Keyboard fingering practice device based on fingerprint identification

Abstract

The invention discloses a keyboard fingering practice device based on fingerprint identification, and relates to the technical field of keyboards, the device comprises a keyboard main body, the upper surface of the keyboard main body is provided with a group of keycaps for a user to press and operate by fingers; the upper surface of each keycap is provided with a cap cover plate for providing a contact interface for fingerprint identification and a liquid crystal panel for displaying fingering practice information, and the keycaps are provided with fingerprint identification modules and pressure sensing modules and are equipped with system processors, so that the positions and actions of the fingers of a user can be accurately monitored in real time; the fingerprint recognition module rapidly and accurately collects fingerprint information, the system processor judges the finger position and accurately positions wrong operation according to the fingerprint information, the operation habit and the skill level of each user can be deeply analyzed based on a large amount of exercise data, personalized exercise suggestions are customized for the users, and in the exercise process of the users, the system analyzes fingering in real time, and the user experience is improved. Once an error action is detected, the error action is immediately corrected, and a user is guided to correct in time.

Description

Technical Field

[0001] The present invention relates to the technical field of keyboards, and particularly to a keyboard fingering practice device based on fingerprint recognition. Background Art

[0002] In the current digital information age, as an important input device of a computer, a keyboard realizes information input through key operations and is widely used in many scenarios such as office work, study, and entertainment. Keyboard fingering practice refers to enabling users to master the correct finger-key assignments and operation skills through targeted training, so as to achieve efficient and accurate keyboard input. It can not only greatly improve the typing speed, but also effectively reduce the error rate, helping users to be more relaxed and convenient when using the keyboard for word processing, data entry and other work, improving work and study efficiency, and is of great significance to modern digital life.

[0003] However, there are certain defects in the existing keyboard fingering practice technologies. Traditional practice tools only rely on key feedback, cannot accurately monitor the finger positions, are difficult to provide personalized training programs for different users, and lack real-time fingering analysis and error correction mechanisms, resulting in users being prone to develop bad typing habits, affecting typing efficiency and accuracy. Therefore, it is of great significance to develop a keyboard fingering practice device based on fingerprint recognition. Summary of the Invention

[0004] The purpose of the present invention is to make up for the deficiencies of the existing technologies, and provides a keyboard fingering practice device based on fingerprint recognition. It can realize real-time and accurate monitoring of the user's finger positions and movements by setting a fingerprint recognition module, a pressure sensing module on the keycaps and equipping a system processor, can provide personalized practice suggestions according to the individual differences of users, analyze and correct incorrect fingerings in real time, and at the same time simulate the real keyboard touch to enhance the user's practice experience.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A keyboard fingering practice device based on fingerprint recognition, the device includes a keyboard main body, a group of keycaps for the user's fingers to press and operate are installed on the upper surface of the keyboard main body, a cap cover plate for providing a contact interface for finger fingerprint recognition and a liquid crystal panel for displaying fingering practice information are installed on the upper surface of each keycap, and the liquid crystal panel is located below the cap cover plate. A fingerprint recognition module for monitoring the user's finger positions and movements is installed inside each keycap, a pressure sensing module for sensing the key pressure to simulate the real keyboard touch feedback is installed inside each keycap, and a system processor and a power module are installed on the upper surface of the keyboard main body;

[0006] The system processor is used to receive and process data from the fingerprint recognition module, the pressure sensing module, and the liquid crystal panel, calculate the comprehensive finger gesture score S according to the formula S = a×T + b×P + c×F, where T is the key press time accuracy score, P is the key press pressure stability score, F is the finger position correctness score, and a + b + c = 1. The system processor analyzes the operation characteristics based on the comprehensive finger gesture score S and the score change trend. If the S value is lower than a specific threshold for multiple consecutive times, it is determined that the user has problems in finger position accuracy, and targeted finger position strengthening practice suggestions are generated for the user and displayed through the liquid crystal panel.

[0007] Furthermore, the edge of the key cap is rounded, and the radius of the rounded corner is 2 millimeters. In the formula for calculating the comprehensive finger gesture score S, the weights of parameters a, b, and c are determined according to the user's practice stage. For the novice stage, a = 0.3, b = 0.3, c = 0.4; for the proficient stage, a = 0.4, b = 0.3, c = 0.3. At different stages, the system processor provides practice content that conforms to the characteristics of this stage based on the score calculated according to the weights and the common problems of the user at this stage.

[0008] Even further, the liquid crystal panel is a touchable display screen with multi-touch function. The display resolution of the liquid crystal panel reaches 1920×1080 pixels. The key press time accuracy score T is calculated by the formula where n c is the number of key press times within the preset error range, and n t is the total number of key press times. When the T value calculated by the system processor is continuously lower than the preset time accuracy standard, a prompt box pops up on the liquid crystal panel, suggesting that the user conduct key press rhythm training and providing a corresponding training plan.

[0009] Even further, the fingerprint recognition module adopts optical fingerprint recognition technology. The fingerprint recognition module adopts a fingerprint feature extraction and matching algorithm based on a convolutional neural network. This algorithm performs feature extraction and matching through convolutional layers and fully connected layers. The fingerprint recognition module collects fingerprint information and transmits it to the system processor. The system processor uses real-time information and combines the data of the pressure sensing module to determine whether the finger position is correct when detecting that the user presses the key cap 2. If the position is incorrect, the correct finger position and an error prompt icon are immediately displayed through the liquid crystal panel.

[0010] Even further, the pressure sensing module is a piezoelectric pressure sensor. A high-speed data transmission interface is adopted between the pressure sensing module and the system processor. The key press pressure stability score P is calculated by the formula where F i is the pressure value of the i-th key press, is the average value of all key pressures, and n is the number of key presses.

[0011] Furthermore, the system processor uses a quad-core processor with a main frequency of 2.5 GHz. The system processor integrates a fingering analysis algorithm library internally. This algorithm library contains various analysis algorithms for different user types and practice stages, dynamically adjusts the analysis strategy according to the user's practice data. The system processor adjusts the practice difficulty according to the comprehensive fingering score S. When S is greater than 80 points, the requirement for practice speed is increased. When S is less than 60 points, the requirement for practice speed is reduced and the frequency of finger position prompts is increased. The system processor analyzes the user's advantages and disadvantages based on the score differences of the user in different practice items, and formulates a personalized practice plan for the user.

[0012] Furthermore, the power supply module uses a rechargeable lithium battery, and the power supply module is also equipped with an intelligent charging management chip. The intelligent charging management chip automatically adjusts the charging current and voltage according to the battery's power status and temperature parameters.

[0013] Furthermore, the keyboard body transmits data with external devices through the Bluetooth communication protocol. The keyboard body also supports Wi-Fi connection, establishes a stable network connection with the cloud server, uploads the user's practice data to the cloud server. The cloud server conducts in-depth analysis on the user's practice data and feeds back the analysis results to the system processor. The system processor further optimizes the practice suggestions and error correction prompts customized for the user according to the cloud feedback.

[0014] Compared with the prior art, the keyboard fingering practice device based on fingerprint recognition has the following beneficial effects:

[0015] First, by setting a fingerprint recognition module, a pressure sensing module and equipping a system processor on the keycap, the present invention realizes real-time and accurate monitoring of the user's finger position and movement. The fingerprint recognition module quickly and accurately collects fingerprint information. The system processor judges the finger position based on this, accurately locates incorrect operations. Based on a large amount of practice data, it can deeply analyze each user's operation habits and skill levels, and customize personalized practice suggestions for them. During the user's practice process, the system analyzes the fingering in real time. Once an incorrect movement is detected, it is immediately corrected to guide the user to correct it in time.

[0016] Second, by simulating the real keyboard touch through the pressure sensing module, the present invention enables the user to feel like using a real keyboard during practice, creates an immersive typing practice environment for the user, allows the user to obtain an experience similar to using a real keyboard during the practice process, and enhances the user's satisfaction and usage stickiness with the practice process.

[0017] Other advantages, objects and features of the present invention will be set forth in part in the following description, and in part will be obvious to those skilled in the art based on the study of the following, or can be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 FIG. is a three-dimensional structural schematic diagram of a keyboard fingering practice device based on fingerprint recognition;

[0020] Figure 2 FIG. is a structural schematic diagram of a keyboard main body in a keyboard fingering practice device based on fingerprint recognition;

[0021] Figure 3 FIG. is a structural schematic diagram of a keycap in a keyboard fingering practice device based on fingerprint recognition;

[0022] Figure 4 FIG. is a schematic diagram of the working process of a keyboard fingering practice device based on fingerprint recognition.

[0023] In the figure: 1, keyboard main body; 2, keycap; 201, cap cover plate; 202, liquid crystal panel; 203, fingerprint recognition module; 204, pressure sensing module; 3, system processor; 4, power module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, detail the specific embodiments, structures, features and their effects of the present invention as follows.

[0025] Embodiment 1

[0026] In the new employee training office of a large enterprise, in order to enable new employees to quickly adapt to the high-intensity office rhythm and improve work efficiency, the enterprise introduced a keyboard fingering practice device based on fingerprint recognition and carried out a special keyboard fingering training comprehensively.

[0027] Training begins. The new employee comes to the training workstation equipped with this device. After turning on the device, the power module 4 supplies stable power to the entire equipment. The system processor 3 immediately starts the initialization program to comprehensively self-check components such as the fingerprint recognition module 203, the pressure sensing module 204, and the liquid crystal panel 202. If any component is detected to have a fault, the system will clearly display a fault prompt message on the liquid crystal panel 202, and the technical staff will promptly repair or replace it to ensure the normal operation of the device.

[0028] The new employee gently places a finger on the cap plate 201 of the keycap 2. The fingerprint recognition module 203, relying on advanced optical fingerprint recognition technology and combined with a fingerprint feature extraction and matching algorithm based on a convolutional neural network, collects and identifies fingerprint information in an extremely short time, and then quickly transmits it to the system processor 3. After the system processor 3 confirms the identity of the new employee, according to the characteristics of the new employee being in the novice stage, it determines the weights in the formula for calculating the comprehensive fingering score S = a×T + b×P + c×F, that is, a = 0.3, b = 0.3, c = 0.4.

[0029] The new employee officially starts fingering practice. During the entire practice process, the fingerprint recognition module 203 always remains highly sensitive, continuously monitors the finger position and movement, and precisely captures the placement of the finger every time a key is pressed; the pressure sensing module 204 also works synchronously, senses the key pressure in real time, and accurately transmits the pressure data to the system processor 3. For each key operation, the system processor 3 will quickly obtain the relevant data and based on calculate the accuracy score T of the key pressing time, where n c is the number of times the key pressing time is within the preset error range, and n t is the total number of key presses; according to calculate the stability score P of the key pressing pressure, F i is the pressure value of the i-th key press, is the average value of all key pressing pressures, and n is the number of key presses; determine the finger position correctness score F through the judgment of the finger position by the fingerprint recognition module 203 for each key press, and then obtain the comprehensive fingering score S.

[0030] Once the new employee makes a finger position error, when the system processor 3 detects the moment of pressing the keycap 2, combining the data of the fingerprint recognition module 203 and the pressure sensing module 204, it quickly judges the error and immediately displays the correct finger position and error prompt message on the liquid crystal panel 202 in a prominent color and icon. If the T value calculated by the system processor 3 is continuously lower than the preset time accuracy standard, the liquid crystal panel 202 will pop up a semi-transparent prompt box, suggesting that the new employee conduct key pressing rhythm training, and at the same time provide a detailed training plan, such as specific key pressing rhythm practice tracks, and display the expected training effect and completion time.

[0031] As the practice progresses continuously, the system processor 3 continuously and deeply analyzes the practice data of new employees. If the S value is lower than a specific threshold for several consecutive times, and it is judged from the trend of score changes that there are problems with the finger position accuracy of new employees, the system processor 3 will generate a set of targeted finger position strengthening practice suggestions for new employees. For example, conduct special practice for easily confused key positions, and display the practice content and requirements in a vivid picture and text form through the liquid crystal panel 202. At the same time, the system processor 3 will also dynamically adjust the practice difficulty according to the S value. When S is less than 60 points, reduce the requirement for practice speed, so that new employees have more time to adjust their fingerings, and at the same time increase the frequency of finger position prompts to ensure that new employees can correct their mistakes in time.

[0032] During the practice process, the pressure sensing module 204 simulates the real keyboard touch to create a realistic typing environment for new employees and improve the practice experience. In addition, the keyboard main body 1 uploads the practice data of new employees to the enterprise's dedicated training management cloud server through a high-speed and stable Wi-Fi connection. The cloud server uses big data analysis technology to deeply mine and analyze the data, and timely feedback the analysis results to the system processor 3. The system processor 3 further optimizes the practice suggestions and error correction prompts customized for new employees according to the cloud feedback. For example, according to the characteristics of the work content of new employees in different departments, recommend more targeted practice content. For example, for the copywriting editing position, increase the text input practice, and for the data processing position, strengthen the practice of number keys and function keys.

[0033] To sum up: After a period of intensive practice, after new employees use this device, both their typing speed and accuracy have been significantly improved. In the training effect assessment, the average typing speed of new employees has increased and the error rate has decreased. The function of this device to accurately locate incorrect operations and provide personalized practice suggestions has helped new employees effectively correct bad typing habits and develop correct fingering habits. At the same time, the design of simulating the real keyboard touch and the recommendation of personalized practice content have improved the enthusiasm and concentration of new employees' practice, enhanced their satisfaction and participation in the practice process, laid a solid foundation for new employees to quickly adapt to the office keyboard input requirements and improve work efficiency, and received unanimous praise from new employees and the training department.

[0034] Embodiment 2

[0035] In the teaching of the school's basic computer courses, improving the keyboard fingering skills of students is one of the important teaching goals. The school has fully equipped the computer classrooms with a keyboard fingering practice device based on fingerprint recognition to optimize the teaching effect and help students better master the keyboard input skills.

[0036] At the beginning of the course, the students enter the computer classroom and turn on the keyboard fingering practice device based on fingerprint recognition. The power supply module 4 starts immediately, providing stable power support for the entire device. The system processor 3 quickly executes the self-check program to comprehensively check components such as the fingerprint recognition module 203, the pressure sensing module 204, and the liquid crystal panel 202. If any abnormality is detected, the system will display detailed fault information through the liquid crystal panel 202, facilitating timely repair by technicians to ensure the normal operation of the device.

[0037] The students place their fingers on the cap plate 201 of the key cap 2. The fingerprint recognition module 203 quickly collects fingerprint information and uses the fingerprint feature extraction and matching algorithm based on convolutional neural network for recognition. The recognition result is transmitted to the system processor 3. After the system processor 3 confirms the student's identity, since it is the first practice, according to the weights in the fingering comprehensive score calculation formula S = a×T + b×P + c×F for the novice stage, a = 0.3, b = 0.3, and c = 0.4.

[0038] The students start fingering practice. During the practice process, the fingerprint recognition module 203 monitors the finger position and movement of the students in real-time, and the pressure sensing module 204 synchronously senses the key pressure. For each key operation, the system processor 3 collects relevant data. The key time accuracy score T is calculated by the formula where n c represents the number of times the key time is within the preset error range, and n t is the total number of key presses; the key pressure stability score P is obtained according to the formula F i represents the pressure value of the i-th key press, is the average value of all key pressures, and n is the number of key presses; the finger position correctness score F is determined by the fingerprint recognition module 203's judgment of the finger position during each key press. The system processor 3 calculates the fingering comprehensive score S based on these three scores.

[0039] When the students make a finger position error, the system processor 3, at the moment of detecting the key cap 2 being pressed, combines the data of the fingerprint recognition module 203 and the pressure sensing module 204 to quickly judge the error and immediately display the correct finger position and error prompt icon in a prominent manner through the liquid crystal panel 202. If the T value calculated by the system processor 3 is continuously lower than the preset time accuracy standard, the liquid crystal panel 202 will pop up an interactive prompt box, suggesting that the students conduct key press rhythm training. The prompt box not only provides corresponding training programs, such as animated demonstrations of rhythm practice, virtual key following practice, etc., but also sets buttons such as "Start Training" and "Temporarily Not Train" for the students to choose.

[0040] As the practice progresses, the system processor 3 continuously analyzes the student's practice data. If the S value is lower than a specific threshold for multiple consecutive times, and the score change trend shows that the student has problems with finger position accuracy, the system processor 3 will generate targeted finger position reinforcement practice suggestions for the student. These suggestions will be displayed on the LCD panel 202 in the form of a task list, such as "perform 10 minutes of baseline key position reinforcement exercises, focusing on the key accuracy of the left index finger and the right index finger", and will also provide an estimated completion time and a possible score range for improvement.

[0041] In addition, the system processor 3 will adjust the difficulty of the exercise according to the S value. When S is less than 60 points, the exercise speed requirement will be reduced and the finger position prompt frequency will be increased. When S is greater than 80 points, the exercise speed requirement will be appropriately increased to further improve students' typing ability.

[0042] During the practice process, the pressure sensing module 204 simulates the touch of a real keyboard, creating a realistic typing environment for students, making them feel as if they are using a real office keyboard, enhancing the immersion and fun of the practice. Moreover, the keyboard body 1 uploads the students' practice data to the school's teaching management cloud server via the campus network via Wi-Fi connection.

[0043] The cloud server uses big data analysis technology to conduct in-depth mining and analysis of data, such as analyzing the fingering characteristics and common errors of students in different classes and at different learning progress levels, and then feeds back the analysis results to the system processor 3. The system processor 3 further optimizes the customized practice suggestions and error correction prompts for students based on these feedbacks. For example, in case of the common problem of inaccurate left-hand little finger key pressing in a certain class, the system will push intensive practice tasks specifically for the left-hand little finger to the students in that class.

[0044] To sum up: After a period of practice, students' overall typing speed and accuracy have been significantly improved after using the device. The device can accurately locate students' incorrect operations and provide personalized practice suggestions to help students gradually correct bad typing habits and develop correct fingering habits. At the same time, the design that simulates the touch of a real keyboard improves students' enthusiasm and concentration in practice, increases students' satisfaction and participation in the practice process, effectively improves the effect of keyboard fingering teaching in basic computer courses, and lays a solid foundation for students' subsequent computer learning and application.

[0045] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention. Although the present invention has been disclosed above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the above-disclosed technical content without departing from the technical solution of the present invention. However, as long as it does not depart from the technical solution content of the present invention, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A keyboard fingering practice device based on fingerprint recognition, characterized in that, The device includes a keyboard body (1). A set of keycaps (2) for users to press and operate with their fingers are installed on the upper surface of the keyboard body (1). On the upper surface of each keycap (2), a cap cover plate (201) providing a contact interface for finger fingerprint recognition and a liquid crystal panel (202) for displaying fingering practice information are installed. The liquid crystal panel (202) is located below the cap cover plate (201). Inside each keycap (2), a fingerprint recognition module (203) for monitoring the position and movement of the user's finger is installed. Inside each keycap (2), a pressure sensing module (204) for sensing the key pressure to simulate the tactile feedback of a real keyboard is installed. A system processor (3) and a power module (4) are installed on the upper surface of the keyboard body (1). The system processor (3) is used to receive and process data from the fingerprint recognition module (203), the pressure sensing module (204), and the liquid crystal panel (202), and calculate the comprehensive fingering score S according to the formula S = a×T + b×P + c×F, where T is the key press time accuracy score, P is the key pressure stability score, F is the finger position correctness score, and a + b + c = 1. The system processor (3) analyzes the operation characteristics based on the comprehensive fingering score S and the score change trend. If the S value is lower than a specific threshold for multiple consecutive times, it is judged that the user has problems in finger position accuracy, and targeted finger position strengthening practice suggestions are generated for the user and displayed through the liquid crystal panel (202).

2. The fingerprint recognition-based keyboard fingering practice device according to claim 1, wherein The edge of the cap cover plate (201) is rounded with a radius of 2 millimeters. In the formula for calculating the comprehensive fingering score S, the weights of the parameters a, b, and c are determined according to the user's practice stage. For the novice stage, a = 0.3, b = 0.3, c = 0.

4. For the proficient stage, a = 0.4, b = 0.3, c = 0.

3. At different stages, the system processor (3) provides practice content that conforms to the characteristics of the stage according to the score calculated based on the weights and the common problems of the user at this stage.

3. The fingerprint recognition-based keyboard fingering practice device according to claim 1, wherein, The liquid crystal panel (202) is a touchable display screen with a multi-touch function. The display resolution of the liquid crystal panel (202) reaches 1920×1080 pixels. The button time accuracy score T is calculated by the formula where n c is the number of times the button time is within the preset error range, and n t is the total number of button presses. When the T value calculated by the system processor (3) is continuously lower than the preset time accuracy standard, a prompt box pops up on the liquid crystal panel (202), suggesting that the user conduct button rhythm training and providing a corresponding training plan.

4. The fingerprint recognition-based keyboard fingering practice device according to claim 1, wherein The fingerprint recognition module (203) adopts optical fingerprint recognition technology. The fingerprint recognition module (203) adopts a fingerprint feature extraction and matching algorithm based on a convolutional neural network. This algorithm performs feature extraction and matching through convolutional layers and fully connected layers. The fingerprint recognition module (203) collects fingerprint information and transmits it to the system processor (3). The system processor (3) uses real-time information and combines the data of the pressure sensing module (204) to judge whether the finger position is correct at the moment when the user presses the keycap (2). If the position is incorrect, the correct finger position and an error prompt icon are immediately displayed through the liquid crystal panel (202).

5. The fingerprint recognition-based keyboard fingering practice device according to claim 1, characterized in that, The pressure sensing module (204) is a piezoelectric pressure sensor. A high-speed data transmission interface is adopted between the pressure sensing module (204) and the system processor (3). The key pressure stability score P is calculated by the formula where F i is the pressure value of the i-th key press, is the average value of all key pressures, and n is the number of key presses.

6. The fingerprint recognition-based keyboard fingering practice device according to claim 1, wherein, The system processor (3) adopts a quad-core processor with a main frequency reaching 2.5 GHz. The system processor (3) integrates a fingering analysis algorithm library internally. This algorithm library contains various analysis algorithms for different user types and practice stages, dynamically adjusts the analysis strategy according to the user's practice data. The system processor (3) adjusts the practice difficulty according to the comprehensive fingering score S. When S is greater than 80 points, the requirement for practice speed is increased. When S is less than 60 points, the requirement for practice speed is decreased and the frequency of finger position prompts is increased. The system processor (3) analyzes the user's strengths and weaknesses based on the score differences of the user in different practice items, and formulates a personalized practice plan for the user.

7. The fingerprint recognition-based keyboard fingering practice device according to claim 1, wherein The power supply module (4) adopts a rechargeable lithium battery. The power supply module (4) is also equipped with an intelligent charging management chip, and the intelligent charging management chip automatically adjusts the charging current and voltage according to the battery's power state and temperature parameters.

8. The fingerprint recognition-based keyboard fingering practice device according to claim 1, characterized in that, The keyboard body (1) transmits data with external devices through the Bluetooth communication protocol. The keyboard body (1) also supports Wi-Fi connection, establishes a stable network connection with the cloud server, uploads the user's practice data to the cloud server. The cloud server conducts in-depth analysis on the user's practice data and feeds back the analysis results to the system processor (3). The system processor (3) further optimizes the practice suggestions and error correction prompts customized for the user according to the cloud feedback.

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