the angular velocity becomes 0 degrees / sec. Through this process, the angular velocity changes from 0 to 5 to 0, and the angle increases from 0 degrees to 50 degrees. To calculate the angle from the angular velocity, integration must be performed over the entire time. Since the gyroscope sensor measures angular velocity in this manner, the tilt angle can be calculated by integrating this angular velocity over the entire time. However, errors occur in the gyroscope sensor due to the influence of temperature, and as these errors accumulate during the integration process, the final value may drift. Accordingly, the electronic device (100) may further be equipped with a temperature sensor and can compensate for the error of the gyro sensor using the temperature sensor.

[0094] An acceleration sensor is a sensor that measures the acceleration or the intensity of an impact of an electronic device (100), and is also called an accelerometer. An acceleration sensor detects dynamic forces such as acceleration, vibration, and impact, and can be implemented as an inertial type, a gyro type, or a silicon semiconductor type depending on the detection method. Here, the inertial type is a method of measuring inertial acceleration, the gyro type is a method of detecting angular velocity acting on an inertial system, and the silicon semiconductor type may be a method using a silicon semiconductor that detects acceleration and converts it into an electrical signal. That is, an acceleration sensor is a sensor that senses the degree of tilt of an electronic device (100) using gravitational acceleration, and can typically be composed of a 2-axis or 3-axis flux gate.

[0095] A magnetometer sensor generally refers to a sensor that measures the strength and direction of the Earth's magnetic field; however, in a broader sense, it also includes sensors that measure the magnetization strength of an object and is also called a magnetometer. Magnetometer sensors can be implemented by suspending a magnet horizontally within a magnetic field and measuring the direction of its movement, or by rotating a coil within the field and measuring the induced electromotive force generated in the coil to measure the strength of the magnetic field.

[0096] In particular, a geomagnetic sensor, which measures the strength of the Earth's magnetic field as a type of magnetometer, can generally be implemented as a fluxgate-type geomagnetic sensor that detects geomagnetism using a fluxgate. A fluxgate-type geomagnetic sensor refers to a device that uses a high-permeability material such as permalloy as a magnetic core and applies an excitation field through a driving coil wound around the core; by measuring the second harmonic component proportional to the external magnetic field generated according to the magnetic saturation and nonlinear magnetic characteristics of the core, it measures the magnitude and direction of the external magnetic field. By measuring the magnitude and direction of the external magnetic field, the current azimuth angle is detected, and accordingly, the degree of rotation can be measured. The geomagnetic sensor can be composed of a 2-axis or 3-axis fluxgate. A 2-axis fluxgate sensor, that is, a 2-axis sensor, means a sensor composed of mutually orthogonal X-axis fluxgates and Y-axis fluxgates, and a 3-axis fluxgate, that is, a 3-axis sensor, means a sensor in which a Z-axis fluxgate is added to the X-axis and Y-axis fluxgates.

[0097] By using the geomagnetic sensor and acceleration sensor as described above, attitude information of the electronic device (100) can be obtained. For example, the attitude information of the electronic device (100) can be expressed as pitch angle, roll angle, and azimuth angle.

[0098] The azimuth (yaw angle) refers to an angle that changes in the left-right direction on a horizontal plane, and by calculating the azimuth, it is possible to determine which direction the electronic device (100) is facing. For example, if a geomagnetic sensor is used, the azimuth (yaw angle) can be measured through the following mathematical formula 1.

[0099] [Mathematical Formula 1]

[0100] ψ=arctan(sinψ / cosψ)

[0101] 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.

[0102] Here, ψ represents the azimuth angle, and cosψ and sinψ represent the X-axis and Y-axis fluxgate output values.

[0103] The roll angle refers to the angle at which a horizontal plane tilts to the left or right, and by calculating the roll angle, the left or right tilt of the electronic device (100) can be determined. The pitch angle refers to the angle at which a horizontal plane tilts up or down, and by calculating the pitch angle, the tilt angle at which the electronic device (100) is tilted upward or downward can be determined. For example, using an accelerometer, the roll angle and pitch angle can be measured through the following mathematical formula 2.

[0104] [Mathematical Formula 2]

[0105] φ=arcsin(ay / g)

[0106] θ=arcsin(ax / g)

[0107] 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.

[0108] Here, g represents the acceleration due to gravity, φ represents the roll angle, θ represents the pitch angle, ax represents the X-axis acceleration sensor output value, and ay represents the Y-axis acceleration sensor output value.

[0109] For convenience of explanation, the sensor (140) has been described above as including at least one of a gyroscope sensor, an accelerometer sensor, a magnetometer sensor, or a sound sensor. However, it is not limited thereto, and the sensor (140) may be any sensor capable of acquiring attitude information of the electronic device (100).

[0110] Meanwhile, if the electronic device (100) is implemented as a type that is worn by the user, the sensor (140) may further include a PPG (photoplethysmography) sensor and a temperature sensor.

[0111] A PPG sensor may be a sensor for measuring changes in blood flow in blood vessels near the skin. A processor (120) may obtain a user's heart rate information based on the PPG sensor. The user's heart rate increases while inhaling and decreases while exhaling, and the processor (120) may obtain heart rate information from the data obtained from the PPG sensor based on the relationship between these respiration and heart rate called respiratory sinus arrhythmia.

[0112] The temperature sensor may be a sensor that measures the temperature of a living organism or a part. The temperature sensor may be implemented in a contact or non-contact manner, and the measured temperature value may be provided to a memory (110) or a processor (120).

[0113] However, it is not limited to this, and the sensor (140) may include as many different types of biosensors.

[0114] The user interface (150) may be implemented as a button, touchpad, mouse, and keyboard, or as a touch screen capable of performing display functions and operation input functions. Here, the button may be a various type of button, such as a mechanical button, touchpad, or wheel, formed in any area of ​​the front, side, or rear surface of the main body of the electronic device (100).

[0115] The display (155) is configured to display an image and can be implemented as various types of displays such as an LCD (liquid crystal display), an OLED (organic light emitting diodes) display, and a PDP (plasma display panel). The display (155) may also include a driving circuit and a backlight unit that can be implemented in forms such as an a-si TFT (thin film transistor), an LTPS (low temperature poly silicon) TFT, and an OTFT (organic TFT). Meanwhile, the display (155) can be implemented as a touch screen combined with a touch sensor, a flexible display, or a 3D display.

[0116] The microphone (160) is configured to receive sound input and convert it into an audio signal. The microphone (160) is electrically connected to the processor (120) and can receive sound under the control of the processor (120).

[0117] For example, the microphone (160) may be formed as an integral unit integrated into the upper, front, or side direction of the electronic device (100). Alternatively, the microphone (160) may be provided in a remote control separate from the electronic device (100). In this case, the remote control may receive sound through the microphone (160) and provide the received sound to the electronic device (100).

[0118] The microphone (160) may include various configurations such as a microphone that collects analog sound, an amplifier circuit that amplifies the collected sound, an A / D (analog to digital) conversion circuit that samples the amplified sound and converts it into a digital signal, and a filter circuit that removes noise components from the converted digital signal.

[0119] Meanwhile, the microphone (160) may be implemented in the form of a sound sensor, and any configuration capable of collecting sound is acceptable.

[0120] The speaker (170) is a component that outputs various audio data processed by the processor (120), as well as various notification sounds or voice messages.

[0121] The camera (180) is configured to capture still images or video. The camera (180) can capture a still image at a specific point in time, but can also capture a series of still images.

[0122] The camera (180) includes a lens, a shutter, an aperture, a solid-state image sensor, an AFE (analog front end), and a TG (timing generator). The shutter controls the time when light reflected from a subject enters the camera (180), and the aperture controls the amount of light incident on the lens by mechanically increasing or decreasing the size of the opening through which light enters. When light reflected from a subject accumulates as photocharges, the solid-state image sensor outputs an image based on the photocharges as an electrical signal. The TG outputs a timing signal for reading out pixel data from the solid-state image sensor, and the AFE samples and digitizes the electrical signal output from the solid-state image sensor.

[0123] As described above, the electronic device (100) can analyze the user's physical activity as a more detailed indicator and provide various information based on the analysis results, thereby encouraging the user's motivation to exercise and forming exercise habits, thereby increasing the user's satisfaction.

[0124] The operation of the electronic device (100) will be described in more detail below through FIGS. 4 to 20. FIGS. 4 to 20 describes individual embodiments for convenience of explanation. However, the individual embodiments of FIGS. 4 to 20 may be implemented in any combination. Additionally, for convenience of explanation below, the score is described as the passion score, the first sub-score as the concentration score, and the second sub-score as the immersion score.

[0125] FIG. 4 is a block diagram for explaining an electronic system (1000) according to one embodiment of the present disclosure.

[0126] The electronic system (1000) may include an electronic device (100) and a wearable device (200). For example, the electronic device (100) may be a smartphone used by a user, and the wearable device (200) may be a smartwatch worn by a user. However, it is not limited thereto, and the electronic device (100) and the wearable device (200) may be implemented as a single device. In this case, the electronic device (100) may be used in a state where it is worn by a user, such as the wearable device (200). However, for convenience of explanation, the electronic device (100) and the wearable device (200) are described separately below.

[0127] The electronic device (100) can receive various information from the wearable device (200). For example, the processor (230) of the wearable device (200) can acquire information about the user's physical activity through the sensor (210), acquire location information of the wearable device (200) through the communication interface (220), and provide the acquired information to the electronic device (100). Here, the sensor (210) may be the same as the sensor (140) of the electronic device (100), the communication interface (220) may be the same as the communication interface (130) of the electronic device (100), and the processor (230) may be the same as the processor (120) of the electronic device (100), so redundant descriptions are omitted.

[0128] The processor (120) can receive information about the user's physical activity and location information of the wearable device (200) from the wearable device (200) through the communication interface (130). The processor (120) can identify the user's location based on the location information of the wearable device (200). If the processor (120) does not receive location information of the wearable device (200), it may identify the user's location based on location information of the electronic device (100).

[0129] The processor (120) can obtain current exercise pattern information (410) based on information about physical activity and location information.

[0130] In the memory (110) of the electronic device (100), existing exercise pattern information (420), exercise goals (450), user's physical information (460), and user's chronic illness information (470) may be stored. The processor (120) may read the existing exercise pattern information (420), exercise goals (450), user's physical information (460), and user's chronic illness information (470) from the memory (110).

[0131] The processor (120) can identify whether the user is looking at the electronic device (100) through the camera (180) and obtain information about the application (430) running and the application's usage pattern (440) through the user interface (150).

[0132] The processor (120) can obtain a concentration score (480) and an immersion score (490) from information obtained using at least one artificial intelligence model (e.g., a neural network model), and can obtain a passion score (495) based on the information obtained, the concentration score (480), and the immersion score (490).

[0133] The specific method for obtaining each score is explained in detail through the following diagram.

[0134] FIG. 5 is a drawing for explaining a method of obtaining a passion score according to one embodiment of the present disclosure. For convenience of explanation, FIG. 5 describes a method of obtaining a passion score (570) while the concentration score (510) and immersion score (520) have been obtained.

[0135] The passion score (570) may be an evaluation indicator of how passionately the user engages in exercise. For example, the passion score (570) is a score that comprehensively evaluates how much the target standard has been reached during the exercise phase. The passion score (570) can be obtained based on physical activity and the concentration score (510) and immersion score (520), and may include an evaluation of whether the user continues the exercise with passion. Here, the concentration score (510) is a score that evaluates the degree of exercise relative to other distracting factors, and the immersion score (520) may be a score that evaluates the intensity of exercise during the exercise phase. Additionally, the passion score (570) may be adjusted based on the user's physical information (540-1) and chronic illness information (550-1). That is, the criteria for achieving the exercise goal may be changed based on the user's health status and condition. Additionally, the criteria for the degree of distracting factors may be changed based on the user's health status and condition.

[0136] As illustrated in FIG. 5, the processor (120) can extract exercise frequency (530-2) from reference exercise pattern information (530-1), extract body index (540-2) from body information (540-1), and extract specific details (550-2) from chronic disease information (550-1). The processor (120) can obtain a passion score (570) by inputting the concentration score (510), immersion score (520), exercise frequency (530-2), body index (540-2), and specific details (550-2) into an artificial intelligence model (560). Here, the artificial intelligence model (560) may be a model trained to receive the concentration score (510), immersion score (520), exercise frequency (530-2), body index (540-2), and specific details (550-2) as inputs and output a passion score (570). Exercise frequency (530-2) may include information on the number of times exercise is performed during a specific time interval and the duration of exercise per day. Body index (540-2) may include information on the user's height, body mass index, location, age, and gender.

[0137] In FIG. 5, for convenience of explanation, it is described that the processor (120) extracts exercise frequency (530-2), body index (540-2), and specific details (550-2), but it is not limited thereto. For example, the processor (120) may input the concentration score (510), immersion score (520), existing exercise pattern information (530-1), body information (540-1), and chronic illness information (550-1) into an artificial intelligence model (560) to obtain a passion score (570).

[0138] Additionally, the processor (120) may provide a message through the display (155) or speaker (170) based on the chronic illness information (550-1). For example, the processor (120) may provide a message through the display (155) or speaker (170) to prevent the user from exercising excessively based on the chronic illness information (550-1).

[0139] FIGS. 6 and FIGS. 7 are drawings for explaining a method of utilizing passion scores according to one embodiment of the present disclosure.

[0140] When a passion score is obtained, the processor (120) can provide a screen containing information related to the passion score through the display (155). For example, as shown in FIG. 6, the processor (120) can provide a screen containing information on the passion score, exercise time, distance, and calories burned through the display (155).

[0141] Alternatively, the processor (120) may provide comparison information with the comparison target user through a display (155) or a speaker (170) when a passion score is obtained. For example, the processor (120) may receive consent for the use of personal information (S710) and consent for the comparison of passion scores between users (S720), as shown in FIG. 7.

[0142] The processor (120) can identify at least one comparison target user based on one of height, weight, body mass index, location, age, and gender based on user input. For example, when the processor (120) receives user input selecting age, it can identify users of a similar age group, compare passion between the user and users of a similar age group (S740-5), and indicate the passion ranking within the group (S750).

[0143] FIG. 8 is a drawing for explaining a method of obtaining a concentration score according to one embodiment of the present disclosure.

[0144] The focus score (840) may be an evaluation indicator of how much the user focuses on the exercise. For example, the focus score (840) may be obtained based on how much the user manipulates the electronic device (100) during the exercise, and based on the user's existing exercise pattern information, whether the exercise is stopped or the speed is reduced. Since the user can manipulate the electronic device (100) while maintaining the heart rate, the focus score (840) may differ from the immersion score based on heart rate described later.

[0145] As illustrated in FIG. 8, the processor (120) can analyze and determine whether there is an interaction with the electronic device (100) based on whether the camera (180) is being looked at (810-1), whether the user interface (150) is being operated (810-2), and whether the application (810-3) is running (820-1). Additionally, the processor (120) can analyze and determine whether there is an application-type-based distraction based on the application (810-3) and the application usage pattern (810-4) (820-2). Additionally, the processor (120) can analyze and determine whether there is an application primarily used during non-exercise time based on the application usage pattern (810-4) (820-3). Additionally, the processor (120) can extract distraction factors, such as the number of exercise pauses and time within the exercise pattern, based on current exercise pattern information (810-5) (820-4). The processor (120) can obtain a concentration score (840) by inputting the results of the analysis and judgment and the concentration distraction factors into the first sub-artificial intelligence model (830).

[0146] However, it is not limited to this, and the processor (120) may also obtain a focus score (840) by inputting the camera (180) gaze status (810-1), user interface (150) operation status (810-2), running application (810-3), application usage pattern (810-4), and current exercise pattern information (810-5) into the first sub-artificial intelligence model (830).

[0147] Meanwhile, the running application (810-3) may be reflected differently in the concentration score (840) depending on the type. For example, if the running application (810-3) is a phone application, the degree to which the concentration score is lowered may be smaller than that of a game application.

[0148] Alternatively, the processor (120) may update the focus score (840) by taking location information into further consideration. For example, if the processor (120) identifies that the location at the time the exercise stopped was due to a traffic light, it may not lower the focus score (840).

[0149] FIGS. 9 and FIGS. 10 are drawings illustrating the cause of a decrease in concentration score and a method for identifying the same according to an embodiment of the present disclosure. The solid line in FIG. 10 represents the user's heart rate information, and the dotted line in FIG. 10 represents the user's exercise speed.

[0150] As shown on the left side of FIG. 9, the exercise may be interrupted by a traffic light when the user passes through an intersection (910, 920) while exercising. Alternatively, as shown on the right side of FIG. 9, the user may use an electronic device (100) while exercising.

[0151] In this case, the processor (120) can identify the reason for stopping exercise based on the user's heart rate information, as shown by the solid line in FIG. 10. For example, the processor (120) can identify that the exercise has been completely stopped in the 1010 and 1030 intervals because the user's heart rate has dropped below a preset rate, and can identify that the exercise has been stopped by a traffic light. Alternatively, the processor (120) can identify that the exercise has been stopped by a traffic light if the location of the electronic device (100) and the wearable device has not changed above a preset time based on the location information of the electronic device (100) or the location information of the wearable device. The processor (120) can identify that the exercise has been stopped by a traffic light in the 1020 interval, where the user's heart rate has dropped but has not dropped below a preset rate, and can identify that the speed has slowed down rather than the exercise has been completely stopped, and that the user is using the electronic device (100). Alternatively, the processor (120) may identify the 1020 interval as the user using the electronic device (100) based on whether the user interface (150) is operated.

[0152] FIGS. 11 and FIGS. 12 are drawings for explaining an operation to propose a new path (1140) for increasing concentration scores according to one embodiment of the present disclosure.

[0153] As illustrated in FIG. 11, the processor (120) can extract the number of exercise stops and time (1120-1) within an existing exercise pattern based on existing exercise pattern information (1110-1). Additionally, the processor (120) can extract the number of crosswalks (1120-2) within an existing exercise path based on existing exercise pattern information (1110-1) and map information (1110-2). Additionally, the processor (120) can extract stop elements (1120-3), such as events within the area surrounding the exercise radius, based on real-time news information (1110-3). Furthermore, the processor (120) can extract reference points (1120-4), such as the exercise zone / radius, time, and start / end point, based on the exercise goal (1110-4). The processor (120) can input the extracted information into a third sub-artificial intelligence model (1130) to obtain a new path (1140) to increase the concentration score.

[0154] However, it is not limited thereto, and the processor (120) may input existing exercise pattern information (1110-1), map information (1110-2), real-time news information (1110-3), and exercise goal (1110-4) into the third sub-artificial intelligence model (1130) to obtain a new path (1140) to increase the concentration score. Alternatively, the processor (120) may input existing exercise pattern information (1110-1), map information (1110-2), and exercise goal (1110-4) into the third sub-artificial intelligence model (1130), excluding the real-time news information (1110-3), to obtain a new path (1140) to increase the concentration score.

[0155] The processor (120) may provide a new route through a display (155) or a speaker (170). For example, the processor (120) may provide a map including an existing route (1210) and a new route (1220) through a display (155), as shown in FIG. 12. Additionally, the processor (120) may provide information about the advantages of the new route (1220) compared to the existing route (1210) through a display (155) or a speaker (170). For example, the processor (120) may provide information through a display (155) or a speaker (170) that the new route (1220) has fewer traffic lights and less traffic flow compared to the existing route (1210).

[0156] In the case of outdoor exercises such as running, walking, and cycling, various variables such as crosswalks, traffic lights, vehicles, and unexpected situations may exist compared to indoor exercises, and accidents caused by smartphone operation can be prevented through such actions.

[0157] FIG. 13 is a drawing for explaining a method of obtaining an immersion score according to one embodiment of the present disclosure.

[0158] The engagement score (1340) may be an evaluation metric regarding how much the user is engaged in exercise. For example, the engagement score (1340) may be obtained based on the user's current state based on heart rate zones (HR zones) and whether they are following the guides in the selected exercise program. The engagement score (1340) based on heart rate may differ from the concentration score in that the user may exercise at a low intensity without operating the electronic device (100).

[0159] As illustrated in FIG. 13, the processor (120) can extract a maintenance rate by heart rate zone (1320-1) based on heart rate information (1310-1) and current exercise pattern information (1310-2). Additionally, the processor (120) can extract an exercise guide following rate (1320-2) based on current exercise pattern information (1310-2) and exercise goal (1310-3). The processor (120) can input the extracted information into a second sub-artificial intelligence model (1330) to obtain an immersion score (1340).

[0160] However, it is not limited to this, and the processor (120) may also obtain a focus score (1340) by inputting heart rate information (1310-1), current exercise pattern information (1310-2), and exercise goal (1310-3) into a second sub-artificial intelligence model (1330).

[0161] FIGS. 14 and FIGS. 15 are drawings for explaining the operation when the immersion score is low according to one embodiment of the present disclosure.

[0162] Even though the concentration score is high because the user does not cross the crosswalk or operate the electronic device (100), the user's heart rate may not fall into any heart rate zone, such as 1410 in Fig. 14, and in this case, the immersion score may be low.

[0163] Alternatively, if the user's heart rate is 1420 in FIG. 14, the exercise intensity may be higher than 1410 in FIG. 14, and if the user's heart rate is 1430 in FIG. 14, the exercise intensity may be higher than 1420 in FIG. 14, and the processor (120) may intuitively provide information about the exercise intensity to the user by displaying different colors for each heart rate zone.

[0164] The processor (120) may provide at least one of a must message, a cheer message, or a warning message to increase the immersion score through a display (155) or a speaker (170). For example, the processor (120) may provide a should message, a could message, and a must message through a display (155) or a speaker (170), as illustrated in FIG. 15. For instance, a should message may include a briefing on previous exercise results, encouragement / cheering messages for entering the goal zone, and health information (e.g., information on the benefits of the current exercise, information on the benefits of consistent exercise). A must message may include motivation for entering the goal zone, a warning to be careful of overwork, and information on the current exercise relative to the goal. A must message may include a warning of continued overwork, a warning of danger when exercising in non-sidewalk areas such as roads on a map, and a warning of danger when exercising in areas with loud noises such as horns or brakes.

[0165] FIG. 16 is a flowchart illustrating the provision of a message according to a heart rate zone according to one embodiment of the present disclosure.

[0166] 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.

[0167] First, the processor (120) can identify whether the program by goal is being used (S1610). If the processor (120) identifies that the program by goal is not being used, it can identify whether the heart rate zone 2 has been entered (S1620). If the processor (120) identifies that the heart rate zone 2 has not been entered, it can provide a should message, a could message, and a must message (S1625). For example, the processor (120) can provide the should message, the could message, and the must message simultaneously. Alternatively, the processor (120) can provide an icon representing the should message, an icon representing the could message, and an icon representing the must message, and if one of the multiple icons is selected, it can provide a message corresponding to the selected icon.

[0168] Subsequently, as exercise progresses further, the user's heart rate may enter heart rate zone 2. When the processor (120) identifies that the user has entered heart rate zone 2, it can identify whether the user has entered heart rate zone 5 (S1630). When the processor (120) identifies that the user has not entered heart rate zone 5, it can provide a should message or a must message through the display (155) or speaker (170) (S1640). When the processor (120) identifies that the user has entered heart rate zone 5, it can provide only a must message through the display (155) or speaker (170) (S1650).

[0169] If the processor (120) is identified as using a program specific to the goal, it can identify whether it has entered the goal zone (S1660). If the processor (120) is identified as not having entered the goal zone, it can provide a should message, a could message, and a must message (S1665).

[0170] Subsequently, as the exercise progresses further, the user's heart rate may enter the target zone. When the processor (120) identifies that the user has entered the target zone, it can identify whether the user has entered heart rate zone 5 (S1670). When the processor (120) identifies that the user has not entered heart rate zone 5, it can provide a should message or a must message through the display (155) or speaker (170) (S1680). When the processor (120) identifies that the user has entered heart rate zone 5, it can provide only a must message through the display (155) or speaker (170) (S1690).

[0171] FIG. 17 is a drawing for explaining a method of obtaining a novel goal according to one embodiment of the present disclosure.

[0172] As illustrated in FIG. 17, the processor (120) can extract heart rate zone tracking information relative to the exercise guide (1720-1) based on existing exercise pattern information (1710-1). Additionally, the processor (120) can extract the occupancy ratio by heart rate zone (1720-2) based on existing exercise pattern information (1710-1) and exercise goals (1710-2). Additionally, the processor (120) can analyze whether there is a desire to improve exercise intensity (1720-3) based on user feedback (1710-3). The processor (120) can input the extraction results and analysis results into a fourth sub-artificial intelligence model (1730) to obtain a new goal (1740).

[0173] However, it is not limited to this, and the processor (120) may also obtain a new goal (1740) by inputting existing exercise pattern information (1710-1), exercise goal (1710-2), and user feedback (1710-3) into a fourth sub-artificial intelligence model (1730).

[0174] FIG. 18 is a drawing for illustrating heart rate zone feedback according to one embodiment of the present disclosure.

[0175] The processor (120) may provide feedback for each heart rate zone through a display (155) or a speaker (170). For example, the processor (120) may guide to decrease heart rate zone 1 and increase heart rate zone 3 in relation to heart rate zones 1, 2, and 3 (1810) of Record 1, as shown in FIG. 18, and may provide an encouraging message through the display (155) or a speaker (170) for exceeding the goal in the case of heart rate zone 2.

[0176] Alternatively, the processor (120) may guide a method of immersion for effective exercise through the display (155) or speaker (170) when the heart rate zone 1 (1820) of Record 2 is below the ratio of heart rate zone 2 (1830). Additionally, the processor (120) may provide a warning message through the display (155) or speaker (170) because there is a possibility of overwork in heart rate zone 4 (1840) of Record 2.

[0177] Alternatively, the processor (120) may indicate that the target has been exceeded for heart rate zones 2 and 3 (1850) of record 3, indicate the possibility of reaching a runner's high over time, and then suggest a rate reduction in heart rate zone 1 via the display (155) or speaker (170). Here, runner's high may be a feeling of euphoria that running enthusiasts may experience. For example, runner's high may be a feeling of happiness resulting from physical stress that occurs when running.

[0178] FIG. 19 is a drawing for explaining an information providing screen according to one embodiment of the present disclosure.

[0179] When a passion score is obtained, the processor (120) can provide a screen containing information related to the passion score through the display (155). For example, the processor (120) can provide a screen (1910) containing information on the passion score, exercise time, distance, and calories burned through the display (155), as shown on the left side of FIG. 19.

[0180] When a user clicks on the passion score, the processor (120) can provide messages for the passion score, focus score, and immersion score, respectively, through a display (155) or a speaker (170). For example, as shown on the right side of FIG. 19, when a user clicks on the passion score (1910-1), the processor (120) can provide an evaluation of the passion score (1920-1), an evaluation and improvement guide for the focus score (1920-2), and an evaluation, improvement guide, and attention guide for the immersion score (1920-3) through a display (155) or a speaker (170).

[0181] Through the above actions, the user can evaluate their own exercise and receive feedback for the next exercise even without professional knowledge. Additionally, the electronic device (100) can provide the user with an interpretation of the exercise effect, thereby providing the user with the need for exercise and assisting in the formation of the user's exercise habit.

[0182] FIG. 20 is a flowchart illustrating a method for controlling an electronic device according to one embodiment of the present disclosure.

[0183] 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.

[0184] First, first information regarding the user's physical activity and second information regarding the operation of the electronic device are obtained while the user is exercising (S2010). Then, a score regarding the physical activity is obtained based on the first information and the second information (S2020). Then, information related to the physical activity is provided based on the score (S2030).

[0185] Additionally, the step of acquiring first information and second information (S2010) acquires at least one of the following as second information: the user’s gaze at the electronic device, touch of the electronic device, frequency of operation of the electronic device, time of operation of the electronic device, and application running on the electronic device or usage pattern of the application while the user is exercising; and the step of acquiring a score (S2020) acquires a first sub-score based on the number of times physical activity is paused, the pause time among the first information, and the second information, and can acquire a score based on the first information and the first sub-score.

[0186] And, if the first sub-score is less than a preset score, the method may further include the steps of identifying a new path based on at least one of the first information, the user's location information, news, or the user's exercise goal, and providing a new path.

[0187] Additionally, the method further includes the step of receiving user's heart rate information from a wearable device, and the step of obtaining a score (S2020) obtains a second sub-score based on at least one of the first information, heart rate information, or user's exercise goal, and obtains a score based on the first information, the second information, and the second sub-score, and the heart rate information may include information on the maintenance rate and maintenance time for each heart rate zone.

[0188] And, based on the second sub score, it may further include a step of providing at least one of an essential message, a cheering message, or a warning message to increase the second sub score.

[0189] Here, the method may further include a step of providing a message indicating the possibility of overwork if the maintenance ratio of a preset zone among the maintenance ratios by heart rate zone is above a threshold value.

[0190] Additionally, the step of acquiring a score (S2020) can acquire a score based on the user's physical information, the user's chronic disease information, the first information, and the second information.

[0191] And, the step of acquiring the score (S2020) can acquire the score by inputting the user's physical information, the user's chronic disease information, the first information, and the second information into an artificial intelligence model.

[0192] Additionally, the providing step (S2030) may identify at least one comparison target user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the user's physical activity and the physical activity of at least one comparison target user through a display (155) as information related to physical activity.

[0193] And, based on at least one of the first information, the user's exercise goal, or the user's feedback, the method may further include the step of identifying a new goal that updates the exercise goal and the step of providing the new goal.

[0194] An electronic device according to one embodiment as described above includes one or more processors including a memory for storing instructions and a processing circuitry, and when the instructions are executed individually or collectively by the one or more processors, first information regarding the user's physical activity and second information regarding the operation of the electronic device while the user is exercising are obtained, a score regarding the physical activity is obtained based on the first information and the second information, and information related to the physical activity is provided based on the score.

[0195] According to one example, when the instructions are executed individually or collectively by the one or more processors, at least one of the following is obtained as the second information: the user’s gaze at the electronic device while exercising, the touch of the electronic device, the frequency of operation of the electronic device, the time of operation of the electronic device, an application running on the electronic device, or a usage pattern of the application; the number of times the physical activity is stopped, the time of the stop, and the second information are obtained as the first information, and the score is obtained based on the first information and the first sub-score.

[0196] According to one example, when the instructions are executed individually or collectively by one or more processors, if the first sub-score is less than a preset score, a new path can be identified based on at least one of the first information, the user's location information, news, or the user's exercise goal, and the new path can be provided.

[0197] According to one example, the system further includes a communication interface, wherein the instructions, when executed individually or collectively by one or more processors, receive heart rate information of the user from a wearable device through the communication interface, obtain a second sub-score based on at least one of the first information, the heart rate information, or the user's exercise goal, and obtain a score based on the first information, the second information, and the second sub-score, and the heart rate information may include information on the maintenance rate and maintenance time for each heart rate zone.

[0198] According to one example, when the instructions are executed individually or collectively by the one or more processors, they may provide at least one of an essential message, a cheering message, or a warning message for raising the second subscore based on the second subscore.

[0199] According to one example, when the instructions are executed individually or collectively by one or more processors, if the maintenance ratio of a preset zone among the maintenance ratios by heart rate zone is above a threshold value, a message indicating that there is a possibility of overwork may be provided.

[0200] According to one example, when the instructions are executed individually or collectively by one or more processors, the score can be obtained based on the user's physical information, the user's chronic disease information, the first information, and the second information.

[0201] According to one example, the memory further stores an artificial intelligence model, and when the instructions are executed individually or collectively by the one or more processors, the user's physical information, the user's chronic disease information, the first information, and the second information can be input into the artificial intelligence model to obtain the score.

[0202] According to one example, when the instructions are executed individually or collectively by the one or more processors, they may identify at least one comparison user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the user's physical activity with the at least one comparison user's physical activity as information related to the physical activity.

[0203] According to one example, when the instructions are executed individually or collectively by the one or more processors, they can identify a new goal that updates the exercise goal based on at least one of the first information, the user's exercise goal, or the user's feedback, and provide the new goal.

[0204] A control method for an electronic device according to one example may include the steps of obtaining first information regarding a user's physical activity and second information regarding the operation of the electronic device while the user is exercising, obtaining a score regarding the physical activity based on the first information and the second information, and providing information related to the physical activity based on the score.

[0205] According to one example, the step of acquiring the first information and the second information may acquire at least one of the user’s gaze at the electronic device, touch of the electronic device, frequency of operation of the electronic device, time of operation of the electronic device, application running on the electronic device, or usage pattern of the application as the second information while the user is exercising, and the step of acquiring the score may acquire a first sub-score based on the number of times the physical activity is stopped, the time of the stop, and the second information among the first information, and acquire the score based on the first information and the first sub-score.

[0206] According to one example, if the first sub-score is less than a preset score, the method may further include the steps of identifying a new path based on at least one of the first information, the user's location information, news, or the user's exercise goal, and providing the new path.

[0207] According to one example, the method further includes the step of receiving heart rate information of the user from a wearable device, and the step of obtaining the score involves obtaining a second sub-score based on at least one of the first information, the heart rate information, or the user's exercise goal, and obtaining the score based on the first information, the second information, and the second sub-score, wherein the heart rate information may include information on the maintenance rate and maintenance time for each heart rate zone.

[0208] According to one example, the method may further include the step of providing at least one of an essential message, a cheering message, or a warning message to increase the second sub-score based on the second sub-score.

[0209] According to one example, if the maintenance ratio of a preset zone among the maintenance ratios by heart rate zone is above a threshold value, the method may further include a step of providing a message indicating that there is a possibility of overwork.

[0210] According to one example, the step of obtaining the score may be to obtain the score based on the user's physical information, the user's chronic illness information, the first information, and the second information.

[0211] According to one example, the step of obtaining the score may be to obtain the score by inputting the user's physical information, the user's chronic disease information, the first information, and the second information into an artificial intelligence model.

[0212] According to one example, the step of providing the above may identify at least one comparison target user based on at least one of the user's height, weight, body mass index (BMI), location, age, or gender, and provide information comparing the physical activity of the user and the physical activity of the at least one comparison target user as information related to the physical activity.

[0213] According to one example, the method may further include the steps of identifying a new goal that updates the exercise goal based on at least one of the first information, the user's exercise goal, or the user's feedback, and providing the new goal.

[0214] In a non-transient computer-readable storage medium storing a program for executing a method of operation of an electronic device according to one example, the method of operation may include the steps of obtaining first information regarding a user's physical activity and second information regarding the operation of the electronic device while the user is exercising, obtaining a score regarding the physical activity based on the first information and the second information, and providing information related to the physical activity based on the score.

[0215] According to various embodiments of the present disclosure as described above, the electronic device can analyze the user's physical activity as a more detailed indicator and provide various information based on the analysis results, thereby encouraging the user's motivation to exercise and forming exercise habits, and increasing the user's satisfaction.

[0216] The electronic device according to one or more embodiments disclosed in this disclosure may be a device 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 disclosure is not limited to the devices described above.

[0217] One or more embodiments of the present disclosure and the terms used therein are not intended to limit the technical features described in the present disclosure 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 the present disclosure, each of 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 include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as “first,” “second,” or “first” or “second” may be used simply to distinguish a component from another component and do not limit the components in any other aspect (e.g., importance or order). Where any (e.g., first) component is referred to as “coupled” or “connected” to another (e.g., second) component, with or without the terms “functionally” or “communicationally,” it means that said component may be connected to said other component directly (e.g., wired), wirelessly, or through a third component.

[0218] The term “module” as used in one or more embodiments of the present disclosure 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).

[0219] One or more embodiments of the present disclosure may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in 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.

[0220] According to one embodiment, the method according to one or more 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 in a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0221] According to one or more 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 one or more embodiments, one or more of the components or operations among 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 one or more 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, Memory for storing instructions; and One or more processors including processing circuitry; and When the above instructions are executed individually or collectively by the one or more processors, While the user is exercising, first information regarding the user's physical activity and second information regarding the operation of the electronic device are obtained, and Based on the first information and the second information above, a score for the physical activity is obtained, and An electronic device that provides information related to the physical activity based on the above score.

2. In Paragraph 1, When the above instructions are executed individually or collectively by the one or more processors, At least one of the user’s gaze at the electronic device, touch on the electronic device, frequency of operation on the electronic device, time of operation on the electronic device, application running on the electronic device, or usage pattern of the application is obtained as the second information while the user is exercising, and A first sub-score is obtained based on the number of pauses and pause times of the physical activity among the first information and the second information, and An electronic device that obtains the score based on the first information and the first sub-score.

3. In Paragraph 2, When the above instructions are executed individually or collectively by the one or more processors, If the above first sub-score is less than a preset score, a new path is identified based on at least one of the above first information, the user's location information, news, or the user's exercise goal, and An electronic device providing the above-mentioned new path.

4. In Paragraph 1, It further includes a communication interface; and When the above instructions are executed individually or collectively by the one or more processors, Receiving the user's heart rate information from the wearable device through the above communication interface, and A second sub-score is obtained based on at least one of the first information, the heart rate information, or the user's exercise goal, and The score is obtained based on the first information, the second information, and the second sub-score, and The above heart rate information is, An electronic device containing information on the maintenance rate and maintenance time by heart rate zone.

5. In Paragraph 4, When the above instructions are executed individually or collectively by the one or more processors, An electronic device that provides at least one of an essential message, a cheering message, or a warning message for increasing the second sub-score based on the second sub-score.

6. In Paragraph 4, When the above instructions are executed individually or collectively by the one or more processors, An electronic device that provides a message indicating the possibility of overwork if the maintenance ratio of a preset zone among the above heart rate zone maintenance ratios is above a threshold value.

7. In Paragraph 1, When the above instructions are executed individually or collectively by the one or more processors, An electronic device that obtains the score based on the user's physical information, the user's chronic disease information, the first information, and the second information.

8. In Paragraph 7, The above memory is, Store more artificial intelligence models, When the above instructions are executed individually or collectively by the one or more processors, An electronic device that inputs the user's physical information, the user's chronic disease information, the first information, and the second information into the artificial intelligence model to obtain the score.

9. In Paragraph 1, When the above instructions are executed individually or collectively by the one or more processors, Identify at least one comparison target user based on at least one of the height, weight, body mass index (BMI), location, age, or gender of the above user, and An electronic device that provides information comparing the physical activity of the above user and the physical activity of at least one comparison target user as information related to the physical activity.

10. In Paragraph 1, When the above instructions are executed individually or collectively by the one or more processors, Identifying a new goal that updates the exercise goal based on at least one of the first information, the user's exercise goal, or the user's feedback, and An electronic device providing the above-mentioned new objective.

11. In a method for controlling an electronic device, A step of obtaining first information regarding the physical activity of the user and second information regarding the operation of the electronic device while the user is exercising; A step of obtaining a score for the physical activity based on the first information and the second information; and A control method comprising the step of providing information related to physical activity based on the above score.

12. In Paragraph 11, The step of obtaining the first information and the second information is At least one of the user’s gaze at the electronic device, touch on the electronic device, frequency of operation on the electronic device, time of operation on the electronic device, application running on the electronic device, or usage pattern of the application is obtained as the second information while the user is exercising, and The step of obtaining the above score is, A first sub-score is obtained based on the number of pauses and pause times of the physical activity among the first information and the second information, and A control method for obtaining the score based on the first information and the first sub-score.

13. In Paragraph 12, If the first sub-score is less than a preset score, a step of identifying a new path based on at least one of the first information, the user's location information, news, or the user's exercise goal; and A control method further comprising the step of providing the above-mentioned new path.

14. In Paragraph 11, The method further includes the step of receiving the user's heart rate information from a wearable device, The step of obtaining the above score is, A second sub-score is obtained based on at least one of the first information, the heart rate information, or the user's exercise goal, and The score is obtained based on the first information, the second information, and the second sub-score, and The above heart rate information is, A control method including information on the maintenance rate and maintenance time by heart rate zone.

15. In Paragraph 14, A control method further comprising the step of providing at least one of an essential message, a cheering message, or a warning message to increase the second sub-score based on the second sub-score.

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