Signal noise reduction processing method and device, auscultation equipment and storage medium

Abstract

The invention relates to the technical field of signal processing, in particular to a signal noise reduction processing method and device, auscultation equipment and a storage medium, the method is applied to a stethoscope comprising a body sound signal module and an environment signal module, and a body sound inlet hole of the body sound signal module is attached to a sound receiving cavity shell; the body sound inlet hole is communicated with a sound receiving hole formed in the sound receiving cavity shell, and a noise sound inlet hole of the environment signal module is formed in the sound receiving cavity shell in a back-to-back mode; after a sound receiving cavity of the stethoscope is in contact with the human body surface of a target user to form a closed space, a body sound signal collected by a body sound signal module and an environment noise signal collected by an environment signal module are obtained; performing signal filtering processing on the body sound signal, and determining a body sound target signal according to the obtained body sound filtering signal and the pickup included angle of the body sound signal module; and determining a body sound real signal according to the body sound target signal and the environment noise signal. The invention aims to improve the noise reduction processing capability of the stethoscope so as to improve the auscultation accuracy.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a signal noise reduction processing method, device, stethoscope equipment and storage medium. Background Art

[0002] With the continuous development of medical technology and signal processing technology, electronic smart stethoscopes have become an indispensable tool in modern medical diagnosis.

[0003] Currently, the electronic smart stethoscopes on the market mainly have the functions of collecting heart and lung sounds and single noise reduction, but their auscultation effect is still seriously affected by environmental noise. In addition, although electronic stethoscopes can amplify weak body sound signals (such as heart sounds, lung sounds, etc.), they are easily disturbed by environmental noise due to their high sensitivity, thus reducing the accuracy of diagnosis.

[0004] Therefore, how to improve the noise reduction processing capability of the stethoscope to improve the accuracy of auscultation is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of this application is to provide a signal noise reduction processing method, device, auscultation equipment and storage medium, aiming to improve the noise reduction processing capability of a stethoscope to improve the accuracy of auscultation.

[0006] To achieve the above-mentioned purpose, the present application provides a signal noise reduction processing method, which is applied to a stethoscope including a body sound signal module and an environmental signal module, wherein the body sound inlet hole of the body sound signal module is mounted on a sound receiving cavity housing of the stethoscope, the body sound inlet hole is connected to a sound receiving hole provided on the sound receiving cavity housing, and the noise inlet hole of the environmental signal module is provided on the sound receiving cavity housing in a direction opposite to that of the stethoscope;

[0007] The signal noise reduction processing method comprises:

[0008] After the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space, obtaining the body sound signal collected by the body sound signal module and the environmental noise signal collected by the environmental signal module;

[0009] Performing signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determining a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module;

[0010] A real body sound signal is determined according to the body sound target signal and the environmental noise signal.

[0011] In one embodiment, the body sound signal module includes a first body sound sensor and a second body sound sensor arranged side by side at a preset distance interval, and the step of determining the body sound target signal based on the body sound filter signal and the sound pickup angle of the body sound signal module includes:

[0012] According to the first sound pickup angle area of ​​the first body sound sensor and the second sound pickup angle area of ​​the second body sound sensor, construct a sound pickup angle of the body sound signal module, and determine a signal collection frequency band of the sound pickup angle;

[0013] A signal frequency band identical to the signal acquisition frequency band is searched from the overall signal frequency band of the body sound filter signal, and the body sound filter signal corresponding to the signal frequency band identical to the signal acquisition frequency band is used as the body sound target signal.

[0014] In one embodiment, the step of constructing the sound pickup angle of the body sound signal module according to the first sound pickup angle area of ​​the first body sound sensor and the second sound pickup angle area of ​​the second body sound sensor includes:

[0015] Determine a first sound pickup angle area of ​​the first body sound sensor and a second sound pickup angle area of ​​the second body sound sensor, and obtain a sound pickup intersection area formed by the first sound pickup angle area and the second sound pickup angle area;

[0016] Subtracting the minimum sound pickup angle value in the sound pickup intersection area from the maximum sound pickup angle value in the sound pickup intersection area to obtain the sound pickup intersection angle value of the sound pickup intersection area;

[0017] Taking the middle position between the first body sound sensor and the second body sound sensor as the origin and the sensor central axis passing through the origin as the angle bisector, an angle area with the same value as the sound pickup intersection angle is constructed in the sound receiving cavity as the sound pickup angle of the body sound signal module.

[0018] In one embodiment, the step of determining the real body sound signal according to the body sound target signal and the ambient noise signal comprises:

[0019] Determining a noise threshold of the ambient noise signal and a body sound threshold of the body sound target signal;

[0020] According to a preset sound pickup cavity transfer function, the inverse of the noise threshold is superimposed on the body sound threshold to obtain a body sound prediction signal of the body sound signal module;

[0021] Transforming the body sound prediction signal into a body sound observation signal of the body sound signal module by Gaussian transformation, and detecting whether the body sound prediction signal is within a signal observation threshold range corresponding to the body sound observation signal;

[0022] If the body sound prediction signal is within the signal observation threshold range, the body sound prediction signal is used as the body sound real signal.

[0023] In one embodiment, the step of Gaussian transforming the body sound prediction signal into the body sound observation signal of the body sound signal module comprises:

[0024] Determining a plurality of signal frequency values ​​of the body sound prediction signal within a preset collection time;

[0025] Performing mean processing on each of the signal frequency values ​​to obtain a frequency mean between each of the signal frequency values, and performing variance processing on a square difference between each of the signal frequency values ​​and the frequency mean to obtain a frequency variance value between each of the signal frequency values;

[0026] Gaussian transformation is performed according to the frequency mean and the frequency variance value to obtain a body sound observation signal of the body sound signal module.

[0027] In one embodiment, after the step of detecting whether the body sound prediction signal is within a signal observation threshold range corresponding to the body sound observation signal, the signal noise reduction processing method includes:

[0028] If the body sound prediction signal is not within the signal observation threshold range, determining a plurality of signal observation frequency values ​​of the body sound observation signal at the acquisition time, and determining a total observation frequency value between each of the signal observation frequency values, and a total signal frequency value between each of the signal frequency values;

[0029] Calculating the log-likelihood value according to the divisor quotient between the total signal frequency value and the total observation frequency value to obtain an adjustment function of the body sound signal module;

[0030] The adjustment function is used as the next pickup cavity transfer function, and the step of superimposing the inverse of the noise threshold onto the body sound threshold according to the preset pickup cavity transfer function is returned to be executed.

[0031] In one embodiment, after the step of determining the real body sound signal according to the body sound target signal and the ambient noise signal, the signal noise reduction processing method further includes:

[0032] The real body sound signal is input into a preset auscultation record model for model training to obtain an auscultation record report of the target user, and the health results of the auscultation record report are displayed to the target user.

[0033] In addition, to achieve the above-mentioned purpose, the present application also provides a signal noise reduction processing device, which is applied to a stethoscope including a body sound signal module and an environmental signal module, wherein the body sound inlet hole of the body sound signal module is mounted on a sound receiving cavity housing of the stethoscope, the body sound inlet hole is connected to the sound receiving hole provided on the sound receiving cavity housing, and the noise inlet hole of the environmental signal module is provided on the sound receiving cavity housing in a reverse direction, and the signal noise reduction processing device comprises:

[0034] An acquisition module, used for acquiring the body sound signal collected by the body sound signal module and the environmental noise signal collected by the environmental signal module after the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space;

[0035] A filtering module, configured to perform signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determine a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module;

[0036] The real signal determination module is used to determine the real body sound signal according to the body sound target signal and the environmental noise signal.

[0037] Each functional module of the signal noise reduction processing device of the present application implements the steps of the signal noise reduction processing method of the present application as described above during operation.

[0038] In addition, to achieve the above-mentioned purpose, the present application also provides a stethoscope device, which includes a memory, a processor, and a signal noise reduction processing program stored in the memory and executable on the processor, and the signal noise reduction processing program implements the steps of the above-mentioned signal noise reduction processing method when executed by the processor.

[0039] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a signal noise reduction processing program is stored on the computer-readable storage medium. When the signal noise reduction processing program is executed by the processor, the steps of the above-mentioned signal noise reduction processing method are implemented.

[0040] The present application provides a signal noise reduction processing method to optimize the noise reduction processing capability of existing stethoscopes. Specifically, the body sound inlet hole of the body sound signal module provided in the present application is mounted on the sound receiving cavity shell of the stethoscope and is connected with the sound receiving hole provided on the sound receiving cavity shell; next, after the sound receiving cavity of the stethoscope contacts the human body surface of the target user to form a closed space, the hole design connecting the body sound inlet hole and the sound receiving hole can effectively reduce the loss and distortion of the body sound signal during the transmission process, ensuring that the body sound signal module can accurately collect the body sound signal. At the same time, through the structure that the noise inlet hole of the environmental signal module is provided on the sound receiving cavity shell facing away, the environmental signal module can clearly capture the surrounding environmental noise signal, so as to avoid interference with the body. The body sound signal is confused; subsequently, the body sound signal is effectively filtered to obtain a clearer and purer body sound filter signal, and combined with the sound pickup angle that reflects the signal receiving radiation range of the body sound signal module, a more accurate and clear body sound target signal can be further determined, effectively eliminating the signal interference outside the signal receiving radiation range; finally, the ambient noise signal collected by the ambient signal module is used to offset the noise part of the body sound target signal, so as to obtain an accurate body sound real signal, effectively improving the signal-to-noise ratio of the body sound signal, thereby significantly improving the noise reduction processing capability of the stethoscope, and then enhancing the accuracy of auscultation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flowchart of the first embodiment of the signal noise reduction processing method of the present application;

[0042] Figure 2 It is a schematic diagram of the assembly structure of a stethoscope microphone involved in the embodiment of the present application;

[0043] Figure 3 is a block diagram of a stethoscope system involved in an embodiment of the present application;

[0044] Figure 4 is a schematic diagram of a dual-microphone sound pickup array involved in an embodiment of the present application;

[0045] Figure 5 This is a block diagram of the active noise reduction principle involved in the embodiment of the present application;

[0046] Figure 6 It is a structural schematic diagram of a signal noise reduction processing device involved in an embodiment of the present application;

[0047] Figure 7 This is a schematic diagram of the structure of the stethoscope device involved in the embodiment of the present application.

[0048] Description of Figure Numbers:

[0049] 10. Body sound signal module; 20. Environmental signal module; 101. First body sound sensor; 102. Second body sound sensor.

[0050] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] The present application provides a method for signal noise reduction processing, referring to Figure 1 As shown, Figure 1 It is a flowchart of the first embodiment of the signal noise reduction processing method of the present application.

[0052] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0053] The electronic smart stethoscopes currently on the market only support simple heart and lung sound collection or a single noise reduction function. If multiple active noise reduction functions are added, the auscultation effect will be greatly improved.

[0054] Traditional electronic stethoscopes can amplify weak body sound signals and have functions such as signal storage, display, and playback, which provides great convenience for doctors to listen to their stethoscopes. However, due to its high sensitivity, it is also very susceptible to interference from environmental noise. In order to reduce the sensitivity of the stethoscope to environmental noise, a pickup made of piezoelectric film material can be used. Piezoelectric film pickups collect displacement signals, so they are not easily disturbed by environmental noise. However, in order to ensure sensitivity, its stethoscope head needs to be designed with a specific structure, which is costly and difficult to promote to home users. Current electronic stethoscopes generally use electret microphones for sound pickup, which has the advantages of simple structural design and low cost. In other words, electret microphones are one of the preferred sensors for existing electronic stethoscopes. However, electret microphones are very sensitive and are easily disturbed by environmental noise even if they are encapsulated in a metal cavity.

[0055] In order to reduce the impact of environmental noise, one of the most common denoising methods for this type of application is dual-microphone adaptive filtering, which uses the main microphone to collect noisy signals and the secondary microphone to collect environmental noise. The environmental noise measured by the secondary microphone is linearly processed to offset the noise in the noisy signal to achieve denoising. The dual-microphone adaptive filtering method has been widely used in many occasions such as teleconferencing and mobile phones due to its strong denoising ability. However, the promotion of dual-microphone adaptive filtering on electronic stethoscopes has the following disadvantages:

[0056] (I) Currently, products with dual-microphone adaptive filtering are either too large or too expensive; however, electronic stethoscopes need to be portable and handheld, so their size is limited; in order to achieve promotion and application, the cost of electronic stethoscopes should not be too high;

[0057] (II) When mobile medical care is used to achieve remote auscultation, mobile phones are usually used as signal receiving terminals. At this time, common access methods include audio port and Bluetooth. However, when a Bluetooth mobile phone is connected to other Bluetooth headsets or bracelets and other devices, manual switching and pairing are required, and the Bluetooth signal transmission bandwidth and rate are relatively low, which makes it difficult to meet the needs of high-quality audio signal transmission.

[0058] In order to solve the technical defects that the existing electronic stethoscopes are easily disturbed by environmental noise and have difficulty in accurately identifying body sound signals, the present application provides a signal noise reduction processing method, device, stethoscope equipment and storage medium.

[0059] The signal noise reduction processing method of the present application is applied to a stethoscope including a body sound signal module 10 and an environmental signal module 20, or is executed by a stethoscope device that performs noise reduction processing on the signal, specifically, the control center in the stethoscope device executes the following signal noise reduction processing method. In the following embodiments, the execution subject of the present application will not be described in detail. In addition, the body sound input hole of the body sound signal module 10 provided in the present application is mounted on the sound receiving cavity housing of the stethoscope, and the body sound input hole is connected to the sound receiving hole provided in the sound receiving cavity housing, and the noise input hole of the environmental signal module 20 is provided on the sound receiving cavity housing with its back facing.

[0060] The signal noise reduction processing method of the present application includes:

[0061] Step S10: After the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space, the body sound signal collected by the body sound signal module 10 and the environmental noise signal collected by the environmental signal module 20 are obtained.

[0062] In this embodiment, the stethoscope provided in the present application includes a body sound signal module 10 and an environmental signal module 20. The body sound inlet hole of the body sound signal module 10 is precisely mounted on the sound receiving cavity housing of the stethoscope to ensure direct communication with the sound receiving hole on the sound receiving cavity housing. Exemplarily, when the sound receiving cavity of the stethoscope is in close contact with the human body surface of the target user to form a closed space, the energy loss and distortion of the body sound signal during transmission can be significantly reduced through the connecting hole between the body sound inlet hole and the sound receiving hole, thereby ensuring that the body sound signal module 10 can accurately capture the body sound signal. At the same time, the noise inlet hole in the environmental signal module 20 is cleverly arranged on the back of the sound receiving cavity housing. This back-to-back placement structure allows the environmental signal module 20 to clearly capture the environmental noise signal in the surrounding environment, so that the body sound signal and the environmental noise signal can be clearly distinguished, avoiding mutual interference between the two, and ensuring that the data collected by the stethoscope is purer and more accurate.

[0063] It should be noted that the body sound signal module 10 provided in the present application may include a first body sound sensor 101 and a second body sound sensor 102 arranged side by side at a preset distance interval, and the first body sound sensor 101 and the second body sound sensor 102 are both Figure 2 The bottom hole MEMS (Micro Electromechanical System) microphone shown. Exemplarily, the bottom hole MEMS microphone includes at least a PCB substrate, a MEMS device, a diaphragm, a back plate and an ASIC (Application Specific Integrated Circuit). Exemplarily, the PCB substrate is provided with a plurality of pads at preset arrangement intervals and welded to a preset FPC (Flexible Printed Circuit), and the flexible printed circuit board is adhered and fixedly connected to the sound receiving cavity housing by double-sided tape, that is, the present application places the bottom hole MEMS microphone on the sound receiving cavity housing of the stethoscope instead of the inner wall, which can effectively facilitate production, assembly and maintenance. In addition, the PCB substrate is also provided with a body sound input hole connected to the sound receiving hole on the sound receiving cavity housing, and the PCB substrate at both ends of the body sound input hole is fixedly connected with a MEMS device, and diaphragms of the same size are respectively provided on both ends of the MEMS device, that is, the MEMS device is electrically connected to the back plate by welding the diaphragm, and the back plate is electrically connected to the PCB substrate through the ASIC. In addition, referring to Figure 2 In the present application, sealing foam or sponge is attached around the bottom hole MEMS microphone, and double-sided tape is used around the body sound input hole to seal the body sound input hole, thereby increasing the sound receiving directivity of the bottom hole MEMS microphone and reducing noise pickup.

[0064] The environmental signal module 20 is Figure 2 The top-opening MEMS (Micro Electromechanical System) microphone shown in the figure also includes a PCB substrate, a MEMS device, a diaphragm, a back plate and an ASIC, wherein the PCB substrate is provided with a plurality of pads at preset arrangement intervals and is welded and connected to a preset FPC (Flexible Printed Circuit), and the pins at both ends of the MEMS device are electrically connected to the closed space formed by the PCB substrate to form the back cavity of the top-opening MEMS microphone. In addition, diaphragms of the same size are respectively provided on both ends of the MEMS device, that is, the MEMS device is electrically connected to the back plate by welding through the diaphragm, and the back plate is electrically connected to the PCB substrate through the ASIC, thereby forming a microphone collection circuit, and then a noise inlet hole is provided on the surface relative to the PCB substrate in the packaging cavity that encapsulates the microphone collection circuit. In addition, the hole position of the noise inlet hole can be understood as the front cavity of the top-opening MEMS microphone, which is provided directly in front of the ASIC.

[0065] In addition, it should be noted that the sensors provided in the body sound signal module 10 and the environmental signal module 20 of the present application are MEMS microphones, which can perform SMT (Surface Mounted Technology) operations with a preset flexible printed circuit board. Compared with traditional ECM (Electret Condenser Micphone) microphones, MEMS microphones will produce lower vibration coupling to PCB noise caused by speakers installed on the same PCB substrate. At the same time, their sensitivity is less affected by temperature, vibration, humidity and time, and the consistency of sensitivity and frequency response is better, which is beneficial to subsequent noise reduction processing.

[0066] Step S20 : ​​performing signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determining a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module 10 .

[0067] In this embodiment, the body sound signal is amplified according to a preset signal amplification factor to obtain an amplified body sound signal; next, a signal frequency band that is the same as the preset signal frequency range is found from the amplified body sound signal, so that interference sounds in other frequency bands (such as environmental noise, high-frequency noise, etc.) can be effectively filtered out, and then a purer body sound filter signal can be generated based on the signal frequency band that is the same as the signal frequency range, and combined with the pickup angle that reflects the signal receiving radiation range of the body sound signal module 10, a more accurate and clear body sound target signal can be further determined, effectively eliminating signal interference outside the signal receiving radiation range.

[0068] For example, refer to Figure 3 , Figure 3 It is a block diagram of the stethoscope system involved in the embodiment scheme of the present application. The body sound signal provided in the present application refers to the cardiopulmonary sound collected simultaneously by the first body sound sensor 101 and the second body sound sensor 102; according to the electrical connection between the body sound signal module 10 and the low-noise amplifier, after receiving the body sound signal uploaded by the body sound signal module 10, the low-noise amplifier amplifies the body sound signal according to the preset signal amplification factor, and the body sound amplified signal can be accurately obtained. In addition, the low-noise amplifier provided in the present application ensures that the body sound signal maintains a high sound quality while amplifying it, and reduces the influence of noise and distortion; next, according to the electrical connection between the low-noise amplifier and the bandpass filter, after receiving the body sound amplified signal sent by the bandpass filter, the bandpass filter filters the body sound amplified signal according to its own preset signal frequency range, so that the body sound filtered signal after filtering out interference sounds in other frequency bands can be obtained. Next, according to the electrical connection between the bandpass filter and the active noise reduction audio processing chip, when the active noise reduction audio processing chip receives the body sound filter signal sent by the bandpass filter, the body sound filter signal is subjected to preliminary noise reduction processing according to the sound pickup angle of the body sound signal module 10, so that a clearer body sound target signal can be accurately obtained, and signal interference outside the signal receiving radiation range of the sound pickup angle can be effectively eliminated. In addition, the low-noise amplifier and bandpass filter provided in the present application amplify and filter the ambient noise signal while amplifying and filtering the body sound signal.

[0069] It should be noted that the low-noise amplifier provided in the present application may be a preamplifier of model PGA2500, which has an adjustable amplification factor of 10dB to 65dB (ie, a preset signal amplification factor), and can adjust the amplification degree of the microphone signal according to actual needs.

[0070] The body sound signal may include a heart sound signal and a lung sound signal, and the heart sound signal is mainly concentrated in the frequency range of 30 to 500 Hz, while the lung sound signal is in the range of 100 to 1000 Hz. Therefore, the bandpass filter provided in the present application may be an active bandpass filter, and the passband frequency of the active bandpass filter may be set to 30 to 1000 Hz.

[0071] Step S30: determining a real body sound signal according to the body sound target signal and the ambient noise signal.

[0072] In this embodiment, refer to Figure 3According to the electrical connection among the environmental signal module 20, the low noise amplifier, the bandpass filter and the active noise reduction audio processing chip, after receiving the amplified and filtered environmental noise signal, the active noise reduction audio processing chip can offset the noise part in the body sound target signal through the environmental noise signal, thereby obtaining an accurate body sound real signal, effectively improving the signal-to-noise ratio of the body sound signal, thereby significantly improving the noise reduction processing capability of the stethoscope, and further enhancing the accuracy of auscultation.

[0073] In summary, the present application provides a signal noise reduction processing method to optimize the noise reduction processing capability of the existing stethoscope. Specifically, the body sound inlet hole of the body sound signal module 10 provided in the present application is mounted on the sound receiving cavity shell of the stethoscope, and is connected with the sound receiving hole provided on the sound receiving cavity shell; next, after the sound receiving cavity of the stethoscope contacts the human body surface of the target user to form a closed space, the hole design connecting the body sound inlet hole and the sound receiving hole can effectively reduce the loss and distortion of the body sound signal during the transmission process, ensuring that the body sound signal module 10 can accurately collect the body sound signal, and at the same time, through the structure that the noise inlet hole of the environmental signal module 20 is provided on the sound receiving cavity shell with its back facing, the environmental signal module 20 can clearly capture the surrounding environmental noise signal, so as to avoid confused with the body sound signal; then, the body sound signal is effectively filtered to obtain a clearer and purer body sound filtered signal, and combined with the sound pickup angle reflecting the signal receiving radiation range of the body sound signal module 10, a more accurate and clear body sound target signal can be further determined, and the signal interference outside the signal receiving radiation range is effectively eliminated; finally, the ambient noise signal collected by the ambient signal module 20 is used to offset the noise part in the body sound target signal, so as to obtain an accurate body sound real signal, effectively improve the signal-to-noise ratio of the body sound signal, thereby significantly improving the noise reduction processing capability of the stethoscope, and then enhancing the accuracy of auscultation.

[0074] Furthermore, based on the first embodiment of the signal noise reduction processing method of the present application, a second embodiment of the signal noise reduction processing method of the present application is proposed.

[0075] Further, in some feasible embodiments, the body sound signal module 10 includes a first body sound sensor 101 and a second body sound sensor 102 arranged side by side at a preset distance interval, and the above step S20: determining the body sound target signal according to the body sound filter signal and the sound pickup angle of the body sound signal module 10, further includes the following implementation steps:

[0076] Step S201: constructing a sound pickup angle of the body sound signal module 10 according to a first sound pickup angle area of ​​the first body sound sensor 101 and a second sound pickup angle area of ​​the second body sound sensor 102, and determining a signal collection frequency band of the sound pickup angle.

[0077] In this embodiment, the angle range in which the first body sound sensor 101 can effectively pick up sound is taken as the first sound pickup angle area, and the angle range in which the second body sound sensor 102 can effectively pick up sound is taken as the second sound pickup angle area. Subsequently, based on the same angle range as the first sound pickup angle area and the second sound pickup angle area, the sound pickup angle can be accurately generated, that is, the sound pickup angle refers to the range in which the first body sound sensor 101 and the second sensor can pick up sound together, and then the range in which the sound pickup angle can pick up sound is taken as the signal acquisition frequency band of the sound pickup angle.

[0078] Step S202: searching for a signal frequency band identical to the signal acquisition frequency band from the overall signal frequency band of the body sound filter signal, and taking the body sound filter signal corresponding to the signal frequency band identical to the signal acquisition frequency band as the body sound target signal.

[0079] In this embodiment, in the overall frequency band of the body sound filter signal, the frequency band portion that matches the signal acquisition frequency band corresponding to the sound pickup angle is screened out. Specifically, the frequency band portion that is the same as the signal acquisition frequency band in the overall frequency band of the body sound filter signal is used as the frequency band portion that matches the signal acquisition frequency band, and then the frequency band portion that matches the signal acquisition frequency band is determined as the body sound target signal, thereby effectively eliminating signal interference outside the signal reception radiation range of the sound pickup angle.

[0080] Furthermore, in some other feasible embodiments, the above step S201: constructing the sound pickup angle of the body sound signal module 10 according to the first sound pickup angle area of ​​the first body sound sensor 101 and the second sound pickup angle area of ​​the second body sound sensor 102 may also include the following implementation steps:

[0081] Step S2011: determine a first sound pickup angle area of ​​the first body sound sensor 101 and a second sound pickup angle area of ​​the second body sound sensor 102, and obtain a sound pickup intersection area formed by the first sound pickup angle area and the second sound pickup angle area.

[0082] In this embodiment, the angle range in which the first body sound sensor 101 can effectively pick up sound is taken as the first sound pickup angle area, and the angle range in which the second body sound sensor 102 can effectively pick up sound is taken as the second sound pickup angle area, and then the angle range in which the first sound pickup angle area and the second sound pickup angle area are the same is taken as the sound pickup intersection area.

[0083] Step S2012: obtaining a sound pickup intersection angle value of the sound pickup intersection area by subtracting a minimum sound pickup angle value in the sound pickup intersection area from a maximum sound pickup angle value in the sound pickup intersection area.

[0084] In this embodiment, by calculating the difference between the maximum and minimum sound pickup angle values ​​in the sound pickup intersection area, the angle range in which the two body sound sensors can pick up sound together, that is, the sound pickup intersection angle value of the sound pickup intersection area, can be accurately determined. This is crucial for application scenarios that require precise control of the sound source or the need to exclude noise from a specific direction. Specifically, within a determined sound pickup intersection angle range, the two body sound sensors can receive body sound signals at the same time, which helps reduce errors introduced by the position or directivity limitations of a single sensor and improves the accuracy of body sound signal acquisition.

[0085] Step S2013: Taking the middle position between the first body sound sensor 101 and the second body sound sensor 102 as the origin and the sensor central axis passing through the origin as the angle bisector, construct an angle area with the same value as the sound pickup intersection angle in the sound receiving cavity as the sound pickup angle of the body sound signal module 10.

[0086] In this embodiment, refer to Figure 4 , Figure 4 1 is a schematic diagram of a dual microphone pickup array involved in the embodiment of the present application. The present application constructs an angle region with the same value as the pickup intersection angle in the sound receiving cavity as the pickup angle of the body sound signal module 10 (i.e. Figure 4 Specifically, the present application takes the middle position between the first body sound sensor 101 and the second body sound sensor 102 as the origin, and takes the sensor center axis passing through the origin as the angle bisector, ensuring that the sound pickup angle can accurately match the effective sound pickup range of the first body sound sensor 101 and the second body sound sensor 102, thereby effectively reducing the interference of non-body sound target signals, that is, reducing Figure 4 The noise interference in the two dashed triangle areas shown significantly improves the quality and clarity of the body sound signal, thereby making subsequent signal processing more accurate and reliable.

[0087] Furthermore, in some feasible embodiments, the above step S30: determining the real body sound signal according to the body sound target signal and the ambient noise signal, further includes the following implementation steps:

[0088] Step S301: determining a noise threshold of the ambient noise signal and a body sound threshold of the body sound target signal.

[0089] In this embodiment, refer to Figure 3 After the active noise reduction audio processing chip receives the amplified and filtered ambient noise signal and body sound target signal respectively, the active noise reduction audio processing chip can accurately obtain the noise threshold of the ambient noise signal and the body sound threshold of the body sound target signal, thereby providing accurate and effective data support for the determination of the subsequent body sound prediction signal.

[0090] Step S302: superimposing the inverse of the noise threshold onto the body sound threshold according to a preset sound pickup cavity transfer function to obtain a body sound prediction signal of the body sound signal module 10 .

[0091] In this embodiment, refer to Figure 5 , Figure 5 This is a block diagram of the active noise reduction principle involved in the embodiment of the present application. When the ambient noise signal (i.e. Figure 5 The Noise shown in FIG. 1 is transmitted to the body sound target signal (i.e., Figure 5 When the sound pickup cavity of the sound (Sound) shown in the figure is detected, the inverse number of the noise threshold of the environmental noise signal is superimposed on the body sound threshold of the body sound target signal, so that the body sound prediction signal of the body sound signal module 10 can be accurately obtained. That is, the present application can effectively obtain the body sound prediction signal with the external noise filtered out by the inverse superposition noise reduction process.

[0092] It should be noted that the algorithm of the inverse superposition noise reduction process can be expressed by the following formula (1):

[0093] D O =D Sound -G(w)*D Noise …………Formula (1)

[0094] Among them, D O It can be understood as the body sound prediction signal of the body sound signal module 10; D siund It can be understood as the body sound threshold of the body sound target signal; G(w) can be understood as the preset pickup cavity transfer function, which can be customized according to actual application requirements, and this application does not impose any restrictions here; D Noise It can be understood as the noise threshold of the ambient noise signal.

[0095] Step S303: transforming the body sound prediction signal into a body sound observation signal of the body sound signal module 10 through Gaussian transformation, and detecting whether the body sound prediction signal is within a signal observation threshold range corresponding to the body sound observation signal;

[0096] Step S304: if the body sound prediction signal is within the signal observation threshold range, the body sound prediction signal is used as the body sound real signal.

[0097] In this embodiment, Figure 3The active noise reduction audio processing chip shown in the figure transforms the body sound prediction signal into the body sound observation signal of the body sound signal module 10 through Gaussian transformation, and then detects whether the body sound prediction signal is within the signal observation threshold range corresponding to the body sound observation signal. If the body sound prediction signal is within the signal observation threshold range, the body sound prediction signal is used as the body sound real signal through the feedforward processing module (i.e. Figure 5 The Dff shown in the figure is then output, thereby ensuring the time synchronization between the body sound signals of different body sound sensors and effectively improving the output quality of the real body sound signal.

[0098] The signal observation threshold range can be customized according to actual application requirements. For example, the signal observation threshold range can be understood as floating around the signal threshold of the body sound observation signal according to an increase or decrease of ±0.1. The above embodiment is only one implementation of the present application, and the present application does not make any limitation here.

[0099] Furthermore, in some other feasible embodiments, the above step S303: transforming the body sound prediction signal into the body sound observation signal of the body sound signal module 10 by Gaussian transform may also include the following implementation steps:

[0100] Step S3031: determining a plurality of signal frequency values ​​of the body sound prediction signal within a preset collection time;

[0101] Step S3032: performing mean processing on each of the signal frequency values ​​to obtain a frequency mean between each of the signal frequency values, and performing variance processing on a square difference between each of the signal frequency values ​​and the frequency mean to obtain a frequency variance value between each of the signal frequency values.

[0102] In this embodiment, after determining multiple signal frequency values ​​of the body sound prediction signal within a preset acquisition time, the total frequency value between each signal frequency value can be accurately calculated, and then the frequency mean used to characterize the central trend of all signal frequencies can be accurately calculated based on the total frequency value and the total number of all signal frequency values; next, the square difference between each signal frequency value and the frequency mean is calculated, so that the discreteness and fluctuation of all signal frequencies can be effectively quantified; next, the total square difference between all square differences is divided by the total number of all signal frequency values, so that the frequency variance value between each signal frequency value can be accurately calculated, so as to provide strong data support for the subsequent determination of the body sound observation signal under an ideal state.

[0103] Step S3033: performing Gaussian transformation according to the frequency mean and the frequency variance value to obtain the body sound observation signal of the body sound signal module 10.

[0104] In this embodiment, by performing Gaussian transformation on the frequency mean and frequency variance value according to a preset Gaussian transformation function, a body sound observation signal close to an ideal state (i.e., a state without noise interference) can be accurately obtained, thereby providing an accurate and reliable judgment standard for determining the true body sound signal.

[0105] It should be noted that the preset Gaussian transformation function can be shown as the following formula (2):

[0106]

[0107] Among them, D O ′ represents the body sound observation signal; z represents the random variable corresponding to the Gaussian distribution function, which can be customized according to application requirements; μ represents the frequency mean; σ 2 represents the frequency variance value; exp represents the exponential function of the natural number base e.

[0108] Further, in some feasible embodiments, in the above step S303: detecting whether the body sound prediction signal is within the signal observation threshold range corresponding to the body sound observation signal, the subsequent signal noise reduction processing method may further include the following implementation steps:

[0109] Step A10: if the body sound prediction signal is not within the signal observation threshold range, determine a plurality of signal observation frequency values ​​of the body sound observation signal at the acquisition time, and determine a total observation frequency value between each of the signal observation frequency values, and a total signal frequency value between each of the signal frequency values;

[0110] Step A20: Calculate the log-likelihood value according to the divisor quotient between the total signal frequency value and the total observation frequency value to obtain the adjustment function of the body sound signal module 10.

[0111] In this embodiment, if the body sound prediction signal is not within the signal observation threshold range corresponding to the body sound observation signal, multiple signal observation frequency values ​​of the body sound observation signal within the preset acquisition time are determined, and the total observation frequency value between all signal observation frequency values ​​and the total signal frequency value between all signal frequency values ​​are further calculated; next, the total signal frequency value is divided by the total observation frequency value, so that the divisor quotient value between the total signal frequency value and the total observation frequency value can be accurately obtained; then, the log-likelihood value of the divisor quotient value is calculated according to the preset transfer function algorithm, so that the adjustment function of the body sound signal module 10 can be accurately obtained.

[0112] It should be noted that the preset transfer function algorithm can be shown as the following formula (3):

[0113] G(w)′=-logl(Z|θ*h)…………Formula (3)

[0114] Among them, G(w)′ is the adjustment function of the body sound signal module 10; θ is a fixed value, that is, a random variable adjusted by the pickup cavity transfer function, which can be customized according to application requirements; h represents the total signal frequency; Z represents the total observation frequency; log l represents the mathematical operation formula for log-likelihood calculation; Z|θ*h represents the divisor quotient obtained by dividing the product of the total signal frequency and the random variable by the total observation frequency.

[0115] Step A30: using the adjustment function as the next pickup chamber transfer function, and returning to execute the step of superimposing the inverse of the noise threshold onto the body sound threshold according to the preset pickup chamber transfer function.

[0116] In this embodiment, the adjustment function is used as the next pickup cavity transfer function, and the step of superimposing the opposite of the noise threshold on the body sound threshold according to the preset pickup cavity transfer function is returned to execute, so that the signal noise reduction processing method has stronger robustness and wide applicability in practical applications.

[0117] Further, in some other feasible embodiments, in the above step S30: determining the real body sound signal according to the body sound target signal and the environmental noise signal, the subsequent signal noise reduction processing method may also include the following implementation steps:

[0118] Step B10: input the real body sound signal into a preset auscultation record model for model training, obtain the auscultation record report of the target user, and display the health results of the auscultation record report to the target user.

[0119] In this embodiment, according to the electrical connection between the active noise reduction audio processing chip and the SOC (System on Chip) main control chip, after the SOC main control chip receives the real body sound signal, the SOC main control chip can Figure 3 The WIFI and Bluetooth chips shown communicate wirelessly with smart terminals (such as mobile phones, computers, and cloud servers of professional medical institutions, etc.) installed with a preset auscultation record model, so that the real body sound signals can be accurately and reliably transmitted to the preset auscultation record model for model training, so that an auscultation record report for the target user can be generated, and the auscultation record report can be uploaded to the SOC main control chip through the smart terminal, and then based on the electrical connection between the SOC main control chip and the LED display screen, the health results of the auscultation record report can be displayed to the target user through the LED display screen.

[0120] In another embodiment, referring to Figure 3Doctors can also connect to in-ear Bluetooth headphones through WIFI and Bluetooth chips, or headphone jacks, to achieve efficient and comfortable on-site auscultation; in addition, Figure 3 The memory shown can be used to store the target user's real body sound signal and auscultation record report, and based on the electrical connection between the SOC main control chip and the memory and the "button / switch / volume / pairing" respectively, through the button control of the "button / switch / volume / pairing", the real body sound signal of the target user can be selected for playback, or the health results of the auscultation record report (i.e. whether there are health problems in the real body sound signal) can be selected to be displayed to the target user through the LED display screen, thereby effectively solving the technical problems of traditional medical stethoscopes such as weak sound, discomfort to wearing, susceptibility to environmental noise interference, limited auscultation results and inability to record and play back in real time.

[0121] It should be noted that, refer to Figure 3 The present application can also power the lithium battery in the electronic stethoscope provided in the present application through the USB charging and data interface, and the lithium battery is used to drive Figure 3 The voltage management chip shown supplies power to the SOC main control chip. In addition, the lithium battery capacity of the present application can be customized according to actual application requirements. For example, the lithium battery capacity can be 500mAh to achieve a working time of more than 10 hours.

[0122] In summary, this application is set up as follows Figure 2 The microphone pickup array shown in the figure collects body sound signals and environmental noise signals respectively, and then processes the body sound signals and environmental noise signals through a low noise amplifier and a bandpass filter. Figure 3 The active noise reduction audio processing chip shown uses the environmental noise signal to cancel the noise part of the body sound signal, and can accurately obtain the real body sound signal; then according to the SOC main control chip, it is respectively Figure 3 The electrical connection of the WIFI and Bluetooth chips, LED display, memory, etc. shown can realize the intelligent listening function, thereby effectively solving the technical problems of traditional medical stethoscopes, such as weak sound, discomfort when wearing, susceptibility to environmental noise interference, limited auscultation results and inability to record and play back in real time.

[0123] In addition, the present application also provides a signal noise reduction processing device, which is applied to a stethoscope including a body sound signal module 10 and an environmental signal module 20, wherein the body sound inlet hole of the body sound signal module 10 is mounted on the sound receiving cavity housing of the stethoscope, and the body sound inlet hole is connected to the sound receiving hole set in the sound receiving cavity housing, and the noise inlet hole of the environmental signal module 20 is set on the sound receiving cavity housing in the reverse direction, please refer to Figure 6 , Figure 6 It is a structural schematic diagram of a signal noise reduction processing device involved in an embodiment of the present application.

[0124] The signal noise reduction processing device of the present application comprises:

[0125] An acquisition module H01 is used to acquire the body sound signal collected by the body sound signal module 10 and the environmental noise signal collected by the environmental signal module 20 after the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space;

[0126] A filtering module H02 is used to perform signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determine a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module 10;

[0127] The real signal determination module H03 is used to determine the real body sound signal according to the body sound target signal and the environmental noise signal.

[0128] Each functional module of the signal noise reduction processing device of the present application implements the steps of the signal noise reduction processing method of the present application as described above during operation.

[0129] In addition, this application also provides a stethoscope device. Figure 7 , Figure 7 Schematic diagram of the structure of the stethoscope device involved in the embodiment of the present application. The stethoscope device in the embodiment of the present application may be a device for locally running the signal noise reduction processing method.

[0130] like Figure 7 As shown, the stethoscope device of the embodiment of the present application may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface).

[0131] The memory 1005 is arranged on the main body of the auscultation device, and a program is stored in the memory 1005, and the program implements the corresponding operation when it is executed by the processor 1001. The memory 1005 is also used to store parameters for use by the auscultation device. The memory 1005 can be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0132] Those skilled in the art will understand that Figure 7The structure of the auscultation device shown in the figure does not constitute a limitation on the auscultation device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0133] like Figure 7 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a signal noise reduction processing program of the stethoscope device.

[0134] exist Figure 7 In the stethoscope device shown, the processor 1001 can be used to call the signal noise reduction processing program of the stethoscope device stored in the memory 1005, and execute the steps of any one of the above-mentioned signal noise reduction processing methods.

[0135] In addition, the present application provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores a signal noise reduction processing program, which implements the steps of the above-mentioned signal noise reduction processing method when executed by a processor.

[0136] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0137] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0138] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions for enabling a stethoscope device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0139] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A signal noise reduction processing method, characterized in that: The signal noise reduction processing method is applied to a stethoscope including a body sound signal module and an environmental signal module, wherein the body sound inlet hole of the body sound signal module is mounted on a sound receiving cavity housing of the stethoscope, the body sound inlet hole is connected to a sound receiving hole provided on the sound receiving cavity housing, and the noise inlet hole of the environmental signal module is provided on the sound receiving cavity housing facing away from the sound receiving cavity; The signal noise reduction processing method comprises: After the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space, obtaining the body sound signal collected by the body sound signal module and the environmental noise signal collected by the environmental signal module; Performing signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determining a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module; A real body sound signal is determined according to the body sound target signal and the environmental noise signal.

2. The signal noise reduction processing method according to claim 1, characterized in that: The body sound signal module includes a first body sound sensor and a second body sound sensor arranged side by side at a preset distance interval, and the step of determining the body sound target signal according to the body sound filter signal and the sound pickup angle of the body sound signal module includes: According to the first sound pickup angle area of ​​the first body sound sensor and the second sound pickup angle area of ​​the second body sound sensor, construct a sound pickup angle of the body sound signal module, and determine a signal collection frequency band of the sound pickup angle; A signal frequency band identical to the signal acquisition frequency band is searched from the overall signal frequency band of the body sound filter signal, and the body sound filter signal corresponding to the signal frequency band identical to the signal acquisition frequency band is used as the body sound target signal.

3. The signal noise reduction processing method according to claim 2, characterized in that: The step of constructing the sound pickup angle of the body sound signal module according to the first sound pickup angle area of ​​the first body sound sensor and the second sound pickup angle area of ​​the second body sound sensor comprises: Determine a first sound pickup angle area of ​​the first body sound sensor and a second sound pickup angle area of ​​the second body sound sensor, and obtain a sound pickup intersection area formed by the first sound pickup angle area and the second sound pickup angle area; Subtracting the minimum sound pickup angle value in the sound pickup intersection area from the maximum sound pickup angle value in the sound pickup intersection area to obtain the sound pickup intersection angle value of the sound pickup intersection area; Taking the middle position between the first body sound sensor and the second body sound sensor as the origin and the sensor central axis passing through the origin as the angle bisector, an angle area with the same value as the sound pickup intersection angle is constructed in the sound receiving cavity as the sound pickup angle of the body sound signal module.

4. The signal noise reduction processing method according to claim 1, characterized in that: The step of determining the real body sound signal according to the body sound target signal and the ambient noise signal comprises: Determining a noise threshold of the ambient noise signal and a body sound threshold of the body sound target signal; According to a preset sound pickup cavity transfer function, the inverse of the noise threshold is superimposed on the body sound threshold to obtain a body sound prediction signal of the body sound signal module; Transforming the body sound prediction signal into a body sound observation signal of the body sound signal module by Gaussian transformation, and detecting whether the body sound prediction signal is within a signal observation threshold range corresponding to the body sound observation signal; If the body sound prediction signal is within the signal observation threshold range, the body sound prediction signal is used as the body sound real signal.

5. The signal noise reduction processing method according to claim 4, characterized in that: The step of Gaussian transforming the body sound prediction signal into the body sound observation signal of the body sound signal module comprises: Determining a plurality of signal frequency values ​​of the body sound prediction signal within a preset collection time; Performing mean processing on each of the signal frequency values ​​to obtain a frequency mean between each of the signal frequency values, and performing variance processing on a square difference between each of the signal frequency values ​​and the frequency mean to obtain a frequency variance value between each of the signal frequency values; Gaussian transformation is performed according to the frequency mean and the frequency variance value to obtain a body sound observation signal of the body sound signal module.

6. The signal noise reduction processing method according to claim 5, characterized in that: After the step of detecting whether the body sound prediction signal is within the signal observation threshold range corresponding to the body sound observation signal, the signal noise reduction processing method includes: If the body sound prediction signal is not within the signal observation threshold range, determining a plurality of signal observation frequency values ​​of the body sound observation signal at the acquisition time, and determining a total observation frequency value between each of the signal observation frequency values, and a total signal frequency value between each of the signal frequency values; Calculating the log-likelihood value according to the divisor quotient between the total signal frequency value and the total observation frequency value to obtain an adjustment function of the body sound signal module; The adjustment function is used as the next pickup cavity transfer function, and the step of superimposing the inverse of the noise threshold onto the body sound threshold according to the preset pickup cavity transfer function is returned to be executed.

7. The signal noise reduction processing method according to claim 1, characterized in that: After the step of determining the real body sound signal according to the body sound target signal and the environmental noise signal, the signal noise reduction processing method further includes: The real body sound signal is input into a preset auscultation record model for model training to obtain an auscultation record report of the target user, and the health results of the auscultation record report are displayed to the target user.

8. A signal noise reduction processing device, characterized in that: The signal noise reduction processing device is applied to a stethoscope including a body sound signal module and an environmental signal module, the body sound inlet hole of the body sound signal module is mounted on a sound receiving cavity housing of the stethoscope, the body sound inlet hole is connected to a sound receiving hole provided on the sound receiving cavity housing, and the noise inlet hole of the environmental signal module is provided on the sound receiving cavity housing in a reverse direction, and the signal noise reduction processing device includes: An acquisition module, used for acquiring the body sound signal collected by the body sound signal module and the environmental noise signal collected by the environmental signal module after the sound receiving cavity of the stethoscope contacts the body surface of the target user to form a closed space; A filtering module, configured to perform signal filtering processing according to the body sound signal to obtain a body sound filter signal, and determine a body sound target signal according to the body sound filter signal and a sound pickup angle of the body sound signal module; The real signal determination module is used to determine the real body sound signal according to the body sound target signal and the environmental noise signal.

9. A stethoscope device, characterized in that: The stethoscope device includes a memory, a processor, and a signal noise reduction processing program stored in the memory and executable on the processor. When the processor executes the signal noise reduction processing program, the steps of the signal noise reduction processing method according to any one of claims 1 to 7 are implemented.

10. A storage medium, the storage medium being a computer-readable storage medium, characterized in that: The computer-readable storage medium stores a signal noise reduction processing program, and when the signal noise reduction processing program is executed by the processor, the steps of the signal noise reduction processing method according to any one of claims 1 to 7 are implemented.

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