An intelligent auxiliary recognition system and method for the critical degree of respiratory signs

Abstract

The present invention discloses an intelligent auxiliary recognition system and method for the critical degree of children's respiratory system signs, belonging to the fields of sound processing and sound recognition. The system includes an intelligent stethoscope for acquiring the cardiopulmonary sounds, respiratory rate, heart rate, body temperature of a child patient, as well as the identity and condition information of the child patient, processing the acquired auscultation data and sending it; a mobile terminal for receiving and uploading the auscultation data sent by the intelligent stethoscope, as well as doctor login, message notification, and display of child patient information; and a server for receiving the auscultation data uploaded by the mobile terminal, performing intelligent recognition and comparison of cardiopulmonary sounds, intelligent recognition of body temperature, respiratory rate, and heart rate, and storing the auscultation data. By adopting the above intelligent auxiliary recognition system and method for the critical degree of children's respiratory system signs, the present invention can collect data on heart rate, respiratory rate, breath sounds, and cardiopulmonary sounds, and can perform early recognition of the critical degree of children's respiratory system signs based on the processed auscultation data, providing a reference for clinical practice.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence auscultation, and in particular to an intelligent auxiliary recognition system and method for the critical degree of children's respiratory system signs. Background Art

[0002] Respiratory diseases are the primary diseases in children, but misdiagnosis and mistreatment are relatively common. Due to reasons such as poor cooperation of children during diagnosis and treatment compared to adults and a wide variety of respiratory diseases, the misdiagnosis rate of children's respiratory diseases is relatively high. In particular, it is difficult to identify early-stage lobar pneumonia and pulmonary consolidation. In the early stage of lobar pneumonia, the range of pulmonary consolidation is small, so symptoms such as cough are not obvious, and there are no characteristic abnormalities such as medium and small bubbling rales during early physical examination auscultation. Misdiagnosis and mistreatment are relatively common.

[0003] Traditional stethoscopes have limitations, and intelligent stethoscopes have emerged as the times require. Although traditional stethoscopes are widely used in clinical practice due to their simple operation and low cost, traditional stethoscopes have problems such as inability to record data, limited sound transmission distance, inability to eliminate external noise, and inability to amplify volume. Moreover, the auscultation method also has certain limitations, such as strong subjectivity, inability to quantify, and being easily affected by factors such as the auscultation timing and the crying of children. At the same time, there is a risk of cross-infection and its application is limited in the diagnosis and treatment of infectious diseases.

[0004] At present, there have been various developments and application researches on electronic stethoscopes, which are of great significance. The application field mainly focuses on heart sounds, and there are few inventions using electronic stethoscopes for lung auscultation to identify pneumonia, and even fewer can achieve intelligent recognition and real-time display of results. The following are the defects of existing intelligent stethoscopes:

[0005] 1) Existing intelligent stethoscopes cannot identify respiratory rate, respiratory sound intensity, and pitch. Most of them only classify the rales of respiratory sounds, but there are no rales in the early stage of lobar pneumonia with pulmonary consolidation, so their application is limited;

[0006] 2) Limited by the sensitivity of the human ear and the experience of physicians, it is still difficult to identify early-stage children's pneumonia at present;

[0007] 3) To reduce unnecessary radioactive examinations (chest DR and CT), the problem to be solved by the present invention is to design an intelligent auxiliary recognition system for early identification of children's pneumonia, especially pulmonary consolidation. Summary of the Invention

[0008] To solve the above problems, the present invention provides an intelligent auxiliary recognition system and method for the critical degree of children's respiratory system signs. By collecting heart rate, respiratory rate, respiratory sounds, and cardiopulmonary sound data, and identifying children's pneumonia based on the processed auscultation data, it provides a reference for clinical practice.

[0009] To achieve the above object, the present invention provides an intelligent auxiliary recognition system for the critical degree of children's respiratory system signs, including

[0010] An intelligent stethoscope, which is used to obtain the cardiopulmonary sounds, respiratory rate, heart rate, body temperature of a child patient, as well as the identity and condition information of the child patient, and processes and sends the auscultation data after obtaining it;

[0011] A mobile terminal, which is used to receive and upload the auscultation data sent by the intelligent stethoscope, as well as doctor login, message notification, and display of child patient information;

[0012] A server, which is used to receive the auscultation data uploaded by the mobile terminal, perform intelligent recognition and comparison of cardiopulmonary sounds, intelligent recognition of body temperature, respiratory rate, and heart rate, and storage of auscultation data;

[0013] The intelligent stethoscope includes:

[0014] A receiver end, which is used for a doctor to auscultate the breathing sounds of a child patient in real time;

[0015] An auscultation end, which is connected to the receiver end, and is used for auscultation data transmission, cardiopulmonary sound collection, separation, and noise reduction, and monitoring of respiratory rate, heart rate, and body temperature.

[0016] Preferably, the auscultation end includes

[0017] A wireless communication module, which is used to implement the communication function between the intelligent stethoscope and the mobile terminal, and transmits the auscultation data and child patient information to the mobile app through 5G / 4G;

[0018] A cardiopulmonary sound collection module, which is used to collect the cardiopulmonary sounds of the auscultation site of a child patient in real time, separate the heart sound and lung sound, and form two different auscultation data for transmission;

[0019] A respiratory rate collection module, which is used to collect the respiratory rate and breathing sounds (breathing sound intensity and pitch) of a child patient in real time, transmits the breathing sound to the receiver end, and transmits the respiratory rate data to the respiratory rate monitoring module;

[0020] A respiratory rate monitoring module, which is used to monitor the respiratory rate collected by the respiratory rate collection module in real time, perform identification and display it on the display screen of the auscultation end in real time (unit: times / minute);

[0021] A heart rate collection module, which is used to collect the heart rate of a child patient in real time, and transmit it to the heart rate monitoring module;

[0022] A heart rate monitoring module, which is used to monitor the heart rate information collected by the heart rate collection module in real time, perform identification and display it on the display screen of the auscultation end in real time (unit: times / minute);

[0023] The blood oxygen saturation monitoring module is used to monitor the patient's blood oxygen saturation in real time and display it on the display screen at the auscultation end;

[0024] The body temperature monitoring module is used to collect and monitor the body temperature of the auscultation site of pediatric patients in real time and transmit the body temperature information.

[0025] Preferably, the cardiopulmonary sound acquisition module includes

[0026] An acquisition unit for collecting and preprocessing the cardiopulmonary sound information of the auscultation site of pediatric patients;

[0027] A separation unit for separating the preprocessed heart sound and lung sound.

[0028] Preferably, the earpiece end is a wireless earphone or a wired earphone or the rubber tube and ear hook of a traditional stethoscope. The rubber tube and ear hook can be connected to the auscultation end of the stethoscope, with the functions of a traditional stethoscope, which is convenient for clinicians to use when the power is insufficient, increasing the practicability; the wired earphone is connected to the 3.5mm headphone jack on the auscultation end through a headphone cable, and the wireless earphone is connected to the auscultation end via Bluetooth; on the auscultation end, there are a recording button for the doctor to record the breath sound, a stop button for the doctor to stop recording the breath sound, and a switching button for switching between the home mode and the doctor mode. The auscultation end is provided with a red light, a yellow light, and a green light.

[0029] Preferably, the mobile terminal includes but is not limited to a mobile phone.

[0030] Preferably, the mobile terminal includes:

[0031] A doctor login module for doctors to log in to the app to query patient information;

[0032] A notification module for reminding doctors that the storage and identification of pediatric patient information are completed;

[0033] A patient information storage module for storing and displaying patient identity information, medical record information, and auscultation information.

[0034] Preferably, the server includes:

[0035] A data receiving module for receiving the cardiopulmonary sound, respiratory rate, heart rate, and body temperature data collected by the auscultation end;

[0036] A cardiopulmonary sound processing module for receiving the auscultation data transmitted by the cardiopulmonary sound acquisition module and performing filtering and noise reduction processing on the heart sound and lung sound;

[0037] A cardiopulmonary sound prediction module for using the Boost training model to predict the heart sound and lung sound data processed by the cardiopulmonary sound processing module, and then calculating the entire heart sound and lung sound respectively by taking the average;

[0038] A cardiopulmonary sound judgment module, which is used to compare the characteristic information of the heart sound and lung sound data predicted and processed by the cardiopulmonary sound prediction module with the pre-stored standard cardiopulmonary sound information, record the comparison data and the cardiopulmonary sound data information, determine whether the received cardiopulmonary sound signal is abnormal, and transmit all the recorded data to the cloud server;

[0039] An identification module, which is used to record, identify the collected respiratory rate, heart rate, and body temperature, and transmit them to the cloud server;

[0040] A cloud server, which is used to store the identity information of pediatric patients, the standard cardiopulmonary sound information data, the cardiopulmonary sound data processed after each auscultation of pediatric patients, the respiratory rate, heart rate, and body temperature data processed after each auscultation of pediatric patients, and the identification results;

[0041] A data transmission module, which wirelessly transmits various information stored in the cloud service to the mobile terminal.

[0042] Preferably, the cardiopulmonary sound processing module includes

[0043] A filtering unit, which is used to perform filtering processing on the separated heart sound and lung sound data according to the filter and its corresponding filtering parameters respectively;

[0044] A noise reduction unit, which is used to perform noise reduction processing on the cardiopulmonary sound data according to the noise reduction parameters and the noise reduction algorithm built into the WebRTC technology, and transmit it to the cardiopulmonary sound prediction module.

[0045] The present invention also provides an identification method for an intelligent auxiliary identification system based on the critical degree of pediatric respiratory system signs, including a home mode identification method and a physician mode identification method. The home mode identification method includes the following steps:

[0046] Step 1: Place the intelligent stethoscope at the symmetrical positions on the front and back chests of a febrile and coughing pediatric patient for auscultation;

[0047] Step 2: The intelligent stethoscope identifies and monitors the body temperature T, heart rate HR, respiratory rate R, and finger pulse oxygen saturation SPO2 of the auscultation site of the pediatric patient;

[0048] Step 3: Determine whether the body temperature, heart rate, respiratory rate, and finger pulse oxygen saturation of the pediatric patient exceed the set values. If they exceed, the mobile terminal will give a notification prompt; if not, proceed to the next step;

[0049] Step 4: Select multiple auscultation sites in sequence, and record the mean and extreme values of their T, HR, and R;

[0050] Step 5: Identify the heart rate corresponding to the maximum value of T as HR1 and the corresponding respiratory rate as R1, and calculate the heart rate and respiratory rate ratio Q1 during fever;

[0051] Step 6: If the body temperature exceeds 38.5°C, the mobile device will automatically prompt: The body temperature is too high. It is recommended to take oral antipyretics. XX mg of ibuprofen suspension, which is XX ml;

[0052] Step 7: 2 hours after the child patient takes the antifebrile, measure the heart rate HR2 and respiratory rate R2 at the same auscultation site, and calculate the ratio Q2 of the heart rate and respiratory rate 2 hours after taking the antifebrile;

[0053] Step 8: Calculate the heart rate and respiratory ratio variability V;

[0054] Step 9: Determine whether the heart rate, respiratory rate, and respiratory ratio variability exceed (or are lower than) the set values, and prompt through the display screen;

[0055] The physician mode recognition method includes the following steps:

[0056] S1: Place the intelligent stethoscope on the upper right, upper left, middle right, middle left, lower right, lower left of the patient's chest and under the right scapula and left scapula of the back in sequence for symmetric auscultation;

[0057] S2: When high-quality breath sounds are auscultated at the above positions, click the "Record" button, record one respiratory cycle, and then click the "End" button;

[0058] S3: The intelligent stethoscope screen will display the body temperature T, breath sound intensity L, respiratory tone Pi, and the patient's respiratory rate R and heart rate HR at the auscultation site in real time;

[0059] S4: The server automatically calculates the differences in breath sound intensity and tone differences at the above symmetric auscultation sites;

[0060] S5: If the difference in sound intensity or tone difference > 10%, the mobile device will prompt that it conforms to the auscultation characteristics of lobar pneumonia (lung consolidation), and it is recommended to further perform imaging examinations. If the difference in sound intensity and tone difference ≤ 10%, the mobile device will prompt that it does not conform to the auscultation characteristics of lobar pneumonia (lung consolidation) temporarily.

[0061] Preferably, in step 3 of the family mode recognition method, if T > 38.5°C and HR > 160 beats / minute and R > 50 breaths / minute or the lowest finger pulse oxygen saturation is lower than 93%, the mobile device will notify and prompt that the vital signs are critical and seek medical attention immediately. Otherwise, proceed to step 4;

[0062] In step 5, Q1 = HR1 / R1;

[0063] In step 7, Q2 = HR2 / R2;

[0064] In step 8, V = |Q1 - Q2| / Q1;

[0065] In Step 9, if V ≤ 10%, the mobile device will prompt that it does not currently meet the auscultation characteristics of pneumonia and requires dynamic observation. For high fever, take oral antipyretics and you can visit the outpatient clinic the next day. The auscultation end is marked with a green light.

[0066] If V > 10%, measure the average sound intensity and pitch of the left and right breath sounds, and calculate the average sound intensity variation rate L’ and the average pitch variation rate Pi’ of the left and right lungs. L’ = |L 左 -L 右 | / L 右 , Pi’ = |Pi 左 -Pi 右 | / Pi 右 ;

[0067] If L’ > 10% or Pi’ > 10%, the mobile device will prompt that it meets the auscultation characteristics of lobar pneumonia (lung consolidation). The auscultation end is warned with a red light. If L’ ≤ 10% or Pi’ ≤ 10%, the mobile device will prompt that it meets the auscultation characteristics of bronchopneumonia and does not currently meet the auscultation characteristics of lobar pneumonia (lung consolidation), and requires immediate medical attention and dynamic observation. The auscultation end is marked with a yellow light.

[0068] The present invention has the following beneficial effects:

[0069] 1. The present invention can realize the real-time display of the patient's respiratory rate, heart rate, sound intensity and pitch of the breath sound at the auscultation site.

[0070] 2. The present invention can realize the separation of heart and lung sounds, avoiding the mutual interference of heart and lung sounds.

[0071] 3. The present invention combines an intelligent stethoscope, which is wirelessly transmitted to the mobile device and then to the cloud server, and the real-time signal analysis results are fed back to the mobile phone. This greatly facilitates clinical applications and helps improve the doctor's recognition rate of early pneumonia and lung consolidation.

[0072] 4. The method adopted by the present invention measures the heart rate, respiratory rate, and breath sounds (including indicators such as sound intensity and pitch) at symmetric parts on both sides of the lungs, and automatically calculates the results such as the heart rate-respiratory rate ratio variation rate, average sound intensity variation rate, and average pitch variation rate. Based on these results, the probability of the patient suffering from pneumonia and lobar pneumonia (lung consolidation) is predicted, providing a reference for clinical practice and a certain basis for prescribing radiological imaging examinations.

[0073] 5. The present invention enables parents to conveniently collect key information about the child in a quiet state and provide it to the doctor at the first time, and will automatically push treatment suggestions according to the child's condition, reducing the incidence of acute conditions such as febrile convulsions and pneumonia complications.

[0074] 6. By modifying relevant parameters, the present invention can also be used for the real-time display of adult body temperature, heart rate, respiratory rate and other signs and the identification of early pneumonia and lung consolidation.

[0075] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Description of the Drawings

[0076] Figure 1 It is a schematic diagram of the system structure of an embodiment of the present invention;

[0077] Figure 2 It is a schematic diagram of the flow of the home mode recognition method according to an embodiment of the present invention;

[0078] Figure 3 It is a schematic diagram of the flow of the physician mode recognition method according to an embodiment of the present invention. Detailed Embodiments

[0079] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout.

[0080] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0081] Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0082] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the present invention is usually placed during use. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0083] In the description of the present invention, it should also be noted that unless otherwise clearly specified and defined, the terms "set", "installed", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0084] As Figure 1 shown, an intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to the present invention includes an intelligent stethoscope, a mobile terminal, and a server, and all three are wirelessly connected. The intelligent stethoscope is used to obtain the heart and lung sounds, respiratory rate, heart rate, body temperature of a child patient, as well as the identity and condition information of the child patient, and after obtaining the auscultation data, it is processed and sent. The mobile terminal is used to receive and upload the auscultation data sent by the intelligent stethoscope, as well as doctor login, message notification, and display of child patient information. The server is used to receive the auscultation data uploaded by the mobile terminal, perform intelligent recognition and comparison of heart and lung sounds, intelligent recognition of body temperature, respiratory rate, and heart rate, and storage of auscultation data.

[0085] The intelligent stethoscope includes a receiver end and an auscultation end. The receiver end is placed on the doctor's ear, and the auscultation end is placed on the auscultation site of the child patient. The receiver end is used for the doctor to auscultate the breathing sounds of the child patient in real time. The receiver end is a wireless earphone or a wired earphone or the rubber tube and ear hook of a traditional stethoscope. The rubber tube and ear hook can be connected to the auscultation end of the stethoscope, and have the functions of a traditional stethoscope, which is convenient for clinical doctors to use when the battery is low, increasing the practicability. The wired earphone is connected to the 3.5mm headphone jack on the auscultation end through a headphone connection line, and the wireless earphone is connected to the auscultation end through Bluetooth. On the auscultation end, there are a recording button for the doctor to record the breathing sounds, a stop button for the doctor to stop recording the breathing sounds, and a switching button for switching between the home mode and the doctor mode. The auscultation end is provided with a red light, a yellow light, and a green light.

[0086] The stethoscope end, connected to the earphone end, is used for auscultation data transmission, cardiopulmonary sound collection, separation and noise reduction, and respiration rate, heart rate, and body temperature monitoring. The stethoscope end includes a wireless communication module for realizing the communication function between the intelligent stethoscope and the mobile terminal, and transmitting auscultation data and pediatric patient information to the mobile app through 5G / 4G; a cardiopulmonary sound collection module for collecting the cardiopulmonary sounds at the auscultation site of pediatric patients in real time, separating the heart sounds and lung sounds, and transmitting the two different auscultation data; a respiration rate collection module for collecting the respiration rate and respiration sounds (respiration sound intensity and pitch) of pediatric patients in real time, transmitting the respiration sounds to the earphone end, and transmitting the respiration rate data to the respiration rate monitoring module; a respiration rate monitoring module for monitoring the respiration rate collected by the respiration rate collection module in real time, identifying it, and displaying it on the display screen of the stethoscope end in real time (unit: times / minute); a heart rate collection module for collecting the heart rate of pediatric patients in real time and transmitting it to the heart rate monitoring module; a heart rate monitoring module for monitoring the heart rate information collected by the heart rate collection module in real time, identifying it, and displaying it on the display screen of the stethoscope end in real time (unit: times / minute); a blood oxygen saturation monitoring module for monitoring the blood oxygen saturation of the patient in real time (finger pulse oxygen saturation can be monitored) and displaying it on the display screen of the stethoscope end; a body temperature monitoring module for collecting and monitoring the body temperature at the auscultation site of pediatric patients in real time and transmitting the body temperature information. The cardiopulmonary sound collection module includes a collection unit for collecting and preprocessing the cardiopulmonary sound information at the auscultation site of pediatric patients; a separation unit for separating the preprocessed heart sounds and lung sounds.

[0087] The mobile terminal includes, but is not limited to, a mobile phone. The mobile terminal includes: a doctor login module for doctors to log in to the app to query patient information; a notification module for reminding doctors that pediatric patient information storage and identification are completed; a patient information storage module for storing and displaying patient identity information, medical record information, and auscultation information.

[0088] The server includes: a data receiving module for receiving cardiopulmonary sound, respiratory rate, heart rate, and body temperature data collected by the auscultation end; a cardiopulmonary sound processing module for receiving the auscultation data transmitted by the cardiopulmonary sound acquisition module and performing filtering and noise reduction processing on heart sounds and lung sounds; a cardiopulmonary sound prediction module for using the Boost training model to predict the heart sound and lung sound data processed by the cardiopulmonary sound processing module, and then calculating the entire heart sound and lung sound respectively by taking the average; a cardiopulmonary sound judgment module for comparing the heart sound and lung sound data after prediction processing by the cardiopulmonary sound prediction module with the pre-stored standard cardiopulmonary sound information for feature information comparison, recording the comparison data and the cardiopulmonary sound data information, determining whether the received cardiopulmonary sound signal is abnormal, and transmitting all the recorded data to the cloud server; an identification module for recording, identifying the collected respiratory rate, heart rate, and body temperature, and transmitting them to the cloud server; a cloud server for storing the identity information of child patients, the standard cardiopulmonary sound information data, the cardiopulmonary sound data processed after each auscultation of child patients, the respiratory rate, heart rate, body temperature data processed after each auscultation of child patients, and the identification results; a data transmission module for wirelessly transmitting various information stored in the cloud service to the mobile terminal. The cardiopulmonary sound processing module includes a filtering unit for filtering the separated heart sound and lung sound data respectively according to the filter and its corresponding filtering parameters; a noise reduction unit for performing noise reduction processing on the cardiopulmonary sound data according to the noise reduction parameters and the built-in noise reduction algorithm of the WebRTC technology, and transmitting it to the cardiopulmonary sound prediction module.

[0089] The recognition method of an intelligent auxiliary recognition system based on the critical degree of children's respiratory system signs described in the present invention includes a family mode recognition method and a doctor mode recognition method, as Figure 2 shown. The family mode recognition method includes the following steps:

[0090] Step 1, place the intelligent stethoscope at the symmetrical positions on the front and back chests of the fever and cough patient for auscultation;

[0091] Step 2, the intelligent stethoscope recognizes and monitors the body temperature T, heart rate HR, respiratory rate R, and finger pulse oxygen saturation SPO2 of the auscultation site of the child patient;

[0092] Step 3, determine whether the body temperature, heart rate, respiratory rate, and finger pulse oxygen saturation of the child patient exceed the set values. If T > 38.5°C and HR > 160 beats / minute and R > 50 times / minute or the lowest finger pulse oxygen saturation is lower than 93%, the mobile terminal notifies that the vital signs are critical and seek immediate medical attention. Otherwise, proceed to Step 4;

[0093] Step 4, sequentially select multiple auscultation sites and record the mean and extreme values of their T, HR, and R;

[0094] Step 5: Identify the heart rate corresponding to the maximum T as HR1 and the corresponding respiratory rate as R1, and calculate the ratio Q1 of the heart rate to the respiratory rate during fever, Q1 = HR1 / R1;

[0095] Step 6: If the body temperature exceeds 38.5°C, the mobile terminal will automatically prompt according to the patient's age and weight: The body temperature is too high. It is recommended to take oral antipyretics. XX mg of ibuprofen suspension is XX ml;

[0096] Step 7: 2 hours after the patient takes the antipyretics, measure the heart rate as HR2 and the respiratory rate as R2 at the same auscultation site, and calculate the ratio Q2 of the heart rate to the respiratory rate 2 hours after taking the antipyretics, Q2 = HR2 / R2;

[0097] Step 8: Calculate the heart rate and respiratory ratio variability V, V = |Q1 - Q2| / Q1;

[0098] Step 9: Determine whether the heart rate, respiratory rate, and respiratory ratio variability exceed (or are lower than) the set values. If V ≤ 10%, the mobile terminal prompts that it does not currently meet the auscultation characteristics of pneumonia and needs to be dynamically observed. For high fever, take oral antipyretics and you can visit the outpatient clinic the next day. The auscultation end is marked with a green light;

[0099] If V > 10%, the mobile terminal notifies that it may be pneumonia. Under guidance, further measure the sound intensity and pitch of the breath sounds in both lungs, measure the average sound intensity and pitch of the left and right breath sounds, and calculate the average sound intensity variability L’ and the average pitch variability Pi’ of the left and right lungs, L’ = |L 左 -L 右 | / L 右 ,Pi’ = |Pi 左 -Pi 右 | / Pi 右 ;

[0100] If L’ > 10% or Pi’ > 10%, the mobile terminal prompts that it meets the auscultation characteristics of lobar pneumonia (lung consolidation), and the auscultation end is warned with a red light. If L’ ≤ 10% or Pi’ ≤ 10%, the mobile terminal prompts that it meets the auscultation characteristics of bronchopneumonia and does not currently meet the auscultation characteristics of lobar pneumonia (lung consolidation), and needs to seek medical attention in time and be dynamically observed. The auscultation end is marked with a yellow light.

[0101] Click the switch button to switch to the doctor mode. As Figure 3 shown, the doctor mode recognition method includes the following steps:

[0102] S1: Place the intelligent stethoscope on the patient's front upper right, upper left, middle right, middle left, lower right, lower left, and right subscapular and left subscapular areas of the back in sequence for symmetric auscultation;

[0103] S2. When high-quality breath sounds are auscultated at the above-mentioned locations, click the "Record" button, and after recording one respiratory cycle, click the "End" button;

[0104] S3. The intelligent stethoscope screen real-time displays the body temperature T (unit: degree Celsius °C), breath sound intensity L (unit: decibel dB), breath sound pitch Pi (unit: hertz Hz) of the auscultation location, as well as the patient's respiratory rate R (unit: times per minute) and heart rate HR (unit: times per minute);

[0105] S4. The server automatically calculates the difference in breath sound intensity and the difference in pitch between the above-mentioned symmetric auscultation locations;

[0106] S5. If the difference in sound intensity or the difference in pitch > 10%, the mobile terminal prompts that it conforms to the auscultation characteristics of lobar pneumonia (lung consolidation), and it is recommended to further perform imaging examinations. If the difference in sound intensity and the difference in pitch ≤ 10%, the mobile terminal prompts that it does not conform to the auscultation characteristics of lobar pneumonia for the time being.

[0107] Through the server, the cardiopulmonary sound data collected and processed are combined with the results obtained by the cardiopulmonary sound judgment module of the present invention. By real-time displaying auscultation data such as body temperature, heart rate, respiratory rate, breath sound intensity, and pitch, and based on the processed auscultation data, it provides auxiliary identification of children's lung consolidation and medical advice, providing a reference for clinical practice. It centrally displays vital sign data such as body temperature, respiration, and heart rate, and quantifies the breath sound characteristics, providing convenience for clinical practice.

[0108] Therefore, the present invention adopts the above-mentioned intelligent auxiliary identification system and its identification method for children's pneumonia with lung consolidation. By collecting heart rate, respiratory rate, breath sounds, and cardiopulmonary sound data, and based on the processed auscultation data, it identifies pneumonia in children patients, providing a reference for clinical practice.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent auxiliary recognition system for the critical level of children's respiratory system signs, characterized in that: including An intelligent stethoscope, which is used to obtain the cardiopulmonary sounds, respiratory rate, heart rate, body temperature of a child patient, as well as the identity and condition information of the child patient, and processes and sends the auscultation data after obtaining it; A mobile terminal, which is used to receive and upload the auscultation data sent by the intelligent stethoscope, as well as doctor login, message notification, and display of child patient information; A server, which is used to receive the auscultation data uploaded by the mobile terminal, perform intelligent identification and comparison of cardiopulmonary sounds, intelligent identification of body temperature, respiratory rate, and heart rate, and storage of auscultation data; The intelligent auxiliary identification system for the critical degree of the child's respiratory system signs has a family mode and a doctor mode. When the family mode is adopted, the server judges whether the body temperature, heart rate, respiratory rate, and finger pulse oxygen saturation of the child patient exceed the set values. If T>38.5°C and HR>160 beats per minute and R>50 times per minute, exceeding the set values, the mobile terminal notifies and prompts. If not, the intelligent stethoscope auscultates multiple auscultation sites of the child. The server records the mean and extreme values of its T, HR, and R, identifies the heart rate corresponding to the maximum value of T as HR1 and the corresponding respiratory rate as R1, and calculates the heart rate and respiratory rate ratio Q1 at this time, Q1 = HR1 / R1; The intelligent stethoscope records the heart rate as HR2 and the respiratory rate as R2 at the stethoscope site 2 hours after the fever subsides, and calculates the heart rate and respiratory rate ratio Q2, where Q2 = HR2 / R2; calculates the heart rate and respiratory ratio variability V, where V = |Q1 - Q2| / Q1; determines whether the heart rate and respiratory ratio variability exceeds the standard value. If V ≤ 10%, the stethoscope end is marked with a green light; if V > 10%, the intelligent stethoscope measures the sound intensity and pitch of the breath sounds in both lungs, measures the average sound intensity and pitch of the left and right breath sounds, and the server calculates the average sound intensity variability L’ and the average pitch variability Pi’ of the left and right lungs, where L’ = |L 左 -L 右 | / L 右 , Pi’ = |Pi 左 -Pi 右 | / Pi 右 ; if L’ > 10% or Pi’ > 10%, the intelligent stethoscope gives a red light warning, and if L’ ≤ 10% or Pi’ ≤ 10%, the intelligent stethoscope is marked with a yellow light; When the doctor mode is adopted, the intelligent stethoscope auscultates the breath sounds at the auscultation sites of the child. The intelligent stethoscope displays the body temperature T, breath sound intensity L, breath sound pitch Pi, respiratory rate R, and heart rate HR of the auscultation site in real time. The server automatically calculates the difference in breath sound intensity and the difference in pitch at the auscultation site. If the difference in sound intensity or the difference in pitch > 10%, the intelligent stethoscope issues an inspection prompt.

2. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 1, characterized in that: The intelligent stethoscope includes: A receiver end, which is used for a doctor to auscultate the breath sounds of a child patient in real time; An auscultation end, which is connected to the receiver end and is used for auscultation data transmission, cardiopulmonary sound collection, separation, and noise reduction, and monitoring of respiratory rate, heart rate, and body temperature.

3. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 2, characterized in that: The auscultation end includes A wireless communication module, which is used to realize the communication function between the intelligent stethoscope and the mobile terminal, and transmits the auscultation data and child patient information to the mobile app through 5G / 4G; A cardiopulmonary sound collection module, which is used to collect the cardiopulmonary sounds at the auscultation sites of a child patient in real time, separate the heart sounds and lung sounds, and form two different auscultation data for transmission; A respiratory rate collection module, which is used to collect the respiratory rate and breath sounds of a child patient in real time. The breath sounds are transmitted to the receiver end, and the respiratory rate data is transmitted to the respiratory rate monitoring module; A respiratory rate monitoring module, which is used to monitor the respiratory rate collected by the respiratory rate collection module in real time, identify it, and display it on the display screen of the auscultation end in real time; A heart rate collection module, which is used to collect the heart rate of a child patient in real time and transmit it to the heart rate monitoring module; A heart rate monitoring module, which is used to monitor the heart rate information collected by the heart rate collection module in real time, identify it, and display it on the display screen of the auscultation end in real time; An oxygen saturation monitoring module, which is used to monitor the oxygen saturation of the patient in real time and display it on the display screen of the auscultation end; A body temperature monitoring module, which is used to collect and monitor the body temperature at the auscultation sites of a child patient in real time and transmit the body temperature information.

4. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 3, characterized in that: The cardiopulmonary sound collection module includes A collection unit, which is used for the collection and preprocessing of cardiopulmonary sound information at the auscultation sites of a child patient; Separation unit, used for separating preprocessed heart sounds and lung sounds.

5. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 2, wherein: The receiver end is a wireless earphone or a wired earphone or the rubber tube and ear hook of a traditional stethoscope. The rubber tube and ear hook are connected to the auscultation end. The wired earphone is connected to the 3.5mm headphone jack on the auscultation end through a headphone connecting wire, and the wireless earphone is connected to the auscultation end via Bluetooth. On the auscultation end, there are a recording button for the doctor to record breathing sounds, a stop button for the doctor to stop recording breathing sounds, and a switching button for switching between the home mode and the doctor mode. The auscultation end is provided with a red light, a yellow light, and a green light.

6. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 4, wherein: The mobile terminal includes: Doctor login module, used for doctors to log in to the app to query patient information; Notification module, used to remind doctors that the storage and identification of pediatric patient information are completed; Patient information storage module, used for storing and displaying patient identity information, medical record information, and auscultation information.

7. The intelligent auxiliary recognition system for the critical degree of children's respiratory system signs according to claim 6, characterized in that: The server includes: Data receiving module, used for receiving cardiopulmonary sound, respiratory rate, heart rate, and body temperature data collected by the auscultation end; Cardiopulmonary sound processing module, used for receiving the auscultation data transmitted by the cardiopulmonary sound acquisition module and performing filtering and noise reduction processing on heart sounds and lung sounds; Cardiopulmonary sound prediction module, used for using the Boost training model to predict the heart sound and lung sound data processed by the cardiopulmonary sound processing module, and then calculating the entire heart sound and lung sound respectively by taking the average; Cardiopulmonary sound judgment module, used for comparing the heart sound and lung sound data predicted and processed by the cardiopulmonary sound prediction module with the pre-stored standard cardiopulmonary sound information for feature information comparison, recording the comparison data and the cardiopulmonary sound data information, determining whether the received cardiopulmonary sound signal is abnormal, and transmitting all the recorded data to the cloud server; Identification module, used for recording, identifying the collected respiratory rate, heart rate, and body temperature, and transmitting them to the cloud server; Cloud server, used for storing pediatric patient identity information, standard cardiopulmonary sound information data, cardiopulmonary sound data processed after each auscultation of pediatric patients, respiratory rate, heart rate, body temperature data processed after each auscultation of pediatric patients, and identification results; Data transmission module, wirelessly transmitting various information stored in the cloud service to the mobile terminal.

8. An intelligent auxiliary recognition system for the critical level of children's respiratory system signs according to claim 7, characterized in that: The cardiopulmonary sound processing module includes Filtering unit, used for filtering the separated heart sound and lung sound data according to the filter and its corresponding filtering parameters respectively; Noise reduction unit, used for performing noise reduction processing on the cardiopulmonary sound data according to the noise reduction parameters and the noise reduction algorithm built into the WebRTC technology, and transmitting it to the cardiopulmonary sound prediction module.

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