Calligraphy writing body data visual monitoring method and system based on body perception

Abstract

The invention provides a calligraphy writing body data visual monitoring method and system based on body perception, and relates to the technical field of calligraphy teaching. According to the method, data such as body actions, pen holding pressure, tracks and wrist angles of a writer are collected in real time by installing at least one set of sensors, filtering, fusion and feature extraction are conducted on the data, indexes such as writing precision and posture stability are calculated, then the data are converted into visual feedback through the visualization technology, and the state of the writer can be adjusted conveniently. The system comprises a sensor module, a data collecting and processing module, a visual feedback module and a dynamic adjusting module, all the modules cooperate, and comprehensive monitoring and real-time feedback of the writing process are achieved. The multi-sensor fusion and data visualization technology is utilized, the action precision and the posture stability in the writing process are objectively quantified, the problems of feedback lagging and high evaluation subjectivity of traditional teaching are solved, and scientificity and effectiveness of calligraphy teaching are improved.

Description

Technical Field

[0001] The present invention relates to the field of calligraphy teaching technology, and in particular to a method and system for visually monitoring calligraphy writing body data based on body perception. Background Art

[0002] As an important part of traditional Chinese culture, calligraphy emphasizes the coordination of the writer's physical movements and mental state to achieve an artistic effect of smooth characters and vivid artistic charm. However, in modern calligraphy education, traditional teaching methods often focus on the teaching of techniques and theoretical explanations, while neglecting physical perception and movement coordination during the writing process. This makes it difficult for students to fully understand the core skills of calligraphy. In particular, in actual writing, how to accurately perceive and control body posture, pen grip strength, stroke continuity, etc. are often difficult to fully convey through language and demonstration. Therefore, calligraphy learners often have the problem of not being able to accurately master writing skills in actual practice. Especially for beginners, how to effectively understand and experience the essence of calligraphy is particularly difficult.

[0003] In recent years, with the advancement of science and technology, the application of sensor technology and data processing technology has brought new development opportunities to calligraphy education. By real-time monitoring of the writer's body movements, muscle activity, pen grip pressure, wrist angle and other physiological data, combined with data processing and analysis, it is possible to more scientifically reveal the key factors in the writing process, thereby helping learners better understand and master calligraphy skills. In the existing technology, some data monitoring systems have been applied to calligraphy teaching, such as electromyography sensors to monitor muscle activity, gyroscopes and accelerometers to monitor movement trajectory and angle, etc. However, how to convert this abstract physiological data into intuitive and easy-to-understand feedback and compare and analyze it with expert data so that learners can quickly identify and improve deficiencies remains a difficult problem in current technology.

[0004] Therefore, a device for visually monitoring and providing feedback on calligraphy writing data based on body perception has been proposed. Through multi-sensor integration, real-time data analysis, and data visualization, it aims to provide calligraphy learners with scientific and intuitive learning feedback, helping them better understand the relationship between body movements and calligraphy skills, and effectively improving their calligraphy learning outcomes. The innovation of this device lies in its ability to transform the dynamic body data of calligraphy writing into easily understandable knowledge through visualization technology, providing a new feedback method and auxiliary tool for calligraphy education. Summary of the Invention

[0005] In order to solve the technical problem that the conventional calligraphy teaching method in the prior art only relies on oral explanation and static demonstration, and cannot monitor and quantify key parameters such as body action, force control and posture stability in the writing process, the present application provides a calligraphy writing body data visual monitoring method and system based on body perception.

[0006] The technical scheme provided by the present application is as follows:

[0007] The first aspect is:

[0008] The calligraphy writing body data visual monitoring method based on body perception provided by the present application comprises:

[0009] S1, real-time monitoring of body action of a calligraphy writer by at least one group of sensors, wherein the sensors include inertial sensors, electromyographic sensors, angle sensors, acceleration sensors and pressure sensors;

[0010] S2, acquiring action data of the calligraphy writer in the writing process, wherein the action data includes hand movement trajectory, writing speed, pen holding pressure and wrist angle of the writer;

[0011] S3, calculating writing action precision and writing posture stability according to the action data, wherein the writing action precision is used to evaluate the accuracy and consistency of the writing trajectory of the calligraphy writer in the writing process, and the writing posture stability is used to evaluate the stability of the posture of the hand and wrist of the calligraphy writer in the writing process;

[0012] S4, obtaining a comprehensive evaluation result of the writing state of the writer by analyzing the writing action precision and the writing posture stability;

[0013] S5, visualizing the evaluation result and providing it to the writer through a feedback device, wherein the feedback device includes a display screen, a tactile feedback device and an audio feedback device, so as to enable the writer to adjust and optimize the writing posture;

[0014] S6, dynamically adjusting the monitoring parameters according to the adjustment information fed back by the writer, so as to adapt to individual differences of different writers.

[0015] The second aspect is:

[0016] The calligraphy writing body data visual monitoring system based on body perception provided by the present application comprises:

[0017] At least one group of sensors, a data acquisition module, a data analysis module, a visual feedback module and an adjustment module;

[0018] The sensors are used to monitor the body action data of the calligraphy writer in real time;

[0019] The data acquisition module is configured to receive and store the writing action data collected by the sensors.

[0020] The data analysis module is configured to calculate precision parameters and stability parameters based on the writing action data, and generate a comprehensive evaluation result.

[0021] The visual feedback module is configured to provide the evaluation result to the writer in the form of graphics, sound or haptic, for the writer to adjust the writing posture.

[0022] The adjustment module is configured to dynamically adjust the monitoring parameters and feedback thresholds according to the feedback of the writer, to adapt to the individual needs of different writers.

[0023] The technical solution provided by the present application has at least the following beneficial effects:

[0024] (1) In the present application, by integrating multiple high-precision sensors, real-time monitoring of key data such as body movements, pen pressure, wrist angle, etc. of the writer during calligraphy writing is realized. By using high-frequency acquisition of sensor data and data fusion technology, the writing dynamics are accurately recorded, effectively solving the problem of lack of real-time feedback in traditional teaching, and providing a solid data foundation for subsequent action analysis and skill improvement.

[0025] (2) In the present application, the collected raw data is filtered, fused, feature extracted and index calculated, and then quantitative indexes such as writing action precision and writing posture stability are generated. Through this technical means, the system can objectively evaluate the accuracy of handwriting and the stability of writing posture in the writing process, solve the defects of strong subjectivity of evaluation means and inability to accurately quantify writing quality in traditional calligraphy teaching, and provide scientific and quantitative improvement basis for the writer.

[0026] (3) In the present application, data visualization technology is used to convert complex body data into intuitive and easy-to-understand charts, animations and color coding information, and combined with display, haptic and audio feedback modes, real-time feedback is provided to the writer. Through this comprehensive feedback mechanism, the writer can immediately understand their own shortcomings and advantages in the writing process, so as to realize dynamic adjustment and personalized training, effectively solve the problem of delayed feedback and difficulty in targeted training in traditional calligraphy teaching, and promote the development of calligraphy teaching towards digitalization and intelligentization. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative effort.

[0028] Figure 1 The flowchart of the handwriting writing body data visualization monitoring method based on body perception provided by the embodiment of the present application is shown in the figure.

[0029] Figure 2 The writing action precision calculation flowchart of the handwriting writing body data visualization monitoring method based on body perception provided by the embodiment of the present application is shown in the figure.

[0030] Figure 3 The writing posture stability calculation flowchart of the handwriting writing body data visualization monitoring method based on body perception provided by the embodiment of the present application is shown in the figure.

[0031] Figure 4 The feedback flowchart of the writing precision of the handwriting writing body data visualization monitoring method based on body perception provided by the embodiment of the present application is shown in the figure.

[0032] Figure 5 The structural schematic diagram of the handwriting writing body data visualization monitoring system based on body perception provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0033] The technical solutions in the present application will be described below with reference to the drawings.

[0034] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0035] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent. "Of", "corresponding" and "corresponding" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent.

[0036] In the embodiments of the present application, sometimes the subscript such as W1 may be mistakenly written in the form of non-subscript such as W1, and the meanings expressed thereby are consistent when the difference is not emphasized.

[0037] To make the technical problems, technical solutions and advantages to be solved by the present application clearer, specific embodiments will be described in detail below with reference to the drawings.

[0038] Reference is made to the accompanying drawings Figure 1 , which shows a flowchart of the method for monitoring calligraphy writing body data visualization based on body perception provided by the embodiments of the present application.

[0039] The embodiments of the present application provide a method for monitoring calligraphy writing body data visualization based on body perception, which can be implemented by a device for monitoring calligraphy writing body data visualization based on body perception, which can be a terminal or a server, and the processing flow of the method for monitoring calligraphy writing body data visualization based on body perception can include the following steps:

[0040] S1, real-time monitoring of the body action of a calligraphy writer by at least one set of sensors, including inertial sensors, electromyography sensors, angle sensors, acceleration sensors and pressure sensors.

[0041] It can be understood that the system monitors the body action of a calligraphy writer in real time by installing at least one set of sensors, including inertial sensors, electromyography sensors, angle sensors, acceleration sensors and pressure sensors. The sensors work cooperatively after pre-calibration to capture the dynamic changes of each part of the writer during the writing process, thereby providing an accurate and comprehensive physical signal basis for subsequent data acquisition and ensuring the high precision and stability of real-time monitoring data.

[0042] S2, obtaining action data of the calligraphy writer during the writing process, including the hand movement trajectory, writing speed, pen holding pressure and wrist angle of the writer.

[0043] It can be understood that the system collects action data during the writing process from the above-mentioned sensors, which specifically includes the hand movement trajectory, writing speed, pen holding pressure and wrist angle of the writer. The collected data is subjected to preliminary processing and time sequence synchronization, so that each frame of data can accurately reflect the subtle changes during the writing process, thereby laying a data foundation for subsequent fine calculation and analysis.

[0044] S3, calculating the writing action precision and the writing posture stability according to the action data, the writing action precision being used to evaluate the accuracy and consistency of the writing trajectory of the calligraphy writer during the writing process, and the writing posture stability being used to evaluate the stability of the posture of the hand and wrist of the calligraphy writer during the writing process.

[0045] It can be understood that after the data collection is completed, the system calculates two key parameters: writing action accuracy and writing posture stability according to the collected action data. The writing action accuracy evaluates the accuracy and consistency of the trajectory in the writing process by comparing the deviation between the actual trajectory and the ideal writing trajectory; and the writing posture stability quantifies the stability of the posture in the writing process by analyzing the fluctuation of the hand and wrist angle changes. This step uses algorithms to deeply analyze the data, thereby converting complex dynamic data into intuitive numerical indicators.

[0046] S4, a comprehensive evaluation result of the writing state of the writer is obtained by analyzing the writing action accuracy and the writing posture stability.

[0047] It can be understood that the system comprehensively analyzes the writing action accuracy and the writing posture stability indicators calculated, and obtains a comprehensive evaluation result reflecting the overall writing state of the writer through data fusion and multi-angle evaluation. This comprehensive result considers both trajectory accuracy and posture stability, thereby providing an objective indicator that comprehensively reflects the writing quality of the writer.

[0048] S5, the evaluation result is visualized and provided to the writer through a feedback device, and the feedback device includes a display screen, a tactile feedback device and an audio feedback device, so that the writer can adjust and optimize the writing posture.

[0049] It can be understood that after the comprehensive evaluation result is generated, the system visualizes the result, converts the data into intuitive forms such as graphics, numbers and color coding, and transmits feedback information to the writer in real time through various terminals such as display screens, tactile feedback devices and audio feedback devices. The writer can understand the shortcomings in the writing process through these intuitive feedbacks in a timely manner, and adjust the pen holding force, writing speed and posture according to the prompts to further optimize the writing action.

[0050] S6, according to the adjustment information fed back by the writer, the monitoring parameters are dynamically adjusted to adapt to the individual differences of different writers.

[0051] It can be understood that the system dynamically adjusts the monitoring parameters and evaluation model according to the adjustments made by the writer to the feedback information by collecting new action data and comparing the changes before and after, to adapt to the individual differences of different writers and the real-time changes of the writing state. This adaptive adjustment mechanism ensures that the system can continuously optimize the monitoring accuracy and feedback effect, and ultimately helps the writer to continuously improve the calligraphy skills and writing performance.

[0052] In one possible implementation, as shown in Figure 2 the writing action accuracy further includes:

[0053] S201, calculating the deviation value between the writing path and the ideal writing path using a Bezier curve fitting algorithm based on the hand motion trajectory of the writer;

[0054] S202, calculating the average absolute value of the deviation between the hand motion trajectory and the ideal path, and using the value to measure the writing accuracy;

[0055] S203, when the deviation value is lower than the preset threshold, it is determined that the writing accuracy of the writer is high; otherwise, when the deviation value is higher than the threshold, the writer is fed back to adjust.

[0056] In a possible implementation, as shown in Figure 3 the writing posture stability further includes:

[0057] S301, calculating the angle change rate of the hand and wrist during writing based on the motion data of the hand and wrist;

[0058] S302, using a low-pass filter to smooth the angle change rate data and remove high-frequency noise, and the low-pass filter uses a first-order Butterworth low-pass filter, and the specific formula is:

[0059]

[0060] wherein s is a complex frequency variable, representing the input signal of the filter, ω c is the cutoff frequency of the filter, which determines the frequency response of the filter;

[0061] S303, calculating the standard deviation of the smoothed angle change rate, and the lower the standard deviation value, the more stable the writing posture;

[0062] S304, when the standard deviation value is lower than the preset stability threshold, it is determined that the writing posture is relatively stable, otherwise, the writer is fed back to adjust.

[0063] In a possible implementation, the deviation value further includes:

[0064] The deviation value calculation method between the writing path and the ideal path is:

[0065]

[0066] wherein Δ represents the deviation value between the writing path and the ideal path, P real (i) is the actual writing position of the i-th point, P ideal (i) is the ideal writing position of the i-th point, and n is the total number of trajectory points.

[0067] In a possible implementation, the calculation method of the angle change rate further includes:

[0068]

[0069] wherein Rate represents the rate of change of angle, Δθ is the amount of change in angle, in degrees, and Δt is the time interval, in seconds, and Δθ is the amount of change in angle of the hand and wrist over the time interval Δt.

[0070] In one possible implementation, as shown in FIG. 1, the feedback of writing accuracy further comprises: Figure 4

[0071] S601, the display screen displays the real-time deviation of the writing trajectory;

[0072] S602, the haptic feedback device prompts the writer to adjust the writing posture through vibration;

[0073] S603, the audio prompt device reminds the writer to adjust the writing action through sound.

[0074] In one possible implementation, the action data includes the heart rate data of the writer, and the physiological state of the writer is further analyzed.

[0075] In one possible implementation,

[0076] The feedback device dynamically adjusts the writing accuracy and stability threshold according to the feedback of the writer.

[0077] In one possible implementation, the evaluation result further comprises evaluating the psychological state of the writer, and giving suggestions based on the evaluation result.

[0078] In the first embodiment of the present application, mainly for professional calligraphers, the hand movement trajectory, pen holding pressure, wrist angle and writing speed of the writer are collected in real time by high-precision sensors, and the collected data are comprehensively analyzed by the system to calculate the writing action accuracy parameters and the writing posture stability parameters described in the claims, while introducing the writing force balance coefficient E p and the writing rhythm continuity index R c , so as to more comprehensively evaluate and feedback the writing behavior of the writer. The specific implementation steps are as follows:

[0079] 1. System initialization and sensor calibration

[0080] 1.1 Install and fix the sensor module, which includes:

[0081] Inertial Measurement Unit (IMU): contains an accelerometer and a gyroscope, used to collect hand movement trajectory and wrist angle data;

[0082] ​Pressure sensor: used to detect the pen-holding pressure during writing;

[0083] Optical or magnetic positioning sensor (optional): used to assist in extracting the precise position of the hand.

[0084] 1.2 Zero-point calibration and sensitivity calibration of each sensor are performed to ensure the accuracy of data acquisition.

[0085] 1.3 Set the data sampling frequency (e.g., 100 samples per second) and synchronize the timestamps of each sensor data.

[0086] 2. Data acquisition and preprocessing

[0087] 2.1 Before writing begins, the system starts the data acquisition module and continuously collects hand motion trajectory, pen-holding pressure, and angle change data;

[0088] 2.2 Preprocess the raw data:

[0089] Smooth the angle data and motion trajectory data using filtering algorithms (e.g., first-order Butterworth low-pass filter);

[0090] Use mean filtering to remove high-frequency noise from pressure data;

[0091] Fuse multi-sensor data according to a unified time axis to ensure data synchronization.

[0092] 3. Writing action precision and posture stability parameter calculation

[0093] 3.1 Calculate the deviation value between the actual motion trajectory of the writer and the preset ideal trajectory using the Bezier curve fitting algorithm, and calculate the average deviation value Δ to obtain the writing action precision parameter;

[0094] 3.2 Calculate the angle change rate of the hand and wrist angle data, and after low-pass filtering, calculate the standard deviation as the writing posture stability parameter.

[0095] 4. To further quantify the balance of force and the coherence of rhythm during writing, this embodiment introduces the following two formulas:

[0096] To measure the fluctuation of pen-holding pressure during writing and reflect the balance of writing force, the writing force balance coefficient E p is calculated as follows:

[0097]

[0098] Where P i is the pen-holding pressure value at the i-th sampling, The average pen pressure value during the entire writing process is calculated by n is the total number of sampling data during the writing process, and δ is a small constant (for example, 0.01) to prevent the denominator from being zero, which is calibrated according to the sensitivity of the sensor.

[0099] This formula can quantitatively reflect the amplitude of pressure fluctuation during writing, and the lower the value, the more balanced the pen holding force.

[0100] The writing structure coherence index R c is used to measure the stability of writing speed changes during writing, that is, the coherence of writing rhythm.

[0101]

[0102] where v i is the instantaneous writing speed calculated at the i-th sampling, and the calculation method is as follows:

[0103]

[0104] where (x i , y i ) represents the two-dimensional coordinates of the hand at the i-th sampling, v i-1 is the instantaneous writing speed at the previous sampling, n is the total number of samplings, and ∈ is a small constant (for example, 0.01) to prevent the denominator from being zero. γ is used to ensure a positive offset for the function internal parameters (for example, 1).

[0105] This formula comprehensively reflects the relative amplitude and coherence of speed changes during writing, and a lower value indicates a more stable writing rhythm.

[0106] 5. The data processing module calculates the writing action precision, posture stability, force balance coefficient E p , and rhythm coherence index R c , and presents them on the display screen in the form of graphics, numbers, and color coding through the visual feedback module in real time;

[0107] 5.2 At the same time, the system provides immediate feedback to the writer through tactile feedback devices (such as vibration devices) and audio prompt devices to help the writer adjust the writing posture;

[0108] 5.3 According to the writer's feedback and historical data, dynamically adjust the monitoring parameters and thresholds to realize personalized writing data monitoring and evaluation.

[0109] 6. Data storage and subsequent analysis

[0110] 6.1 After the writing is completed, the system uploads all the collected and calculated data to the data storage module;

[0111] 6.2 Users can analyze historical data, compare evaluations, and provide feedback on training effects through dedicated software, thereby adjusting training strategies or providing targeted guidance.

[0112] Through the above implementation steps, professional calligraphy artists can obtain real-time fine data feedback during their writing process. They can not only understand the writing trajectory deviation and posture stability, but also understand the balance of pen-holding force and writing rhythm through the force balance coefficient and rhythm continuity index. This helps them continuously optimize writing movements and improve calligraphy skills in long-term training.

[0113] In the second embodiment of the present application, mainly for calligraphy teaching environment, by equipping each student with a portable sensor module, a multi-user data acquisition and analysis system is constructed to realize real-time monitoring of the writing state of all students in the classroom, and the student data is displayed on the teacher's end to assist the teacher's guidance and the student's self-adjustment. The specific implementation steps are as follows:

[0114] 1. System networking and device distribution

[0115] 1.1 Equip each student with a portable sensor module including IMU, pressure sensor, and heart rate sensor;

[0116] 1.2 Connect the sensor modules of each student to the central data acquisition terminal through a wireless network (such as Wi-Fi or Bluetooth) to realize real-time data transmission;

[0117] 1.3 The central terminal uniformly initializes and synchronizes all student sensor modules to ensure the consistency of data sampling.

[0118] 2. Data acquisition and preprocessing

[0119] 2.1 Each student starts the system before starting writing to collect real-time data of writing movements, pen-holding pressure, hand movement trajectory, wrist angle, and heart rate;

[0120] 2.2 The preprocessing process is similar to that of embodiment 1, and each data is filtered and fused to ensure data stability and accuracy;

[0121] 2.3 For each student, the system independently calculates the writing movement accuracy parameter and the posture stability parameter.

[0122] 3. Group index and individual extended evaluation

[0123] 3.1 In addition to calculating the traditional index for each student, the system also calculates the writing force balance coefficient E p and the writing rhythm continuity index R c for each student in the aforementioned embodiment 1;

[0124] 3.2 In the central data analysis module, the system statistically processes the above-mentioned indicators of each student, calculates the average writing force balance coefficient and rhythm continuity index of the whole class, and provides the teachers with a macroscopic view of the group writing state;

[0125] 3.3 At the same time, the abnormal data of individual students (for example, the E p and R c of a student deviate significantly from the average level of the class) are marked to prompt the teachers for targeted guidance.

[0126] 4. Feedback and dynamic adjustment

[0127] 4.1 The central terminal displays the real-time data of each student on the teacher terminal through a graphical interface, and some indicators can be publicly displayed on a large screen.

[0128] 4.2 For students with abnormal data, the system pushes personalized prompt information to their devices through wireless transmission, such as suggesting adjusting the pen holding force or adjusting the writing rhythm.

[0129] 4.3 The system automatically updates the feedback threshold based on the statistical results of the group data, making the data feedback more suitable for the current teaching situation.

[0130] 5. Data storage and subsequent teaching improvement

[0131] 5.1 The writing data and calculation results of all students are uploaded to the central database after each course ends.

[0132] 5.2 Teachers can analyze the progress of each student using historical data, optimize teaching plans, and provide targeted guidance to students through data playback functions.

[0133] This embodiment realizes real-time monitoring of multiple users in calligraphy class. By introducing the force balance coefficient E p and rhythm continuity index R c for each student, it helps teachers quickly identify weaknesses in the writing process, thereby achieving personalized teaching and group data feedback, and improving the overall quality of calligraphy teaching.

[0134] The third embodiment of the present application further expands on the basis of the foregoing technology, and jointly evaluates the physiological and psychological state of the writer during the writing process. In addition to collecting writing action, pressure, and posture data, a heart rate sensor is integrated to obtain physiological signals. Through multi-dimensional data fusion, more personalized feedback is provided to help writers achieve optimal writing performance in a relaxed state. The specific implementation steps are as follows:

[0135] 1. Device configuration and multi-modal data acquisition

[0136] 1.1 Install the following sensors on the writer's body simultaneously:

[0137] IMU sensor (to collect hand motion and wrist angle);

[0138] High-precision pressure sensor (to collect pen-holding pressure);

[0139] Heart rate sensor (Heart Rate Monitor, HRM) to collect real-time heart rate data during writing.

[0140] 1.2 When the system starts, synchronize and calibrate all sensors, and set a uniform sampling frequency (e.g., 100 Hz).

[0141] 2. Data preprocessing and multi-channel fusion

[0142] 2.1 Filter and denoise the motion, pressure, and heart rate data respectively;

[0143] 2.2 Fuse the channel data through timestamps to form a multi-dimensional data stream containing writing motion, force, posture, and physiological state;

[0144] 2.3 Remove and correct possible outliers in the data to ensure data quality.

[0145] 3. Parameter calculation and extended evaluation

[0146] 3.1 First, calculate the writing motion accuracy parameter and posture stability parameter according to the methods described in the previous embodiments;

[0147] 3.2 At the same time, use the methods in the first embodiment to calculate the writing force balance coefficient E p and the writing rhythm continuity index R c respectively.

[0148] 3.3 Combined with heart rate data, the system further evaluates the physiological tension during writing.

[0149] For example, the heart rate fluctuation rate HR var (the standard deviation of heart rate within a certain time) can be calculated and analyzed in conjunction with the posture stability parameter to assist in determining whether the writer's motion is unstable due to tension.

[0150] 3.4 According to the parameters, the system can calculate a comprehensive writing performance index C, whose calculation formula can be defined as (this formula is an auxiliary evaluation formula, not necessary, but provides a quantitative basis for personalized feedback):

[0151]

[0152] wherein, Δ represents the writing trajectory deviation, i.e. the average deviation value, Δ m ax represents the preset maximum deviation value (for normalization), σ θ represents the standard deviation of the wrist angle change rate during writing, σ θ,max represents the preset maximum angle change standard deviation, E p represents the writing force balance coefficient, R c represents the writing rhythm continuity index, HR var represents the standard deviation of the heart rate during writing, and α, β, θ, κ, λ are weight coefficients respectively, which are determined according to a large amount of experimental data, and the calculation method is:

[0153]

[0154] θ = k = λ = 0.25

[0155] The above weight coefficients can be optimized and adjusted according to actual conditions.

[0156] 3.5 The higher the comprehensive index C is, the better the writing state is, and vice versa, which indicates that the writer may be in a tense or poor writing state.

[0157] 4. Real-time feedback and personalized guidance

[0158] 4.1 The system displays all the calculation results to the writer through a visual interface, and the interface simultaneously displays the writing trajectory, pressure fluctuation curve, heart rate change curve and comprehensive performance index C;

[0159] 4.2 The system provides immediate adjustment suggestions to the writer through voice prompts, icon prompts or tactile feedback, such as “Please relax your wrist”, “Please pay attention to balance as the pen holding force is uneven” and the like;

[0160] 4.3 The system records all the data during each writing process, provides basis for subsequent adjustment of personalized training plan, and can automatically adjust each threshold according to historical data, so that the feedback is more in line with the individual characteristics of the writer.

[0161] 5. Data storage, analysis and long-term training support

[0162] 5.1 All real-time collected and calculated data are stored in local or cloud database, supporting long-time and multiple writing process data accumulation analysis;

[0163] 5.2 The user can view historical trends, generate training reports and adjust training plans according to data feedback through a dedicated application software;

[0164] 5.3 The system supports remote expert guidance, and the expert can remotely access the writing data through the database and provide targeted training suggestions.

[0165] The embodiment integrates writing action data and physiological and psychological state data, realizes real-time monitoring of writing action and force, rhythm, quantitatively evaluates tension and psychological state of the writer, and further provides more personalized and scientific feedback and guidance for the writer. The introduction of the comprehensive writing performance index C makes the writing effect evaluation more comprehensive and intuitive, and is suitable for professional training and improvement of daily practice.

[0166] The technical scheme provided by the embodiment of the application has at least the following beneficial effects:

[0167] (1) In the application, by integrating a plurality of high-precision sensors, real-time monitoring of key data such as body action, pen-holding pressure and wrist angle of the writer during calligraphy writing is realized, high-frequency acquisition of sensor data and data fusion technology are used to accurately record writing dynamics, and the problem of being unable to quantitatively capture the body state of the writer and lacking real-time feedback in traditional teaching is effectively solved, thereby providing a solid data foundation for subsequent action analysis and skill improvement;

[0168] (2) In the application, the collected original data are filtered, fused, feature-extracted and index-calculated, and then quantitative indexes such as writing action accuracy and writing posture stability are generated. Through this technical means, the system can objectively evaluate the accuracy of handwriting and the stability of writing posture during writing, solve the defects of strong subjectivity of evaluation means and inability to accurately quantify writing quality in traditional calligraphy teaching, and provide scientific and quantitative improvement basis for the writer;

[0169] (3) In the application, data visualization technology is used to convert complex body data into intuitive and easy-to-understand charts, animations and color-coded information, and combine display, tactile and audio feedback modes to deliver to the writer in real time. Through this comprehensive feedback mechanism, the writer can immediately understand his own shortcomings and advantages in the writing process, thereby realizing dynamic adjustment and personalized training, and effectively solving the problems of delayed feedback and difficulty in implementing targeted training in traditional calligraphy teaching, and promoting the development of calligraphy teaching towards digitization and intelligentization.

[0170] Reference is made to the accompanying drawings Figure 5 , which shows a structural schematic diagram of the calligraphy writing body data visualization monitoring system based on body perception provided by the embodiment of the application.

[0171] The application further provides a calligraphy writing body data visualization monitoring system based on body perception, which is applied to the calligraphy writing body data visualization monitoring method based on body perception and comprises:

[0172] at least one group of sensors, a data acquisition module, a data analysis module, a visualization feedback module and an adjustment module;

[0173] a sensor for real-time monitoring of the body action data of the calligraphic writer;

[0174] a data acquisition module for receiving and storing the writing action data collected by the sensor, which can use Arduino;

[0175] a data analysis module for calculating precision parameters and stability parameters according to the writing action data and generating a comprehensive evaluation result;

[0176] a visual feedback module for providing the evaluation result to the writer in the form of graphics, sound or tactile sensation for adjusting the writing posture;

[0177] an adjustment module for dynamically adjusting the monitoring parameters and feedback thresholds according to the feedback of the writer to adapt to the individual needs of different writers.

[0178] The calligraphic writing body data visualization monitoring system based on body perception provided by the present application can perform the calligraphic writing body data visualization monitoring method based on body perception and achieve the same or similar technical effects. To avoid repetition, the present application will not be described again.

[0179] The technical solutions provided by the embodiments of the present application have at least the following beneficial effects:

[0180] (1) In the present application, by integrating multiple high-precision sensors, real-time monitoring of key data such as body action, pen holding pressure and wrist angle of the writer during calligraphic writing is realized. By using high-frequency acquisition and data fusion technology of sensor data, writing dynamics are accurately recorded, effectively solving the problem of inability to quantitatively capture the body state of the writer and lack of real-time feedback in traditional teaching, thereby providing a solid data foundation for subsequent action analysis and skill improvement;

[0181] (2) In the present application, the collected raw data is filtered, fused, feature extracted and index calculated to generate quantitative indexes such as writing action precision and writing posture stability. Through this technical means, the system can objectively evaluate the accuracy of handwriting and the stability of writing posture during writing, solve the defects of strong subjectivity of evaluation means and inability to accurately quantify writing quality in traditional calligraphy teaching, and provide scientific and quantitative improvement basis for the writer;

[0182] (3) In the present application, complex body data is converted into intuitive and understandable charts, animations and color-coded information by using data visualization technology, and is transmitted to the writer in real time in combination with various feedback modes such as display, touch and audio. Through this comprehensive feedback mechanism, the writer can immediately understand the shortcomings and advantages in the writing process, so as to realize dynamic adjustment and personalized training, and practically solve the problems of delayed feedback and difficulty in targeted training in traditional calligraphy teaching, and promote the development of calligraphy teaching in the direction of digitization and intelligentization.

[0183] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which shall be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

[0184] The following points need to be explained:

[0185] (1) The drawings of the embodiments of the present application only involve the structures involved in the embodiments of the present application, and other structures can be referred to the general design.

[0186] (2) For the sake of clarity, the thickness of the layers or regions is exaggerated or reduced in the drawings used to describe the embodiments of the present application, that is, the drawings are not drawn according to the actual proportion. It can be understood that when an element such as a layer, a film, a region or a substrate is referred to as being located on or under another element, the element can be directly on or under another element or there can be an intermediate element.

[0187] (3) In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other to obtain new embodiments.

[0188] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for visualizing calligraphy writing body data based on body perception, characterized in that: include: S1. Real-time monitoring of a calligrapher's body movements using at least one set of sensors, the sensors including an inertial sensor, an electromyographic sensor, an angle sensor, an acceleration sensor, and a pressure sensor; S2. Acquiring motion data of the calligrapher during the writing process, wherein the motion data includes the calligrapher's hand motion trajectory, writing speed, pen grip pressure, and wrist angle; S3. Calculating writing motion accuracy and writing posture stability based on the motion data, wherein the writing motion accuracy is used to evaluate the accuracy and consistency of the calligrapher's writing trajectory during the writing process, and the writing posture stability is used to evaluate the stability of the calligrapher's hand and wrist posture during the writing process; S4. Analyzing the writing action accuracy and writing posture stability to obtain a comprehensive evaluation result of the writer's writing state; S5. Visualizing the evaluation result and providing it to the writer via a feedback device, wherein the feedback device includes a display screen, a tactile feedback device, and an audio feedback device, so that the writer can adjust and optimize his writing posture; S6. Dynamically adjust monitoring parameters according to the adjustment information fed back by the writer to adapt to individual differences of different writers.

2. The method for visualizing and monitoring calligraphy data based on body perception according to claim 1, characterized in that: The writing action accuracy further includes: S201, based on the hand motion trajectory of the writer, using a Bezier curve fitting algorithm to calculate the deviation between the writing path and the ideal writing path; S202, calculating the average absolute value of the deviation between the hand movement trajectory and the ideal path, and using this value to measure the writing accuracy; S203. When the deviation value is lower than the preset threshold, it is determined that the writer has high writing accuracy; conversely, when the deviation value is higher than the threshold, feedback is given to the writer for adjustment.

3. The method for visualizing calligraphy writing data based on body perception according to claim 1 is characterized in that: The writing posture stability further includes: S301, calculating the rate of change of the hand and wrist angles during the writing process based on the hand and wrist motion data; S302: Use a low-pass filter to smooth the angle change rate data to remove high-frequency noise. The low-pass filter adopts a first-order Butterworth low-pass filter. The specific formula is: Among them, s is a complex frequency domain variable, which represents the input signal of the filter, ω c is the cutoff frequency of the filter, which determines the frequency response of the filter; S303, calculating the standard deviation of the angle change rate after smoothing, the lower the standard deviation value, the more stable the writing posture; S304: When the standard deviation value is lower than the preset stability threshold, it is determined that the writing posture is relatively stable; otherwise, feedback is given to the writer for adjustment.

4. The method for visualizing and monitoring calligraphy data based on body perception according to claim 2, characterized in that: The deviation value further includes: The calculation method of the deviation value between the writing path and the ideal path is: Wherein, Δ represents the deviation between the writing path and the ideal path, P real (i) is the actual writing position of the i-th point, P ideal (i) is the ideal writing position of the i-th point, and n is the total number of trajectory points.

5. The method for visualizing and monitoring calligraphy data based on body perception according to claim 3 is characterized in that: The method for calculating the angle change rate further includes: Wherein, Rate represents the angle change rate, Δθ represents the angle change in degrees, Δt represents the time interval in seconds, and Δθ represents the angle change of the hand and wrist within the time interval Δt.

6. The method for visualizing and monitoring calligraphy data based on body perception according to claim 1, characterized in that: The feedback on writing accuracy further includes: S601, the display screen displays the real-time deviation of the writing trajectory; S602: The tactile feedback device prompts the writer to adjust his writing posture through vibration; S603: The audio prompting device reminds the writer to adjust the writing action through sound.

7. The method for visualizing calligraphy data based on body perception according to claim 1 is characterized in that: include: The motion data includes the writer's heart rate data, which is used to further analyze the writer's physiological state.

8. The method for visualizing and monitoring calligraphy data based on body perception according to claim 1, characterized in that: include: The feedback device dynamically adjusts the writing accuracy and stability threshold according to the writer's feedback.

9. The method for visualizing and monitoring calligraphy data based on body perception according to claim 1, characterized in that: include: The evaluation results also include an evaluation of the writer's mental state and providing suggestions based on the evaluation results.

10. A calligraphy writing body data visualization monitoring system based on body perception, characterized in that: include: At least one set of sensors, data acquisition module, data analysis module, visual feedback module and adjustment module; The sensor is used to monitor the body movement data of the calligrapher in real time; The data acquisition module is used to receive and store the writing action data collected by the sensor; The data analysis module is used to calculate the accuracy parameter and the stability parameter based on the writing action data and generate a comprehensive evaluation result; The visual feedback module is used to provide the evaluation results to the writer in the form of graphics, sound or touch, so that the writer can adjust his / her writing posture; The adjustment module is used to dynamically adjust the monitoring parameters and feedback thresholds according to the writer's feedback to adapt to the individual needs of different writers.

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