Musical instrument playing bow pressure and pitch monitoring processing method and device

Abstract

The invention discloses a musical instrument playing bow pressure and pitch monitoring processing method and device, and relates to the technical field of musical instrument playing bow pressure and pitch monitoring, and the method comprises the steps: determining a musical instrument mode in response to the obtained sensor data of a musical instrument; in response to the musical instrument mode being a pause mode, controlling the musical instrument to enter a dormant state, acquiring and updating sensor data in real time, and updating the musical instrument mode in combination with a preset wake-up condition; in response to the updated musical instrument mode being a full-function mode, extracting pressure signal data and vibration signal data from the updated sensor data; determining a preset weight of the musical instrument assembly corresponding to the pressure signal data, and determining a fusion pressure value based on the preset weight and the pressure signal data; and determining a display mode, generating analysis result data matched with the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and displaying the analysis result data on a musical instrument screen. The bow pressure and pitch of the musical instrument in the playing process are accurately monitored, and visual feedback display is carried out.

Description

Technical Field

[0001] The present application relates to the technical field of bow pressure and pitch monitoring for musical instrument performance, and in particular to a method and device for monitoring and processing bow pressure and pitch for musical instrument performance. Background Art

[0002] At present, in the performance of traditional string instruments, the control of bow pressure and pitch depends on the player's experience, and the monitoring of bow pressure and pitch is not accurate and the feedback is not intuitive. Summary of the Invention

[0003] In view of this, the embodiments of the present application provide a method and device for monitoring and processing bow pressure and pitch in musical instrument performance, which can solve the problems in existing traditional string instrument performance, where the control of bow pressure and pitch depends on the player's experience, the monitoring of bow pressure and pitch is inaccurate, and the feedback is not intuitive.

[0004] To achieve the above objectives, according to one aspect of an embodiment of the present application, a method for monitoring bow pressure and pitch of a musical instrument is provided, comprising:

[0005] In response to acquiring sensor data of the musical instrument, determining a musical instrument mode based on the sensor data;

[0006] In response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state, acquiring and updating sensor data in real time, and updating the musical instrument mode based on the updated sensor data and a preset wake-up condition;

[0007] In response to the updated musical instrument mode being the full-function mode, extracting pressure signal data and vibration signal data from the updated sensor data;

[0008] determining preset weights of instrument components corresponding to the pressure signal data, and determining a fused pressure value based on the preset weights and the pressure signal data;

[0009] Determine a display mode, generate analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and display the analysis result data on a screen embedded in the musical instrument.

[0010] Optionally, determining a musical instrument mode based on sensor data includes:

[0011] Extracting bow posture data from sensor data;

[0012] The corresponding instrument mode is predicted based on the bowing posture data through the behavioral model.

[0013] Optionally, in response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state includes:

[0014] In response to the instrument mode being the short-stop mode, the corresponding sleep state is to turn off the wireless network and Bluetooth, disable sensor fusion calculation, and control the instrument to enter the corresponding sleep state.

[0015] Optionally, in response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state includes:

[0016] In response to the instrument mode being the long stop mode, the corresponding sleep state is that the random access memory is maintained by the supercapacitor, the inertial measurement unit is controlled to perform bow posture monitoring at a preset frequency, the wake-up delay is set to a preset duration, and the instrument is controlled to enter the corresponding sleep state.

[0017] Optionally, updating the instrument mode based on the updated sensor data and the preset wake-up condition includes:

[0018] The preset wake-up conditions include that the bow acceleration is greater than the preset acceleration threshold and the duration reaches the preset duration threshold, there is vibration signal data and the vibration duration reaches the preset duration threshold. If the updated sensor data matches the preset wake-up conditions, the instrument mode is updated to the full-function mode.

[0019] Optionally, the musical instrument components corresponding to the pressure signal data include a bridge and a sound filter; the pressure signal data includes bridge pressure signal data and sound filter cotton pressure signal data; and

[0020] Determine the preset weight of the instrument component corresponding to the pressure signal data, including:

[0021] Determining a first preset weight corresponding to the bridge and a second preset weight corresponding to the filter cotton; and

[0022] Determining a fused pressure value based on preset weights and pressure signal data includes:

[0023] Based on the bridge pressure signal data, the string pressure value is obtained;

[0024] Based on the filter cotton pressure signal data, the resonance pressure value is obtained;

[0025] A bow pressure value is determined based on the first preset weight, the chord pressure value, the second preset weight, and the resonance pressure value, and the bow pressure value is determined as the fusion pressure value.

[0026] Optionally, before generating parsing result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, the method further includes:

[0027] Determine the string vibration frequency corresponding to the vibration signal data through zero-crossing detection;

[0028] Based on the string vibration frequency, the pitch value corresponding to the vibration signal data is determined.

[0029] In addition, the present application also provides a device for monitoring and processing bow pressure and pitch of a musical instrument, comprising:

[0030] a musical instrument mode determination unit configured to, in response to acquiring sensor data of the musical instrument, determine a musical instrument mode based on the sensor data;

[0031] a musical instrument mode updating unit configured to, in response to the musical instrument mode being the pause mode, control the musical instrument to enter a dormant state, acquire and update sensor data in real time, and update the musical instrument mode based on the updated sensor data and a preset wake-up condition;

[0032] an extraction unit configured to extract pressure signal data and vibration signal data from the updated sensor data in response to the updated musical instrument mode being the full-function mode;

[0033] a data fusion unit configured to determine preset weights of musical instrument components corresponding to the pressure signal data, and determine a fused pressure value based on the preset weights and the pressure signal data;

[0034] The display unit is configured to determine a display mode, generate analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and display the analysis result data on a screen embedded in the musical instrument.

[0035] Optionally, the musical instrument mode determination unit is further configured to:

[0036] Extracting bow posture data from sensor data;

[0037] The corresponding instrument mode is predicted based on the bowing posture data through the behavioral model.

[0038] Optionally, the musical instrument mode updating unit is further configured to:

[0039] In response to the instrument mode being the short-stop mode, the corresponding sleep state is to turn off the wireless network and Bluetooth, disable sensor fusion calculation, and control the instrument to enter the corresponding sleep state.

[0040] Optionally, the musical instrument mode updating unit is further configured to:

[0041] In response to the instrument mode being the long stop mode, the corresponding sleep state is that the random access memory is maintained by the supercapacitor, the inertial measurement unit is controlled to perform bow posture monitoring at a preset frequency, the wake-up delay is set to a preset duration, and the instrument is controlled to enter the corresponding sleep state.

[0042] Optionally, the musical instrument mode updating unit is further configured to:

[0043] The preset wake-up conditions include that the bow acceleration is greater than the preset acceleration threshold and the duration reaches the preset duration threshold, there is vibration signal data and the vibration duration reaches the preset duration threshold. If the updated sensor data matches the preset wake-up conditions, the instrument mode is updated to the full-function mode.

[0044] Optionally, the musical instrument components corresponding to the pressure signal data include a bridge and a sound filter; the pressure signal data includes bridge pressure signal data and sound filter cotton pressure signal data; and

[0045] The data fusion unit is further configured to:

[0046] Determining a first preset weight corresponding to the bridge and a second preset weight corresponding to the filter cotton; and

[0047] The data fusion unit is further configured to:

[0048] Based on the bridge pressure signal data, the string pressure value is obtained;

[0049] Based on the filter cotton pressure signal data, the resonance pressure value is obtained;

[0050] A bow pressure value is determined based on the first preset weight, the chord pressure value, the second preset weight, and the resonance pressure value, and the bow pressure value is determined as the fusion pressure value.

[0051] Optionally, the apparatus for monitoring and processing bow pressure and pitch of a musical instrument further includes a pitch value determining unit configured to:

[0052] Determine the string vibration frequency corresponding to the vibration signal data through zero-crossing detection;

[0053] Based on the string vibration frequency, the pitch value corresponding to the vibration signal data is determined.

[0054] In addition, the present application also provides an electronic device for monitoring and processing the bow pressure and pitch of a musical instrument, including: one or more processors; a storage device for storing one or more programs, when one or more programs are executed by one or more processors, the one or more processors implement the above-mentioned method for monitoring and processing the bow pressure and pitch of a musical instrument.

[0055] In addition, the present application also provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned method for monitoring and processing bow pressure and pitch of musical instrument performance is implemented.

[0056] To achieve the above objective, according to another aspect of the embodiments of the present application, a computer program product is provided.

[0057] A computer program product according to an embodiment of the present application includes a computer program, which, when executed by a processor, implements the bow pressure and pitch monitoring processing method for musical instrument performance provided by an embodiment of the present application.

[0058] One embodiment of the above invention has the following advantages or beneficial effects: the present application determines an instrument mode based on the sensor data obtained from the instrument; in response to the instrument mode being paused, controls the instrument to enter a dormant state, acquires and updates the sensor data in real time, and updates the instrument mode based on the updated sensor data and preset wake-up conditions; in response to the updated instrument mode being fully functional, extracts pressure signal data and vibration signal data from the updated sensor data; determines preset weights of instrument components corresponding to the pressure signal data, and determines a fused pressure value based on the preset weights and the pressure signal data; determines a display mode, generates parsed result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and displays the parsed result data on a screen embedded in the instrument. This allows accurate monitoring of bow pressure and pitch during instrument performance and provides intuitive feedback display.

[0059] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings are provided to facilitate a better understanding of the present application and do not constitute an undue limitation on the present application.

[0061] Figure 1 1 is a schematic diagram of the main process of a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0062] Figure 2 1 is a schematic diagram of the main process of a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0063] Figure 3 1 is a schematic diagram of the structure of an instrument involved in the implementation of a method for monitoring and processing bow pressure and pitch of an instrument according to an embodiment of the present application;

[0064] Figure 4 is a connection diagram of components involved in implementing a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0065] Figure 5 1 is a hierarchical architecture diagram involved in the implementation of a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0066] Figure 6 This is a schematic diagram of the main process of a method for monitoring bow pressure and pitch of a musical instrument according to one embodiment of the present application;

[0067] Figure 7 This is a diagram of a real-time dual-stream data processing architecture for a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0068] Figure 8 This is a diagram of the power management and deep sleep system architecture involved in the implementation of a method for monitoring and processing bow pressure and pitch of a musical instrument according to one embodiment of the present application;

[0069] Figure 9 This is a schematic diagram of the main process of a deep sleep mode of bow posture prediction based on battery management involved in the implementation of a method for monitoring and processing bow pressure and pitch of a musical instrument according to one embodiment of the present application;

[0070] Figure 10 1 is a schematic diagram of screen display of a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application;

[0071] Figure 11 It is a schematic diagram of the main units of the instrument playing bow pressure and pitch monitoring processing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0072] The following describes exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description. It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solutions of this application comply with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of this application, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered exemplary and are intended solely to illustrate the feasibility of implementing the technical solutions of this application. It does not mean that the applicant has or will necessarily use such solutions. In the technical solutions of this application, the collection, collection, updating, analysis, processing, use, transmission, storage, and other aspects of user personal information involved comply with the provisions of relevant laws and regulations, are used for legal and reasonable purposes, do not violate public order and good morals, are not shared, disclosed, or sold outside of these legal uses, and are subject to supervision and management by regulatory authorities. Necessary measures should be taken to prevent unauthorized access to user personal information, safeguard the security of user personal information, network security, and national security, and ensure that persons with access to personal information comply with relevant laws and regulations. Once such personal information is no longer needed, risks should be minimized by restricting or even prohibiting its collection and / or deleting it.

[0073] When used, including in certain related applications, protect user privacy by de-identifying data, such as by removing specific identifiers when used, controlling the amount or specificity of stored data, controlling how data is stored, and / or other de-identification methods.

[0074] Figure 1 FIG. 1 is a schematic diagram of the main process of a method for monitoring bow pressure and pitch of a musical instrument according to an embodiment of the present application. Figure 1 As shown, the method for monitoring and processing bow pressure and pitch of musical instrument playing mainly includes the following steps S101 to S105.

[0075] Step S101 : In response to acquiring sensor data of a musical instrument, determining a musical instrument mode based on the sensor data.

[0076] The instrument's sensor data can include string vibration data measured by piezoelectric ceramics and / or real-time posture data (i.e., real-time bowing posture data) measured by an IMU. Instrument modes can include full-function mode, short-stop mode, and long-stop mode, with the latter two belonging to pause mode. The acquired instrument sensor data can be input into an LSTM behavioral model to predict the instrument mode corresponding to the sensor data and determine the current instrument state (playing, short-stop, or long-stop).

[0077] In this embodiment, the execution subject of the instrument playing bow pressure and pitch monitoring processing method (for example, it can be a server, specifically can be as follows Figure 5 The microcontroller unit (ESP32-S3 MCU) of the main control layer shown can obtain the sensor data of the musical instrument through a wired connection or a wireless connection, and input the sensor data of the musical instrument into the LSTM behavior model of the algorithm processing unit, so as to parallelly process the pressure / vibration signals in the sensor data of the musical instrument through the LSTM behavior model, thereby accurately determining the musical instrument mode corresponding to the sensor data.

[0078] In some embodiments, determining the instrument mode based on sensor data includes: extracting bowing posture data from the sensor data; and predicting the corresponding instrument mode based on the bowing posture data using a behavioral model.

[0079] In embodiments of the present application, a behavioral model, such as an LSTM behavioral model, classifies the instrument's sensor data to obtain real-time posture data (i.e., real-time bowing posture data) measured by the IMU and string vibration data measured by the piezoelectric ceramic. The real-time posture data (i.e., real-time bowing posture data) measured by the IMU is input into the LSTM behavioral model for bowing behavior detection, which outputs a value representing the instrument's mode: 0 (playing), 1 (short pause), or 2 (long pause).

[0080] Step S102 , in response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state, acquiring and updating sensor data in real time, and updating the musical instrument mode based on the updated sensor data and a preset wake-up condition.

[0081] The pause mode includes a short pause mode and a long pause mode. For example, the short pause mode can be represented by 1 and the long pause mode can be represented by 2.

[0082] Specifically, in response to the instrument mode being in the pause mode, controlling the instrument to enter a sleep state includes: in response to the instrument mode being in the short pause mode, the corresponding sleep state is turning off the wireless network (Wi-Fi) and Bluetooth (BLE), disabling sensor fusion calculation, and controlling the instrument to enter the corresponding sleep state, thereby effectively reducing power consumption.

[0083] Specifically, in response to the instrument mode being the pause mode, controlling the instrument to enter a sleep state includes: in response to the instrument mode being the long-stop mode, the corresponding sleep state is to have the random access memory (RAM) maintained by the supercapacitor, controlling the inertial measurement unit (IMU) to perform bow posture monitoring at a preset frequency (e.g., 10 Hz), and setting the wake-up delay to a preset duration (e.g., 20 ms), thereby controlling the instrument to enter the corresponding sleep state. This effectively reduces power consumption.

[0084] Regardless of whether the instrument is in short-stop mode or long-stop mode, the instrument's bow posture data can be obtained through the IMU, and the string vibration data can also be measured through the piezoelectric ceramic piece. After the instrument is controlled to enter the dormant state, the sensor data that can be obtained (for example, bow posture data and string vibration data) is acquired and updated in real time, and the instrument mode is updated based on the updated sensor data (for example, updated bow posture data and string vibration data) and preset wake-up conditions. The bow posture data can include bow acceleration.

[0085] Specifically, the instrument mode is updated based on the updated sensor data and the preset wake-up conditions, including: the preset wake-up conditions include the bow acceleration being greater than a preset acceleration threshold (for example, >0.5g) and the maintenance duration (i.e., the duration for maintaining the acceleration >0.5g) reaching a preset duration threshold (for example, 20ms), the presence of vibration signal data (i.e., the signal data generated by the string vibration) and the vibration maintenance duration (i.e., the duration for which the string vibration is maintained) reaching a preset duration threshold (for example, 20ms). If the updated sensor data matches the preset wake-up conditions, the instrument mode is updated to the full-function mode.

[0086] For example, if the bow acceleration is greater than a preset acceleration threshold (e.g., >0.5g) and the duration (i.e., the duration of the acceleration >0.5g) reaches a preset duration threshold (e.g., 20ms) and / or there is vibration signal data (i.e., signal data generated by string vibration) and the vibration duration (i.e., the duration of the string vibration) reaches a preset duration threshold (e.g., 20ms), the instrument is awakened and the instrument mode is updated to the full-function mode. This allows for timely response to the user's use of the instrument and improves the user experience.

[0087] Step S103 : In response to the updated musical instrument mode being the full-function mode, extracting pressure signal data and vibration signal data from the updated sensor data.

[0088] The instrument mode is a full-function mode, that is, the instrument is in performance mode, and pressure signal data (for example, updated bridge pressure signal data, filter cotton pressure signal data) and vibration signal data (for example, updated string vibration signal data) are extracted from the updated sensor data.

[0089] Step S104: determining the preset weights of the instrument components corresponding to the pressure signal data, and determining the fusion pressure value based on the preset weights and the pressure signal data.

[0090] Determine the preset weight of the musical instrument component corresponding to the pressure signal data. For example, the musical instrument component corresponding to the bridge pressure signal data is the bridge, and the preset weight of the bridge can be, for example, 0.6; the musical instrument component corresponding to the filter cotton pressure signal data is the filter cotton, and the preset weight of the filter cotton can be, for example, 0.4. The embodiment of the present application does not specifically limit the preset weights of the bridge and the filter cotton, and can be determined according to the user's settings.

[0091] The fusion pressure value is determined based on the preset weight and the pressure signal data. For example, according to the correspondence between the signal and the pressure value, each pressure value corresponding to the pressure signal data is determined. For example, the bridge pressure value corresponding to the bridge pressure signal data, i.e., the string pressure value, is determined. The filter cotton pressure value corresponding to the filter cotton pressure signal data, i.e., the resonance pressure value, is determined. A first product of the preset weight of the bridge and the string pressure value is calculated, and a second product of the preset weight of the filter cotton and the resonance pressure value is calculated. The fusion pressure value is obtained based on the first product and the second product. This improves the accuracy of monitoring the bow pressure of the instrument.

[0092] Step S105 , determining a display mode, generating analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and displaying the analysis result data on a screen embedded in the musical instrument.

[0093] The display mode is determined based on the user's operation of the button on the screen on the neck of the musical instrument. For example, when the user short presses the button on the screen, the display mode is switched (which may include standard mode, training mode and tuning mode), and the display mode selected by the user by short pressing the button on the screen is determined, for example, the standard mode.

[0094] The fusion pressure value reflects the bow pressure, and the pitch value corresponding to the vibration signal data reflects the pitch. Based on the fusion pressure value and the pitch value, the analysis result data corresponding to the display mode selected by the user (for example, the standard mode) is generated, for example, Figure 10 The standard mode shown in the figure shows the corresponding bow pressure, pitch hyperbola, and bow pressure, pitch values. Figure 10 The standard mode shown corresponds to the bow pressure, pitch hyperbola, and bow pressure and pitch values. This allows for accurate monitoring of bow pressure and pitch during instrument performance and provides intuitive feedback.

[0095] This embodiment, in response to acquired instrument sensor data, determines an instrument mode based on the sensor data; in response to the instrument mode being paused, controls the instrument to enter a dormant state, acquires and updates sensor data in real time, and updates the instrument mode based on the updated sensor data and preset wake-up conditions; in response to the updated instrument mode being fully functional, extracts pressure signal data and vibration signal data from the updated sensor data; determines preset weights for instrument components corresponding to the pressure signal data, and determines a fused pressure value based on the preset weights and the pressure signal data; determines a display mode, generates parsed result data matching the display mode based on the fused pressure value and pitch value corresponding to the vibration signal data, and displays the parsed result data on a screen embedded in the instrument. This allows for accurate monitoring of bow pressure and pitch during instrument performance, and provides intuitive feedback display.

[0096] Figure 2 FIG. 1 is a schematic diagram of the main flow of a method for monitoring and processing bow pressure and pitch of a musical instrument according to an embodiment of the present application. Figure 2 As shown, the method for monitoring and processing bow pressure and pitch of musical instrument playing mainly includes the following steps S201 to S208.

[0097] Step S201 : In response to obtaining sensor data of a musical instrument, determining a musical instrument mode based on the sensor data.

[0098] Step S202 , in response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state, acquiring and updating sensor data in real time, and updating the musical instrument mode based on the updated sensor data and a preset wake-up condition.

[0099] Step S203 : In response to the updated musical instrument mode being the full-function mode, extracting pressure signal data and vibration signal data from the updated sensor data.

[0100] The principles of steps S201 to S203 are similar to those of steps S101 to S103 and will not be described in detail here.

[0101] The musical instrument components corresponding to the pressure signal data include the bridge and the sound filter cotton; the pressure signal data includes the bridge pressure signal data and the sound filter cotton pressure signal data.

[0102] Step S204: determining a first preset weight corresponding to the bridge and a second preset weight corresponding to the filter cotton.

[0103] The first preset weight (for example, 0.6) corresponding to the bridge can be determined according to user settings, and the second preset weight (for example, 0.4) corresponding to the sound filter cotton can be determined according to user settings.

[0104] Step S205: obtaining the string pressure value based on the bridge pressure signal data.

[0105] The working principle of the pressure sensor is to convert pressure changes into electrical signal output. For the pressure range of 0-1MPa, the output signal is 4-20mA. Through the above calculation formula, it can be concluded that the pressure value corresponding to each milliampere is 0.0625MPa. The specific calculation method is to subtract 4 from the output current signal value and multiply it by 0.0625 to get the actual pressure value. For example, assuming that the current signal value corresponding to the bridge pressure signal data is 10mA, the actual pressure value (string pressure value in this application, that is, bridge pressure value) is calculated as follows: (10-4)*0.0625=0.375MPa.

[0106] Step S206: obtaining a resonance pressure value based on the sound filter cotton pressure signal data.

[0107] For example, assuming that the current signal value corresponding to the filter cotton pressure signal data is 10mA, the actual pressure value (the resonance pressure value in this application, that is, the filter cotton pressure value) is calculated as follows: (10-4)*0.0625=0.375MPa.

[0108] Step S207 : determining a bow pressure value based on the first preset weight, the string pressure value, the second preset weight, and the resonance pressure value, and determining the bow pressure value as the fusion pressure value.

[0109] Based on the first preset weight (eg, 0.6), the chord pressure value (eg, P1), the second preset weight (eg, 0.4), and the resonance pressure value (eg, P2), a bow pressure value is determined as the fusion pressure value.

[0110] For example, the dual sensor data can be fused using the following formula to obtain the fused pressure value P final :Pfinal = 0.6*P1+0.4*P2+γ·dP / dt. P1 corresponds to the bridge pressure (i.e., the string pressure), P2 corresponds to the filter pressure (i.e., the resonance pressure), and γ is a coefficient that can be set based on experience or by the user, with no specific limitation here. This can improve the accuracy of monitoring the bow pressure of the instrument.

[0111] Step S208 , determining a display mode, generating analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and displaying the analysis result data on a screen embedded in the musical instrument.

[0112] Specifically, before generating analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, the method also includes: determining the string vibration frequency corresponding to the vibration signal data through zero-crossing detection; and determining the pitch value corresponding to the vibration signal data based on the string vibration frequency.

[0113] Zero crossing detection is a method of estimating frequency by monitoring the zero crossing point of the signal. Its principle is based on the zero point change of the periodic signal from the positive half cycle to the negative half cycle or vice versa. Zero crossing detection is achieved through the following steps: Signal sampling: The vibration signal data is converted into a digital signal for sampling. Zero crossing point detection: The zero point is determined by comparing the positive and negative sign changes of adjacent sampling points (for example, positive-negative or negative-positive). Frequency calculation: The frequency is estimated based on the number of zero points and the sampling rate. The formula is: String vibration frequency = number of zero crossing detection points / number of sampling points × sampling rate. According to the preset relationship between pitch and vibration frequency, the pitch value corresponding to the calculated string vibration frequency is determined, that is, the pitch value corresponding to the vibration signal data, thereby improving the efficiency and accuracy of determining the pitch value.

[0114] The display mode is determined according to the user's selection, and analysis result data matching the display mode (for example, training mode) is generated based on the pitch value corresponding to the fused pressure value and vibration signal data, and the analysis result data (for example, bow pressure threshold warning) is displayed on the screen embedded in the instrument.

[0115] The display mode is determined according to the user's selection, and analysis result data matching the display mode (e.g., tuning mode) is generated based on the pitch value corresponding to the fused pressure value and vibration signal data, and the analysis result data (e.g., pitch deviation indication) is displayed on the screen embedded in the musical instrument.

[0116] Figure 3 This is a schematic diagram of the structure of an instrument involved in the implementation of the bow pressure and pitch monitoring processing method for musical instruments according to an embodiment of the present application. The instrument can be an erhu, or a string instrument such as a jinghu, a matouqin, a banhu, or a gaohu. The erhu is used as an example for explanation. Figure 3 As shown, a screen (e.g., a curved screen), a thin film pressure sensor 1, a thin film pressure sensor 2, a piezoelectric ceramic sheet, a main board and a battery are provided on the musical instrument (e.g., an erhu). Specifically, the curved screen is embedded in the neck of the instrument, connected to the main board and the battery through internal wiring, and the neck of the instrument is slotted or made into a detachable mode. The neck of the instrument can be embedded (detachable) in a curved display, using a 240° viewing angle curved bonding technology, and the display logic can support standard modes: hyperbola + numerical value (such as Figure 10 As shown, it displays the bow pressure + pitch hyperbola and the bow pressure value (the bow pressure value is displayed in the form of a diagram, such as Figure 10 The display logic supports bow pressure threshold warning in training mode and pitch deviation indication in tuning mode. Thin-film pressure sensor 1, located between the bridge and the guitar head, detects bridge pressure. Thin-film pressure sensor 2, located between the filter pad and the guitar head, detects filter pressure. The piezoelectric ceramic disc is attached to the bridge sidewall, with a 0.5mm distance between strings. The mainboard and battery are located at the bottom of the guitar neck.

[0117] Figure 4 FIG. 1 is a connection diagram of components involved in the implementation of a method for monitoring and processing bow pressure and pitch of a musical instrument according to an embodiment of the present application. Figure 4 As shown, the components involved in the implementation of the instrument playing bow pressure and pitch monitoring processing method include a main control board (ie Figure 3 The main control board includes a signal acquisition unit (which is connected to the thin film pressure sensor 1, the thin film pressure sensor 2 and the piezoelectric ceramic), a signal processing unit, a main MCU (i.e., the main microcontroller unit), a signal output unit (the signal output unit outputs the signal data to the display screen on the piano bar for display via a data cable) and a power management unit. The power management unit is connected to the lithium battery, and the lithium battery is connected to the power management unit. Figure 4 The power management unit is connected to the display screen on the piano bar through a power line to supply power to the display screen on the piano bar.

[0118] Figure 5 This is a hierarchical structure diagram involved in the implementation of a method for monitoring and processing bow pressure and pitch of a musical instrument according to an embodiment of the present application. Figure 5As shown, the layers involved in implementing the bow pressure and pitch monitoring processing method for musical instruments in the embodiment of the present application include an energy layer, a sensing layer, a signal conditioning layer, a main control layer, and an interaction layer. The energy layer includes a lithium battery, a charging management system, and a USB-C interface. The sensing layer includes piezoelectric ceramics, thin film pressure sensor 1, and thin film pressure sensor 2. The signal conditioning layer includes a charge amplifier, a bandpass filter, an instrumentation amplifier, and a low-pass filter. The main control layer includes an ESP32-S3 MCU, an algorithm processing unit, and a display driver. The interaction layer includes physical buttons and an AMOLED screen.

[0119] At the energy level (lithium batteries, PD charging, and interfaces with charge management functions), the battery's charge and discharge are managed. For example, charging is managed through the USB-C charging interface. This can be applied to magnetic fast-charging energy systems, including a hidden magnetic interface, PD fast-charging protocol support, and a vibration detection wake-up mechanism. The lithium battery can power the charge amplifier (±5V), AMOLED screen (3.3V backlight), and ESP32-S3 MCU (3.3V power supply).

[0120] The piezoelectric ceramic in the sensing layer transmits the vibration charge signal to a charge amplifier, which amplifies the signal and transmits it to a bandpass filter. The bandpass filter filters the amplified signal and transmits it to the ESP32-S3 MCU in the main control layer. Thin-film pressure sensors 1 and 2 in the sensing layer transmit analog pressure signals to an instrumentation amplifier, which amplifies the signal and transmits it to a low-pass filter. The low-pass filter filters the amplified signal and transmits it to the ESP32-S3 MCU in the main control layer. Thin-film pressure sensors 1 and 2 in the sensing layer implement a dual-pressure sensor fusion system: dual-point pressure acquisition from the bridge and filter, using a weighted fusion algorithm to improve accuracy and enhance interference resistance (by 300%). Direct pitch extraction from piezoelectric vibrations is achieved through the piezoelectric ceramics: Direct pitch extraction from piezoelectric vibrations is achieved through a zero-crossing frequency detection algorithm, reducing power consumption by 85% and increasing response speed by 6 times.

[0121] GPIO interrupts are a mechanism that triggers hardware interrupts via general-purpose input / output pins, allowing real-time responses to external events (such as physical button presses and sensor signal changes). At the interaction layer, a physical button press triggers a GPIO interrupt, sending a level signal representing the GPIO interrupt to the ESP32-S3 MCU in the main control layer. This interaction layer also includes an AMOLED screen. The 1.3-inch curved AMOLED screen can display the guitar neck's embedded curved surface. Using "eyes on the guitar" display logic, it enables real-time rendering of bow pressure and pitch hyperbolic curves.

[0122] The main control layer uses ESP32-S3 MCU or MCU with DSP core. For example, the ESP32-S3 MCU of the main control layer transmits the received signal transmitted by the bandpass filter, the signal transmitted by the low-pass filter and the level signal representing the GPIO interrupt transmitted by the interaction layer as raw data to the algorithm processing unit, and performs display driving according to the processing results of the algorithm processing unit, and generates Light and Versatile Graphics Library graphics instructions (LVGL graphics instructions, LVGL provides a wealth of UI controls, such as buttons, labels, text boxes, progress bars, etc., and supports multiple display devices such as LCD, AMOLED, etc.). The interaction layer drives the AMOLED screen for corresponding display based on the LVGL graphics instructions. The algorithm processing unit of the main control layer can realize real-time dual-stream data processing. For example, it adopts a ring buffer dual-channel design and a dynamic compensation coefficient algorithm to perform parallel processing of pressure / vibration signals. For example, Figure 7 As shown, real-time dual-stream data processing: the pressure signal (i.e., the bridge pressure signal data and the filter cotton pressure signal data) enters the circular buffer A, and the vibration signal (i.e., the string vibration signal data) enters the circular buffer B. The fusion algorithm thread is executed on the pressure signal in the circular buffer A (i.e., the bridge pressure signal data and the filter cotton pressure signal data), and the frequency extraction thread is executed on the vibration signal in the circular buffer B (i.e., the string vibration signal data). Then, the rendering thread is displayed based on the execution results of the fusion algorithm thread and the execution results of the frequency extraction thread.

[0123] Figure 6 This is a schematic diagram of the main flow of a method for monitoring and processing bow pressure and pitch during musical instrument performance according to one embodiment of the present application. This embodiment of the present application can determine the current instrument mode using string vibration data measured by a piezoelectric ceramic and / or real-time posture data (i.e., real-time bow posture data) measured by an IMU.

[0124] For example, the instrument mode may include Figure 9The full-function mode shown (the mode entered from the initial state, i.e., the full-function mode. In the full-function mode, the instrument continues to play, all modules are activated, and the sensor has a 100% sampling rate when collecting data), short-stop mode (the short-stop mode can be entered from the full-function mode. Specifically, the LSTM can predict that the instrument is currently in a short-stop state (predictShortBreak) based on the real-time posture data (i.e., real-time bow posture data) measured by the IMU, and then control the instrument to enter the short-stop mode. In the short-stop mode, core collection is performed, i.e., IMU+basic sensor (sampling rate 30%), and energy-saving calculations are performed (only necessary calculations). In the short-stop mode, when the bow acceleration is greater than 0.5g and lasts for 20s, the instrument is awakened and enters the full-function mode), and long-stop mode (the long-stop mode can be entered from the full-function mode Specifically, an LSTM predicts the instrument's current long break state (predictLongBreak) based on real-time posture data measured by the IMU (i.e., real-time bowing posture data). This predicts the instrument's current long break state (predictLongBreak), and controls the instrument to enter long break mode. In long break mode, the instrument enters deep sleep, with only the IMU sampling at 10Hz and RAM data maintained by the supercapacitor. Furthermore, a manual sleep command can be executed in full-function mode to put the instrument into long break mode. Furthermore, in short break mode, if a 30-second timeout fails to wake the instrument back to full-function mode or a long break prediction (i.e., an LSTM prediction of a long break) the instrument enters long break mode. In long break mode, a bowing acceleration greater than 0.5g for 20 seconds awakens the instrument to full-function mode. Both short break and long break modes are considered pause modes. The LSTM behavior recognition model enables real-time bowing posture analysis with prediction accuracy exceeding 95%. In short break mode, Wi-Fi / BLE scanning is disabled, disabling sensor fusion computing and reducing power consumption by 40%. In long-stop mode, the supercapacitor maintains RAM, the IMU monitors at 10Hz, the wake-up delay is only 20ms, and power consumption is reduced by 85%.

[0125] In the embodiment of this application, Figure 8 As shown, the sensor system installed on the bow body may include a 9-axis IMU, an electromagnetic sensor, a fiber optic sensor, and a microphone. Real-time posture data can be detected by the 9-axis IMU installed on the bow body. The real-time posture data is input into the posture prediction engine through the IMU data interface to perform pause recognition through the LSTM behavior model (i.e., bowing behavior prediction, for example, input: 300ms IMU data window, output: 0 (playing) / 1 (short pause) / 2 (long pause), accuracy: > 95%, advantage: 3 times more energy-efficient than the timer), such as short pause recognition, long pause recognition, and output prediction results (0 / 1 / 2), where 0 can represent playing (i.e., corresponding to Figure 9 Full-function mode in the , 1 can indicate a short stop (i.e. corresponding Figure 9Short stop mode in ), 2 can represent long stop (i.e. corresponding Figure 9 The prediction result (0 / 1 / 2) is input into the state decider to select a hierarchical strategy and generate corresponding state instructions. The posture prediction engine can send the generated state instructions to the control interface of the power management unit to control the power management unit. The power management unit includes a module switch matrix and can monitor power consumption. By controlling the module switch matrix of the power management unit, the module switches corresponding to each sensor in the sensor system can be controlled to achieve power consumption control and power consumption monitoring. The wake-up circuit in the power controller is managed by a supercapacitor and can perform bow acceleration threshold detection (i.e., real-time comparison of the bow acceleration with a preset acceleration threshold). When the bow acceleration is greater than a preset acceleration threshold (e.g., greater than 0.5g) and lasts (i.e., maintained at greater than 0.5g) for a preset time threshold (e.g., 20s), a wake-up signal is generated and sent to the power management unit, so that the power management unit controls the module switches corresponding to each sensor in the sensor system according to the wake-up signal to wake the instrument into full-function mode. The sensor system enables sensor collaboration. For example, the IMU can sample at 100Hz, motion recognition supports seven bowing techniques, and the collaborative mechanism involves only the IMU participating in predictions. Advantage: zero additional hardware cost. The power management unit can implement hierarchical power management. For example, short-stop mode disables Wi-Fi / BLE, and long-stop mode only uses the IMU at 10Hz. Power consumption comparison: full-function mode: 120mA, short-stop mode: 72mA (a 40% decrease), and long-stop mode: 18mA (an 85% decrease). The wake-up circuit can implement supercapacitor wake-up. For example, the detection threshold is acceleration > 0.5g, the response time is < 20ms, and the technical support is supercapacitor RAM maintenance. Advantage: 15 times faster than restarting.

[0126] Continue as Figure 6 As shown, the musical instrument can also enter automatic sleep mode and perform low-power standby mode when there is no vibration for 5 seconds. Sleep mode can include shallow sleep (for example, entering short-stop mode) and deep sleep (for example, entering long-stop mode). Specifically, it can be determined according to the user's configuration whether to enter shallow sleep (for example, entering short-stop mode) or deep sleep (for example, entering long-stop mode) when there is no vibration for 5 seconds. When the musical instrument is in the sleep state of low-power standby, if the vibration of the strings is detected, the system startup of the musical instrument is executed, and data from each sensor is collected. For example, the thin film pressure sensor 1 that is tightly fitted between the bridge and the piano skin detects and obtains the pressure signal data of the bridge; the thin film pressure sensor 2 that is tightly fitted between the sound filter cotton and the piano skin detects and obtains the pressure signal data of the sound filter cotton; the piezoelectric ceramic piece located on the side wall of the bridge and attached to the bridge with a distance of 0.5 mm between the strings detects and obtains the vibration signal data of the strings.

[0127] After pressure signal conditioning of the bridge pressure signal data and the filter cotton pressure signal data, dual sensor data fusion is performed, and then the bow pressure value is calculated based on the fused data to obtain the bow pressure value.

[0128] Vibration signal processing is performed on the vibration signal data of the strings, and then frequency extraction is performed on the processed vibration signal. Pitch value conversion is performed based on the extracted frequency to obtain the pitch value corresponding to the vibration signal data.

[0129] The main control board data is integrated based on the obtained bow pressure value and pitch value, and dynamic curves of bow pressure and pitch are generated based on the integrated data and displayed on the neck screen.

[0130] Before performing pressure signal conditioning and vibration signal processing, the user can also perform system calibration. Specifically, the user can operate (for example, long press) the button on the screen (display) on the neck to trigger the system calibration of pressure signal conditioning, vibration signal processing and subsequent operations to ensure the accuracy of pressure signal conditioning, vibration signal processing and subsequent operations. Only after the system calibration is successful can the actual pressure signal conditioning of the bridge pressure signal data and the filter cotton pressure signal data, as well as the actual vibration signal processing of the string vibration signal data and subsequent operations be performed.

[0131] The user can operate (eg, short press) a button on the screen (display) on the neck to switch the display mode of the neck screen display.

[0132] For example, in this application, a dual pressure sensor fusion system can be realized: structural design: thin film pressure sensor 1, that is, bridge sensor → direct string pressure, thin film pressure sensor 1 filter cotton sensor → resonance pressure. Original α-β-γ fusion algorithm: P final = 0.6*P1 + 0.4*P2 + γ·dP / dt. P1 corresponds to the bridge pressure (i.e., the string pressure), P2 corresponds to the filter pressure (i.e., the resonance pressure), and γ is the coefficient. Temperature drift compensation: ±0.03N / °C → ±0.01N / °C. Pressure measurement accuracy: ±0.08N.

[0133] Direct pitch extraction from piezoelectric vibrations is possible: piezoelectric patch → zero-crossing detection. Accuracy: ±0.5Hz, delay: 2.6ms, power consumption: 3.5mW. Frequency f0 = N cross / (2·T sample ), where N cross =∑δ(s i ·s {i-1} <0).

[0134] It enables real-time dual-stream data processing: dual-core division of labor: Core 0 is dedicated to sensor data, while Core 1 is dedicated to display rendering. Priority scheduling: vibration signal > pressure signal. Interrupt response: <10μs.

[0135] The device can be embedded in or removable with a curved display, either by embedding the curved screen into the neck, slotting the neck, or making it removable. Display innovation: 240° viewing angle curved surface lamination technology. Three display modes are available: Standard mode (hyperbola + numerical value); Training mode (bow pressure threshold warning); and Tuning mode (pitch deviation indication).

[0136] It can realize magnetic fast charging energy system: physical connection of magnetic contacts, waterproof design: IP54 level (bottom of the tin support), using fast charging technology: 0→100% only takes 90 minutes, and can realize intelligent sleep: automatically shut down after 30 minutes of no operation.

[0137] The bow pressure and pitch monitoring and processing method for musical instrument performance in the embodiment of the present application can solve the problems of inaccurate bow pressure and pitch monitoring and non-intuitive feedback in erhu performance, and provide an offline real-time data visualization solution.

[0138] Figure 11 Schematic diagram of the main units of the instrument playing bow pressure and pitch monitoring processing device according to the embodiment of the present application. Figure 11 As shown, the musical instrument bow pressure and pitch monitoring processing device 1100 includes a musical instrument pattern determination unit 1101, a musical instrument pattern updating unit 1102, an extraction unit 1103, a data fusion unit 1104 and a display unit 1105.

[0139] The instrument mode determining unit 1101 is configured to, in response to sensor data of the instrument being acquired, determine an instrument mode based on the sensor data;

[0140] The instrument mode updating unit 1102 is configured to, in response to the instrument mode being the pause mode, control the instrument to enter a dormant state, acquire and update sensor data in real time, and update the instrument mode based on the updated sensor data and a preset wake-up condition;

[0141] an extraction unit 1103 configured to extract pressure signal data and vibration signal data from the updated sensor data in response to the updated musical instrument mode being the full-function mode;

[0142] a data fusion unit 1104 configured to determine preset weights of instrument components corresponding to the pressure signal data, and determine a fused pressure value based on the preset weights and the pressure signal data;

[0143] The display unit 1105 is configured to determine a display mode, generate analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and display the analysis result data on a screen embedded in the musical instrument.

[0144] In some embodiments, the instrument mode determination unit 1101 is further configured to: extract bowing posture data from the sensor data; and predict the corresponding instrument mode based on the bowing posture data using a behavioral model.

[0145] In some embodiments, the instrument mode update unit 1102 is further configured to: in response to the instrument mode being the short stop mode, the corresponding sleep state is turning off the wireless network and Bluetooth, disabling sensor fusion calculation, and controlling the instrument to enter the corresponding sleep state.

[0146] In some embodiments, the instrument mode update unit 1102 is further configured to: in response to the instrument mode being a long stop mode, the corresponding sleep state is to maintain the random access memory by a supercapacitor, control the inertial measurement unit to perform bow posture monitoring at a preset frequency, and set the wake-up delay to a preset duration, and control the instrument to enter the corresponding sleep state.

[0147] In some embodiments, the instrument mode update unit 1102 is further configured as follows: the preset wake-up conditions include the bow acceleration being greater than a preset acceleration threshold and the duration of the bowing reaching a preset duration threshold, the presence of vibration signal data and the duration of the vibration reaching a preset duration threshold. If the updated sensor data matches the preset wake-up conditions, the instrument mode is updated to the full-function mode.

[0148] In some embodiments, the musical instrument components corresponding to the pressure signal data include a bridge and filter cotton; the pressure signal data includes bridge pressure signal data and filter cotton pressure signal data; and the data fusion unit 1104 is further configured to: determine a first preset weight corresponding to the bridge and a second preset weight corresponding to the filter cotton; and the data fusion unit 1104 is further configured to: obtain a string pressure value based on the bridge pressure signal data; obtain a resonance pressure value based on the filter cotton pressure signal data; determine a bow pressure value based on the first preset weight, the string pressure value, the second preset weight and the resonance pressure value, and determine the bow pressure value as the fusion pressure value.

[0149] In some embodiments, the apparatus for monitoring and processing bow pressure and pitch of musical instruments further includes: Figure 11 The pitch value determination unit not shown in the figure is configured to: determine the string vibration frequency corresponding to the vibration signal data through zero crossing detection; and determine the pitch value corresponding to the vibration signal data based on the string vibration frequency.

[0150] It should be noted that the musical instrument bow pressure and pitch monitoring processing method and the musical instrument bow pressure and pitch monitoring processing device of the present application have corresponding relationships in specific implementation contents, so the repeated contents will not be explained again.

[0151] The present application also provides an electronic device for monitoring and processing the bow pressure and pitch of a musical instrument, including: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the one or more processors implement the method for monitoring and processing the bow pressure and pitch of a musical instrument provided in an embodiment of the present application.

[0152] The present application also provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the method for monitoring and processing the bow pressure and pitch of an instrument provided in an embodiment of the present application is implemented.

[0153] The embodiment of the present application also provides a computer program product.

[0154] A computer program product according to an embodiment of the present application includes a computer program, which, when executed by a processor, implements the bow pressure and pitch monitoring processing method for musical instrument performance provided by an embodiment of the present application.

[0155] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A method for monitoring and processing bow pressure and pitch of a musical instrument, characterized in that: include: In response to acquiring sensor data of the musical instrument, determining a musical instrument mode based on the sensor data; In response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state, acquiring and updating the sensor data in real time, and updating the musical instrument mode based on the updated sensor data and a preset wake-up condition; In response to the updated musical instrument mode being the full-function mode, extracting pressure signal data and vibration signal data from the updated sensor data; determining a preset weight of an instrument component corresponding to the pressure signal data, and determining a fused pressure value based on the preset weight and the pressure signal data; A display mode is determined, analysis result data matching the display mode is generated based on the fused pressure value and the pitch value corresponding to the vibration signal data, and the analysis result data is displayed on a screen embedded in the musical instrument.

2. The method according to claim 1, characterized in that The determining of the instrument mode based on the sensor data comprises: extracting bow posture data from the sensor data; The corresponding instrument mode is predicted based on the bowing posture data through a behavioral model.

3. The method according to claim 1, characterized in that In response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state includes: In response to the musical instrument mode being the short-stop mode, the corresponding sleep state is to turn off the wireless network and Bluetooth, disable sensor fusion calculation, and control the musical instrument to enter the corresponding sleep state.

4. The method according to claim 1, wherein In response to the musical instrument mode being the pause mode, controlling the musical instrument to enter a dormant state includes: In response to the instrument mode being the long-stop mode, the corresponding sleep state is that the random access memory is maintained by the supercapacitor, the inertial measurement unit is controlled to perform bow posture monitoring at a preset frequency, and the wake-up delay is set to a preset duration, so as to control the instrument to enter the corresponding sleep state.

5. The method according to claim 1, wherein Updating the musical instrument mode based on the updated sensor data and the preset wake-up condition includes: The preset wake-up conditions include that the bow acceleration is greater than the preset acceleration threshold and the duration reaches the preset duration threshold, and there is vibration signal data and the vibration duration reaches the preset duration threshold. If the updated sensor data matches the preset wake-up conditions, the instrument mode is updated to the full-function mode.

6. The method according to claim 1, characterized in that The musical instrument components corresponding to the pressure signal data include the bridge and the sound filter cotton; the pressure signal data includes the bridge pressure signal data and the sound filter cotton pressure signal data; as well as Determining the preset weight of the musical instrument component corresponding to the pressure signal data includes: Determining a first preset weight corresponding to the bridge and a second preset weight corresponding to the filter cotton; and The determining of the fused pressure value based on the preset weight and the pressure signal data includes: Obtaining a string pressure value based on the bridge pressure signal data; Obtaining a resonance pressure value based on the sound filter cotton pressure signal data; A bow pressure value is determined based on the first preset weight, the chord pressure value, the second preset weight, and the resonance pressure value, and the bow pressure value is determined as a fusion pressure value.

7. The method according to claim 6, characterized in that Before generating analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, the method further includes: Determine the string vibration frequency corresponding to the vibration signal data by zero-crossing detection; Based on the string vibration frequency, a pitch value corresponding to the vibration signal data is determined.

8. A device for monitoring and processing bow pressure and pitch of a musical instrument, characterized in that: include: a musical instrument mode determination unit configured to, in response to acquiring sensor data of the musical instrument, determine a musical instrument mode based on the sensor data; a musical instrument mode updating unit configured to, in response to the musical instrument mode being the pause mode, control the musical instrument to enter a dormant state, acquire and update the sensor data in real time, and update the musical instrument mode based on the updated sensor data and a preset wake-up condition; an extraction unit configured to extract pressure signal data and vibration signal data from the updated sensor data in response to the updated musical instrument mode being the full-function mode; a data fusion unit configured to determine a preset weight of a musical instrument component corresponding to the pressure signal data, and determine a fused pressure value based on the preset weight and the pressure signal data; The display unit is configured to determine a display mode, generate analysis result data matching the display mode based on the fused pressure value and the pitch value corresponding to the vibration signal data, and display the analysis result data on a screen embedded in the musical instrument.

9. An electronic device for monitoring and processing bow pressure and pitch of a musical instrument, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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