Electronic device for generating wrist movement data and method for operating same

Abstract

A method for generating a user's wrist movement data using a mouse, according to one aspect of the disclosed invention, may comprise the steps of: receiving first movement data indicating information related to movement of the mouse from at least one of a first sensor or a second sensor included in the mouse; obtaining first rotation intensity data indicating a rotation intensity of the mouse on the basis of the first movement data; obtaining second rotation intensity data indicating an average wrist rotation intensity of the user from the first rotation intensity data using a first model including a first correlation between an average mouse rotation intensity and an average wrist rotation intensity; and generating the user's wrist movement data on the basis of the second rotation intensity data.

Description

Electronic device for generating wrist movement data and method for operating the same

[0001] The present disclosure relates to an electronic device for generating wrist movement data and a method of operating the same.

[0002]

[0003] Since its introduction to the public in 1968, the computer mouse has been a key peripheral for human-computer interaction (HCI) in desktop environments. Despite the emergence of new interfaces, the computer mouse remains widely used, and development of better mouse models continues unabated.

[0004] Beyond the improvements in mouse hardware specifications driven by mouse manufacturers, many people are actively researching optimal mouse usage methods. For example, researchers have actively studied how variables such as mouse sensitivity, weight, shape, cable type, and mouse pad friction affect mouse performance, and how these variables should be adjusted accordingly.

[0005] The present invention was developed under the Ministry of Science and ICT's Information and Communication Broadcasting Innovation Talent Training Program (Project Unique Number:

[0006] This is derived from research conducted as part of the group research support of the Ministry of Science and ICT (Project ID: 1711193986, Project Number: 2020-0-01361-004, Project Management Agency: National IT Industry Promotion Agency, Research Project Name: Artificial Intelligence Graduate School Support (Yonsei University), Project Implementing Agency: Yonsei University Industry-Academic Cooperation Foundation, Research Period: 2023.01.01~2023.12.31) and the group research support of the Ministry of Science and ICT (Project ID: 1711198909, Project Number: 00223062, Project Management Agency: National Research Foundation of Korea, Research Project Name: Bounded Rationality Theory-Based E-Sports Player Behavior Simulation Laboratory, Project Implementing Agency: Yonsei University, Research Period: 2023.06.01~2024.02.29).

[0007] Meanwhile, the Korean government, which provided the task, has no property interest in any aspect of the present invention.

[0008]

[0009] The present disclosure aims to obtain the strength of a user's wrist rotation using only a sensor installed on a mouse, without a motion capture camera.

[0010] The present disclosure aims to accurately acquire user wrist movement data using only a sensor installed on a mouse, without a motion capture camera.

[0011] The present disclosure aims to obtain user wrist movement data by utilizing the correlation between the average mouse rotation strength and the average wrist rotation strength of users.

[0012] The problems to be solved by the present disclosure are not limited to the problems described above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

[0013]

[0014] A method for generating user's wrist movement data using a mouse according to one aspect of the disclosed invention may include: receiving first movement data indicating information related to movement of the mouse from at least one of a first sensor or a second sensor included in the mouse; obtaining first rotation intensity data indicating a rotation intensity of the mouse based on the first movement data; obtaining second rotation intensity data indicating an average wrist rotation intensity of the user from the first rotation intensity data using a first model including a first correlation between an average mouse rotation intensity and an average wrist rotation intensity; and generating the user's wrist movement data based on the second rotation intensity data.

[0015] Additionally, the first sensor and the second sensor may be placed at a certain distance apart from each other.

[0016] Additionally, the first movement data may include first lateral movement information and first longitudinal movement information measured with the location of the first sensor in the mouse as the origin; and second lateral movement information and second longitudinal movement information measured with the location of the second sensor in the mouse as the origin.

[0017] Additionally, the first rotational strength data may be determined based on at least one of the first lateral movement information, the first longitudinal movement information, the second lateral movement information, the second longitudinal movement information, the distance between the position of the first sensor and the position of the second sensor, the time the mouse moved, or the sensitivity of the mouse.

[0018] Additionally, the first model may be characterized as being a linear regression model indicating the first correlation, which is a correlation between the average mouse rotation strength and the average wrist rotation strength.

[0019] Additionally, the first correlation is expressed using a first correlation coefficient, and the first correlation coefficient may be less than 1.

[0020] Additionally, the step of obtaining the second rotational strength data may include the step of obtaining the second rotational strength data based on the mouse average rotational strength determined based on the first rotational strength data and the first correlation coefficient.

[0021] Additionally, the wrist movement data may be generated based on a second correlation between the first movement speed data indicating the movement speed of the mouse extracted from the first movement data and the second rotation strength data.

[0022] In addition, the first movement speed data may represent a horizontal average speed of the mouse, and the step of generating the user's wrist movement data may include a step of generating the wrist movement data based on a ratio value of the first movement speed data and the second rotation strength data.

[0023]

[0024] The present disclosure can acquire the strength of a user's wrist rotation using only a sensor installed on a mouse, without a motion capture camera.

[0025] The present disclosure can accurately acquire user's wrist movement data using only a sensor installed on a mouse, without a motion capture camera.

[0026] The present disclosure can obtain user wrist movement data by utilizing the correlation between the average mouse rotation strength and the average wrist rotation strength of users.

[0027] The effects according to the present disclosure are not limited to the effects described above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0028]

[0029] FIG. 1 is a diagram illustrating a method for acquiring wrist movement data according to one embodiment of the present disclosure.

[0030] FIG. 2 is a diagram illustrating first movement data and second rotation intensity data according to one embodiment of the present disclosure.

[0031] FIG. 3 is a diagram for explaining wrist movement data according to one embodiment of the present disclosure.

[0032] FIG. 4 is a diagram for explaining wrist movement data according to inclination according to one embodiment of the present disclosure.

[0033] FIG. 5 is a flowchart illustrating a method for an electronic device to acquire wrist movement data according to one embodiment of the present disclosure.

[0034] FIG. 6 is a drawing illustrating an electronic device according to one embodiment of the present disclosure.

[0035] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the contents described in the attached drawings. However, the present invention is not limited or restricted by the exemplary embodiments. Unless otherwise defined, all terms (including technical and scientific terms) used in this specification shall be used with meanings that can be commonly understood by those of ordinary skill in the technical field to which this disclosure pertains. However, this may vary depending on the intentions of those skilled in the art, precedents, the emergence of new technologies, etc.

[0036] Additionally, terms defined in commonly used dictionaries should not be interpreted ideally or excessively unless explicitly and specifically defined otherwise. In certain cases, terms may be arbitrarily selected by the applicant, in which case their meanings will be described in detail in the relevant description. Therefore, the terms used in this disclosure should be defined based on their meaning and the overall content of this disclosure, rather than simply their names.

[0037] Throughout this specification, when a part is said to "include" a certain component, this does not mean that other components may be included, but rather that other components may be excluded, unless specifically stated otherwise. Furthermore, the singular forms used herein also include plural forms unless specifically stated otherwise. Furthermore, the expression "at least one of a, b, and / or c" used throughout this specification can encompass "a alone," "b alone," "c alone," "a and b," "a and c," "b and c," or "all of a, b, and c."

[0038] Meanwhile, terms such as "first and / or second" used in this specification may be used to describe various components, but are only used to distinguish one component from another and are not intended to be limited to the components referred to by those terms. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and the second component may also be referred to as the first component.

[0039] In addition, terms such as “unit”, “module”, etc. described in this specification mean a unit that processes at least one function or operation, which may be implemented by hardware or software, or a combination of hardware and software. In addition, embodiments of the present disclosure in this specification may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various numbers of hardware or / and software configurations that execute specific functions. For example, embodiments of the present disclosure may employ direct circuit configurations such as memory, processing, logic, look-up tables, etc. that may execute various functions under the control of one or more microprocessors or other control devices.

[0040] Similar to the components disclosed herein that can be implemented as software programs or software elements, embodiments of the present disclosure may be implemented in a programming or scripting language such as C, C++, Java, assembler, etc., including various algorithms implemented as a combination of data structures, processes, routines, or other programming constructs. Functional aspects may be implemented as algorithms that run on one or more processors. Furthermore, the present embodiments may employ conventional techniques for at least one of electronic configuration, signal processing, and data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” may be used broadly and are not limited to mechanical and physical components. The terms may include the meaning of a series of software processes (routines) in connection with a processor, etc.

[0041] Each block of the processing flow diagrams attached to this specification and combinations of the flow diagrams can be performed by computer program instructions. These computer program instructions can be installed in a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, so that the instructions, when executed by the processor of the computer or other programmable data processing equipment, create a means for performing the functions described in the flow diagram block(s).

[0042] These computer program instructions may be stored in a computer-available or computer-readable memory that can direct a computer or other programmable data processing device to implement a function in a particular manner, and the instructions stored in the computer-available or computer-readable memory may also produce an article of manufacture that includes instruction means for performing the function described in the flowchart block(s).

[0043] Since the computer program instructions may be installed on a computer or other programmable data processing device, a series of operational steps may be performed on the computer or other programmable data processing device to create a computer-executable process, and the instructions that cause the computer or other programmable data processing device to perform the steps for performing the functions described in the flowchart block(s) may also provide steps for performing the functions described in the flowchart block(s).

[0044] Additionally, each block may represent a module, segment, or portion of code that contains one or more executable instructions for performing a specific logical function(s). Furthermore, in some alternative implementation examples, the functions described in the blocks may occur out of order. For example, two blocks depicted in succession may actually be executed substantially concurrently, or the blocks may sometimes be executed in reverse order, depending on their respective functions.

[0045] The “electronic device” or “terminal” referred to in this specification may be implemented as a computer or portable terminal that can connect to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, laptop, etc. equipped with a web browser, and the portable terminal may include, for example, a wireless communication device that ensures portability and mobility, and may include all kinds of handheld-based wireless communication devices such as communication-based terminals such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), smart phones, tablet PCs, etc. In addition, the “electronic device” or “terminal” referred to in this specification may also include a processor, a memory that stores and executes program data, permanent storage such as a disk drive, a communication port that communicates with an external device, a user interface device such as a touch panel, a key, a button, etc.

[0046] In the present disclosure, methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on a processor. The computer-readable recording medium may include a magnetic storage medium (e.g., read-only memory (ROM), random-access memory (RAM), floppy disks, hard disks, etc.) and an optical reading medium (e.g., CD-ROM, DVD: Digital Versatile Disc)). The computer-readable recording medium may be distributed and executed on network-connected computer systems.

[0047] Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In describing the embodiments, descriptions of technical details that are well known in the technical field to which the present invention pertains and are not directly related to the present invention will be omitted. This is to convey the gist of the present invention more clearly without obscuring unnecessary explanation. For the same reason, some components in the accompanying drawings are exaggerated, omitted, or schematically depicted. Furthermore, the size of each component does not entirely reflect the actual size. Throughout this specification, the same reference numerals may refer to the same or corresponding components.

[0048] FIG. 1 is a diagram illustrating a method for acquiring wrist movement data according to one embodiment of the present disclosure.

[0049] One of the most actively discussed issues regarding optimal mouse use in a computer environment is the user's wrist habits. When moving the mouse laterally, rotation of the upper body joints (e.g., wrist, elbow, and shoulder) inevitably occurs. Individuals who rotate their wrist joints more per unit of mouse movement are considered to have stronger wrist habits than others. This can also be interpreted as indicating weaker arm habits.

[0050] To understand the wrist usage habits described above, wrist usage habit measurement technology is required. If a motion capture system were used to measure the rotation of each arm joint as the user moves the mouse, the user's wrist usage habits could be analyzed. However, using a motion capture system requires complex measurement equipment, which can be costly for the user. Motion capture (Mocap) systems are a technology that converts human or animal movements into a digital environment. This process captures physical movements in real time, allowing the data to be applied to a virtual 3D model.

[0051] Accordingly, the present disclosure provides a technology that allows users to analyze their wrist usage habits at a low cost. By analyzing their wrist usage habits at a low cost, users can change and improve their wrist usage habits on their own to improve their wrist health or to play games using a mouse. Therefore, the present disclosure utilizes a dual-sensor mouse, which is relatively inexpensive compared to a motion capture system and is accessible to anyone, to generate and provide users with wrist movement data that quantitatively analyzes a player's wrist usage habits.

[0052] A mouse is an input device that allows users to interact with a computer through a graphical user interface. Users can move the cursor or pointer to a desired location on the screen by moving the mouse on a flat surface, and execute commands by clicking or double-clicking the mouse button. Most mice have two main buttons and a scroll wheel in the middle, which can be used to scroll up and down web pages or documents. Additionally, some mice may have additional buttons for additional functionality.

[0053] A dual-sensor mouse can be a device that maximizes the precision and responsiveness of a mouse by using two independent sensors. Each sensor performs a different function, allowing it to more accurately track the user's movements and provide a better user experience. A dual-sensor mouse may include an optical sensor as the first sensor. The optical sensor can be used to track the mouse's position. The optical sensor continuously captures images of the surface on which the mouse moves and compares them to previous images to accurately determine the mouse's movements. A dual-sensor mouse may further include a laser sensor and / or an additional optical sensor as the second sensor. The second sensor of a dual-sensor mouse can use laser technology or an additional optical sensor to detect more subtle mouse movements and maintain high precision on various surfaces. For example, a mouse may use the second sensor to detect the lift-off distance (LOD), which is the minimum height at which the mouse is lifted without detecting movement. This second sensor can be useful when the user needs to reposition the mouse.

[0054] In one embodiment, the electronic device may receive first movement data indicating information related to movement of the mouse from a first sensor (110) and a second sensor (130) included in the mouse (100). For example, the first sensor (110) may be an optical sensor, and the second sensor (130) may be an optical sensor or a laser sensor. The first sensor (110) and the second sensor (130) may be positioned at a predetermined distance apart from each other with respect to the longitudinal axis of the mouse (100). For example, the first sensor (110) and the second sensor (130) may be positioned on the longitudinal axis of the mouse (100) at a distance (150) between the first sensor and the second sensor.

[0055] The first movement data may include data regarding the movement of the mouse. For example, the first movement data may include first lateral movement information (111) and first longitudinal movement information (113) measured with the location of the first sensor (110) in the mouse (100) as the origin, and second lateral movement information (131) and second longitudinal movement information (133) measured with the location of the second sensor (130) in the mouse (100) as the origin. For another example, the first movement data may include lateral movement information and longitudinal movement information measured with the location (170) of the virtual sensor as the origin. The first movement data based on the location (170) of the virtual sensor may be generated based on data acquired from the first sensor (110) and data acquired from the second sensor (130). Additionally, in some embodiments, the movement data acquired by the first sensor and / or the second sensor may include a lateral position change amount or a lateral mouse movement speed, a longitudinal position change amount or a longitudinal mouse movement speed.

[0056] In one embodiment, the electronic device may determine movement speed data of the mouse (100) based on movement data collected from at least one of the sensors included in the mouse (100). In one embodiment, the electronic device may determine a lateral mouse movement speed of the mouse (100) based on a lateral position change amount obtained from a first sensor (110) and determine this as the first movement speed data. In another embodiment, the electronic device may determine a longitudinal mouse movement speed of the mouse (100) based on a longitudinal position change amount obtained from a second sensor (130) and determine this as the first movement speed. Alternatively, the electronic device may determine the first movement speed data based on movement data collected from a plurality of sensors included in the mouse (100).

[0057] In one embodiment, the electronic device may obtain first rotational strength data indicating a rotational strength of the mouse (100) based on the first movement data. The rotational strength of the mouse may be expressed by angular velocity data indicating a speed at which the mouse (100) is rotated by the user. The electronic device may determine the first rotational strength data based on at least one of first lateral movement information (111), first longitudinal movement information (113), second lateral movement information (131), second longitudinal movement information (133) included in the first movement data, a distance (150) between a position of the first sensor (110) and a position of the second sensor (130), a time period during which the mouse (100) moves, or a sensitivity of the mouse (100). The first rotational strength data may be expressed as an angular velocity based on the following mathematical expression 1. The sensitivity of the mouse (100) is a measure of how far the cursor moves on the screen when the user moves the mouse. A mouse with high sensitivity moves the cursor significantly on the screen even with small movements, while a mouse with low sensitivity requires more physical movement. Mouse sensitivity is typically measured in units of DPI (Dots Per Inch) or CPI (Counts Per Inch), with higher values ​​indicating higher mouse sensitivity. Below, Mathematical Formula 1, which calculates the first rotation intensity data, is described.

[0058]

[0059] (Unit: rad / second)

[0060] means the first rotation intensity data at time t, represents the first transverse movement information (111) (e.g., the transverse position change amount measured by the first sensor), represents the second transverse movement information (131) (e.g., the transverse position change amount measured by the second sensor), represents the sensitivity of the mouse (100), represents the distance (150) between the first sensor and the second sensor, can represent the time the mouse moved.

[0061] In one embodiment, the electronic device can obtain a plurality of pairs of (first movement speed data indicating a movement speed of the mouse, first rotation strength data indicating a rotation strength of the mouse). The electronic device can obtain a pair of (average movement speed of the mouse, average rotation strength of the mouse) based on the plurality of pairs of (first movement speed data, first rotation strength data). The average movement speed of the mouse can be determined based on the first movement data, and the average rotation strength of the mouse can be determined based on the first rotation strength data.

[0062] In one embodiment, the electronic device may obtain second rotation strength data indicating an average wrist rotation strength of a user from the first rotation strength data using a first model including a first correlation between an average mouse rotation strength and an average wrist rotation strength. Assuming that the mouse is properly held in the user's hand during mouse control, the mouse rotation amount may have a strong correlation with the average wrist rotation amount of the mouse user. Accordingly, the first model may include a correlation between the average mouse rotation strength and the average wrist rotation strength. The first average wrist rotation strength and the second average wrist rotation strength are for distinguishing an average wrist rotation strength for indicating a correlation with the average mouse rotation strength and an average wrist rotation strength of a specific user, respectively, for convenience of explanation, and the above is merely an example and the present disclosure is not limited thereto. The first model may be a linear regression model indicating a first correlation between the average mouse rotation strength and the average wrist rotation strength. The linear regression model may be expressed by Equation 2.

[0063]

[0064] is the average wrist rotation strength, is the average rotational strength of the mouse, and k may be a correlation coefficient representing the first correlation. k may be less than 1. Since the rotation of the mouse may be influenced not only by the rotation of the wrist but also by the rotation of the elbow or shoulder, the electronic device may determine k to be less than 1.

[0065] In one embodiment, the electronic device can obtain second rotational strength data based on the first rotational strength data and the correlation coefficient. The electronic device can obtain second rotational strength data indicating the average wrist rotational strength of the user by multiplying the average rotational strength of the mouse by the correlation coefficient (e.g., k) using Equation 2. The average angular velocity can be determined based on the first rotational strength data as described above. Accordingly, the pair (average movement speed of the mouse, average rotational strength of the mouse) can be converted to the pair (average movement speed of the mouse, average wrist rotational strength of the user) using Equation 2.

[0066] In one embodiment, the electronic device may generate wrist movement data of the user based on the second rotation intensity data. The wrist movement data may include information regarding horizontal movement, vertical movement, rotational movement, flexion movement, and / or extension movement of the wrist. The wrist movement data may be quantitatively expressed based on the second rotation intensity data.

[0067] In one embodiment, the wrist movement data may be generated based on a second correlation between the first movement data and the second rotation strength data. There may be a second correlation between the average movement speed of the mouse determined based on the first movement data and the average wrist rotation strength of the user. For example, since a plurality of first lateral average movement speeds and the average wrist rotation strength of the user determined based on the first movement data may be generated, a scatter plot may be represented in a graph with the first lateral movement speed as the x-axis and the average wrist rotation strength as the y-axis. For example, referring to FIG. 3, a plurality of pairs of (average movement speed of the mouse, average wrist rotation strength of the user) may be represented as a scatter plot in a graph. In one embodiment, the electronic device may generate the wrist movement data based on a ratio and / or a slope of the first lateral average movement speed of the mouse and the average wrist rotation strength of the user indicated by the second rotation strength data. In this case, the slope may be data representing a correlation between a plurality of first lateral average movement speed data and a plurality of second rotation strength data when using them. That is, the slope can be a means of providing quantitative information about wrist movement. For example, an electronic device can calculate a slope representing the trend of a data distribution based on a scatter plot, and the calculated slope can provide quantitative information about wrist movement.

[0068] This disclosure can be used to conduct further quantitative research and technological development on the relationship between users' wrist usage habits, mouse usage performance, and upper body workload. Furthermore, this disclosure can provide individual mouse users with useful insights regarding wrist usage in a computer environment. For example, amateur and professional gamers who play for several hours each day can be provided with advice on optimal wrist usage habits, and users who experience wrist pain from mouse usage can be provided with health-related advice.

[0069] FIG. 2 is a diagram illustrating first movement data and second rotation intensity data according to one embodiment of the present disclosure.

[0070] In one embodiment, the first movement data may include lateral movement information (171) and longitudinal movement information (173) measured with the position (170) of the virtual sensor as the origin. When the user turns the wrist to the left, the lateral position change amount and the longitudinal position change amount change, so the electronic device may obtain first rotation intensity data based on the first movement data, and obtain second rotation intensity data indicating an average wrist rotation intensity (210) based on the first rotation intensity data.

[0071] FIG. 3 is a diagram for explaining wrist movement data according to one embodiment of the present disclosure.

[0072] In one embodiment, a scatter plot may be expressed on a graph with the lateral average movement speed (330) as the x-axis and the average wrist rotation strength (310) as the y-axis. The lateral average movement speed (330) may be based on the first lateral movement information (111) or the second lateral movement information (131). The lateral movement speed of the mouse may vary depending on the user's mouse operation for each of a plurality of time stamps, and the corresponding average wrist rotation strength may also vary. Accordingly, the electronic device may display a pair of (average movement speed of the mouse, average wrist rotation strength of the user) corresponding to each time stamp as a scatter plot on the graph. The electronic device may calculate a ratio and / or a slope based on the lateral average movement speed (330) and the average wrist rotation strength (310) corresponding to each time stamp. The electronic device may determine the slope using wrist movement data (350). The wrist movement data (350) may include information indicating that the user's wrist movement increases as the inclination increases when the user moves the mouse laterally. Conversely, the wrist movement data (350) may include information indicating that the user's wrist movement decreases as the inclination decreases when the user moves the mouse laterally.

[0073] In another embodiment, the electronic device may calculate the slope based on the longitudinal average movement speed and the average wrist rotation strength. The longitudinal average movement speed may be based on the first longitudinal movement information (113) or may be based on the second longitudinal movement information (133). The electronic device may calculate the slope based on the longitudinal average movement speed and the average wrist rotation strength (310) corresponding to each time stamp. In this case, the x-axis of the graph may be the longitudinal average movement speed, and the y-axis may be the average wrist rotation strength (310). The slope may be wrist movement data (350). The wrist movement data (350) may include information that the user's wrist movement increases as the slope increases when the user moves the mouse in the longitudinal direction. Conversely, the wrist movement data (350) may include information that the user's wrist movement decreases as the slope decreases when the user moves the mouse in the longitudinal direction.

[0074] In another embodiment, the electronic device may calculate the tilt based on the average movement speed of the mouse and the average wrist rotation strength. The average movement speed of the mouse may be determined based on the average lateral movement speed and the average longitudinal movement speed.

[0075] FIG. 4 is a diagram for explaining wrist movement data according to inclination according to one embodiment of the present disclosure.

[0076] The W-index can be an expression of inclination. The W-index indicates that players, on average, rotate their wrist joints more to move the mouse. In other words, users with a higher W-index can be interpreted as having stronger wrist usage habits. For example, since wrist movement data A (410) has a higher inclination than wrist movement data B (430), it can be seen that users corresponding to wrist movement data A (410) rotate their wrist joints more.

[0077] The electronic device can display the graph shown in Fig. 3 or the graph shown in Fig. 4. Through this, users can intuitively understand their wrist usage habits.

[0078] FIG. 5 is a flowchart illustrating a method for an electronic device to acquire wrist movement data according to one embodiment of the present disclosure.

[0079] In one embodiment, the electronic device may receive first movement data indicating information related to the movement of the mouse from a first sensor and a second sensor included in the mouse (S510). The electronic device may be connected to the mouse wirelessly or by wire and may receive the first movement data from the first sensor and the second sensor included in the mouse.

[0080] In one embodiment, the electronic device can obtain first rotation strength data indicating a rotation strength of the mouse based on the first movement data (S520).

[0081] In one embodiment, the electronic device may obtain second rotation strength data indicating an average wrist rotation strength of the user based on a first model including a first correlation between an average mouse rotation strength and an average wrist rotation strength and the first rotation strength data (S530).

[0082] In one embodiment, the electronic device may generate user wrist movement data based on the second rotation strength data (S540).

[0083] Electronic devices can transmit the generated wrist movement data to other devices or display it on a display. This allows users to check their wrist movement data and modify their mouse usage behavior.

[0084] FIG. 6 is a drawing illustrating an electronic device according to one embodiment of the present disclosure.

[0085] An electronic device (600) according to one embodiment may be a server or a user terminal (e.g., a mobile device, a desktop, a laptop, a personal computer, etc.). Referring to FIG. 6, an electronic device (600) according to one embodiment may include a user interface (610), a processor (630), a display (650), and a memory (670). The user interface (610), the processor (630), the display (650), and the memory (670) may be connected to each other via a communication bus (605).

[0086] A user interface (610) encompasses everything that enables interaction between humans and machines. It may enable a user to manipulate and control systems, software, applications, websites, etc. For example, a user interface may include a graphical user interface, a text-based interface, a voice user interface, a natural user interface (e.g., gestures, touch, etc.), etc.

[0087] The display (650) can display wrist movement data generated by the processor (630).

[0088] The memory (670) can store generated wrist movement data. Additionally, the memory (670) can store various pieces of information generated during the processing of the processor (630) described above. Furthermore, the memory (670) can store various types of data and programs. The memory (670) can include volatile memory or non-volatile memory. The memory (670) can store various types of data using a large-capacity storage medium, such as a hard disk.

[0089] In addition, the processor (630) can perform at least one method or an algorithm corresponding to at least one method described above through FIGS. 1 to 5. The processor (630) may be a data processing device implemented as hardware having a circuit having a physical structure for executing desired operations. For example, the desired operations may include code or instructions included in a program. The processor (930) may be configured as, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an NPU (Neural Network Processing Unit). For example, the hardware-implemented simulation device (900) may include a microprocessor, a central processing unit, a processor core, a multi-core processor, a multiprocessor, an ASIC (Application-Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array).

[0090] The processor (630) can execute a program and control the electronic device (700). The program code executed by the processor (630) can be stored in the memory (770).

[0091] Meanwhile, the embodiments disclosed in this specification may be implemented in the form of a recording medium that stores computer-executable instructions. The instructions may be stored in the form of program code, and when executed by a processor, may generate program modules to perform the operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium. The computer-readable recording medium may include any type of recording medium that stores instructions that can be deciphered by a computer. Examples thereof include ROM, RAM, magnetic tape, magnetic disk, flash memory, and optical data storage devices.

[0092] The above-described embodiments are specific examples for implementing the present disclosure. The present disclosure will encompass not only the above-described embodiments, but also embodiments that can be simply designed or easily modified. Furthermore, the present disclosure will encompass techniques that can be easily modified and implemented using the above-described embodiments. Therefore, the scope of the present disclosure should not be limited to the above-described embodiments, but should be defined not only by the claims set forth below, but also by equivalents of the claims of the present disclosure.

Claims

1. A method for generating user's wrist movement data using a mouse, A step of receiving first movement data indicating information related to movement of the mouse from at least one of a first sensor or a second sensor included in the mouse; A step of obtaining first rotational strength data indicating a rotational strength of the mouse based on the first movement data; A step of obtaining second rotation intensity data indicating the average wrist rotation intensity of the user from the first rotation intensity data using a first model including a first correlation between the average mouse rotation intensity and the average wrist rotation intensity; and A step of generating the user's wrist movement data based on the second rotation strength data; How to generate wrist movement data.

2. In paragraph 1, The first sensor and the second sensor are placed at a certain distance apart from each other. How to generate wrist movement data.

3. In paragraph 1, The above first movement data is, First lateral movement information and first longitudinal movement information measured with the position of the first sensor in the mouse as the origin; and Including second lateral movement information and second longitudinal movement information measured with the position of the second sensor in the mouse as the origin, How to generate wrist movement data.

4. In paragraph 3, The above first rotation strength data is, Determined based on at least one of the first lateral movement information, the first longitudinal movement information, the second lateral movement information, the second longitudinal movement information, the distance between the position of the first sensor and the position of the second sensor, the time the mouse moved, or the sensitivity of the mouse. How to generate wrist movement data.

5. In paragraph 1, The first model is characterized in that it is a linear regression model indicating the first correlation, which is a correlation between the average mouse rotation strength and the average wrist rotation strength. How to generate wrist movement data.

6. In paragraph 5, The first correlation is expressed using a first correlation coefficient, and the first correlation coefficient is less than 1. How to generate wrist movement data.

7. In paragraph 6, The step of obtaining the second rotation intensity data is: A step of obtaining the second rotational strength data based on the mouse average rotational strength determined based on the first rotational strength data and the first correlation coefficient, How to generate wrist movement data.

8. In paragraph 1, The above wrist movement data is, A second correlation between the first movement speed data indicating the movement speed of the mouse extracted from the first movement data and the second rotation strength data is generated based on the second correlation, How to generate wrist movement data.

9. In paragraph 8, The above first movement speed data is, Express the average lateral velocity of the mouse above, The step of generating the user's wrist movement data is as follows: A step of generating the wrist movement data based on a ratio value of the first movement speed data and the second rotation strength data; including, How to generate wrist movement data.

10. In paragraph 9, The above user's wrist movement data is, The larger the above ratio value, the greater the information that the user's wrist movement is expressed. How to generate wrist movement data.

11. A non-transitory computer-readable recording medium having recorded thereon a program for executing the method for generating wrist movement data described in paragraph 1.

12. An electronic device for acquiring wrist movement data according to paragraph 1.

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