CN111374694A - Lung function monitoring system, monitoring method and electronic device thereof - Google Patents
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Abstract
The invention discloses a lung function monitoring system, a lung function monitoring method and an electronic device thereof. The invention overcomes the problem that the specific position of the lung lesion can not be determined by the method for monitoring the integral function status of the lung in the prior art, can position the lung lesion part to the specific lung lobe, provides more accurate detection results for clinical diagnosis and treatment, and improves the diagnosis and treatment level of the lung disease.
Description
Technical Field
The present invention relates to human body vital sign monitoring technologies, and in particular, to a pulmonary function monitoring system, a pulmonary function monitoring method, and an electronic device thereof.
Background
The heart and lung function reflects the ability of the heart of human body to pump blood and the lung to suck oxygen, and directly influences the activities of organs and muscles of the whole body, which is very important. If the cardiopulmonary function of the human body is good, the main functions of the human body can be reflected to be operated healthily, so that the possibility that the human body suffers from chronic diseases such as cardiovascular diseases, endocrine system diseases and respiratory system diseases can be inferred to be low. The dysfunction of heart and lung causes the heart to contract powerless, the vital capacity is reduced, the functions of the cardiovascular system and the respiratory system are reduced, and the body blood supply is insufficient, the fatigue is easy, the chest distress, the shortness of breath, the nervousness, the irritability, the emotional instability, the disease resistance is reduced, etc. Therefore, monitoring of cardiopulmonary function is particularly important.
The existing lung function monitoring technology mainly focuses on monitoring the whole lung function condition. However, the lung includes a left lung and a right lung, the left lung includes an upper lung lobe and a lower lung lobe, the right lung includes an upper lung lobe, a middle lung lobe and a lower lung lobe, and when the lung function is affected, the lesion usually occurs only in a local position, so that the specific position of the lung lesion cannot be determined by monitoring the whole functional status of the lung.
Disclosure of Invention
Technical problem to be solved
The invention mainly aims to provide a lung function monitoring system, a lung function monitoring method and an electronic device thereof, so as to solve the problem that the specific position of lung lesion cannot be determined by monitoring the whole lung function state by the existing lung function monitoring technology.
(II) technical scheme
The invention is realized by the following technical scheme:
a lung function monitoring system is used for monitoring lung functions and comprises a lung sound wave detection device and a calculation device, wherein the lung sound wave detection device comprises a plurality of sound wave detection devices, the sound wave detection devices correspond to lung lobes of a lung one by one, and the sound wave detection devices are used for detecting sound wave signals at the lung lobes corresponding to the sound wave detection devices and sending the detected sound wave signals to the calculation device;
the computing device is configured to separate lung lobe breathing sound wave signals, heart beating sound wave signals and background noise sound wave signals in the received sound wave signals through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judge the function condition of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal.
Further, the determining the functional status of each lung lobe according to the waveform of the separated respiratory acoustic wave signal of each lung lobe includes:
and comparing the waveform of each separated lung lobe respiration sound wave signal with the waveform of a preset normal lung lobe respiration sound wave signal, and judging whether the function of each lung lobe is abnormal or not according to a comparison result.
Further, the determining the functional status of each lung lobe according to the waveform of the separated respiratory acoustic wave signal of each lung lobe further includes:
comparing the waveform of the respiratory sound wave signal of the lung lobe with abnormal function with the preset waveforms of the respiratory sound wave signals of different lung lobes, and determining the abnormal lung lobe respiratory sound wave signal with the highest similarity between the waveform and the respiratory sound wave signal of the lung lobe with abnormal function according to the comparison result;
and according to the corresponding relation between the pre-stored abnormal lung lobe breathing sound wave signal and the abnormal type of the lung lobe, taking the abnormal type of the lung lobe corresponding to the abnormal lung lobe breathing sound wave signal with the highest similarity between the waveform and the breathing sound wave signal of the lung lobe with the abnormal function as the abnormal type of the lung lobe with the abnormal function.
Furthermore, the lung lobe position is a lobe bronchus position of the lung lobe, and the lung lobe respiratory sound wave signal is a lobe bronchus respiratory sound wave signal of the lung lobe.
Further, the determining the functional status of each lung lobe according to the waveform of the separated respiratory acoustic wave signal of each lung lobe further includes:
detecting alveolar respiration sound wave interference signals in the separated leaf bronchus respiration sound wave signals of each lung lobe, and judging the alveolar function condition of each lung lobe according to the waveform characteristics of the alveolar respiration sound wave interference signals.
Furthermore, each sound wave detection device comprises two sound wave sensors, and each lung lobe breathing sound wave signal is a lung lobe breathing sound wave signal with high intensity separated from the sound wave signals detected by the two sound wave sensors in the sound wave detection device corresponding to each lung lobe.
Further, the computing means is further configured to determine the heart function status from the waveform of the heart beating sound wave signal having the greatest intensity separated from the sound wave signals at the inferior and superior left lung lobes of the lung.
Further, the plurality of sound wave detection devices are mounted on the flexible patch, the position relationship among the sound wave detection devices is consistent with the position relationship among the lobar bronchi of each pulmonary lobe of the lung, and when the flexible patch is attached to the proper position of the back or the chest of the human body, the sound wave detection devices correspond to the lobar bronchi of each pulmonary lobe of the lung of the human body one to one.
A lung function monitoring method is applied to a computing device in a lung function monitoring system, the lung function monitoring system comprises a lung sound wave detection device and a computing device, the lung sound wave detection device comprises a plurality of sound wave detection devices, the sound wave detection devices are in one-to-one correspondence with lung lobes of a lung, and the sound wave detection devices are used for detecting sound wave signals at the positions of the lung lobes corresponding to the sound wave detection devices and sending the detected sound wave signals to the computing device;
the method comprises the steps of separating lung lobe breathing sound wave signals, heart beating sound wave signals and background noise sound wave signals in the received sound wave signals through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judging the functional status of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal.
An electronic device comprising a processor and a memory, the memory having stored therein a computer program which, when executed by the processor, implements a lung function monitoring method as described above.
(III) advantageous effects
Compared with the prior art, the invention has the advantages that the plurality of sound wave detection devices are arranged to respectively detect the sound wave signals at the lung lobes, the sound wave signals are subjected to signal separation based on the great difference of the respiratory frequency range, the heartbeat frequency range and the background noise frequency range to obtain the respiratory sound wave signals of the lung lobes, and finally the functional conditions of the lung lobes are judged according to the waveforms of the respiratory sound wave signals of the lung lobes. The invention overcomes the problem that the specific position of the lung lesion can not be determined by the method for monitoring the integral function status of the lung in the prior art, can position the lung lesion part to the specific lung lobe, provides more accurate detection results for clinical diagnosis and treatment, and improves the diagnosis and treatment level of the lung disease.
Drawings
Fig. 1 is a schematic diagram illustrating the components and operation of a lung function monitoring system according to an embodiment of the present invention;
fig. 2 is a schematic diagram of the components and operation principle of a lung function monitoring system according to another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the following embodiments and the accompanying drawings.
The lung function monitoring system provided by the embodiment of the invention is mainly used for monitoring the lung function. The lung function monitoring system comprises a lung sound wave detection device 1 and a calculation device 2, wherein the lung sound wave detection device 1 is mainly used for detecting sound wave signals of lung lobes, and the calculation device 2 is mainly used for analyzing the sound wave signals of the lung lobes to judge the function status of the lung lobes so as to position a diseased region to a specific lung lobe when the lung has a disease.
Specifically, the lung sound wave detection device 1 includes a plurality of sound wave detection devices 1, the sound wave detection devices 1 are in one-to-one correspondence with the lung lobes of the lungs, and each sound wave detection device 1 detects a sound wave signal at its corresponding lung lobe and transmits the detected sound wave signal to the calculation device 2. The computing device 2 is configured to separate the lung lobe breathing sound wave signal, the heart beating sound wave signal and the background noise sound wave signal in each received sound wave signal through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judge the function condition of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal. In the present invention, in order to locate a lesion site to a specific lobe when a lung has a lesion, at least five sound wave detection devices 1 should be provided, as shown in fig. 1, the five sound wave detection devices 1 respectively correspond to a left superior lung lobe 6, a left inferior lung lobe 7, a right superior lung lobe 3, a right middle lung lobe 4 and a right inferior lung lobe 5 of the lung to detect a sound wave signal at each of the lobes. Since the lungs are close to the heart, the sound wave signals at the lung lobes include lung lobe breathing sound wave signals, heart beating sound wave signals, and other noise, such as sound wave signals caused by the flow of blood, body fluid, etc., sound wave signals caused by the peristalsis of other organs, sound wave signals caused by environmental noise, etc., which are different from the lung lobe breathing sound wave signals and the heart beating sound wave signals, and are collectively referred to as background noise sound wave signals. Because the ranges of the normal breathing frequency, the heartbeat frequency and the background noise frequency have great contrast, for example, the normal breathing frequency is generally 16 to 20 times per minute, the heartbeat frequency is 60 to 100 times per minute, the background noise frequency is higher, and the three are not overlapped under normal conditions, the lung lobe breathing sound wave signals, the heart beating sound wave signals and the background noise sound wave signals at the lung lobes can be separated from each other by performing frequency analysis on the sound wave signals at the lung lobes, so that the lung lobe breathing sound wave signals are obtained.
In the normal condition, when the lung breathes, each lung lobe breathes synchronously, and the breathing sound wave signals of each lung lobe are consistent, and the waveform accords with a certain characteristic rule, and the waveform characteristics of the breathing sound wave signals of the normal lung lobes are obtained in long-term medical research. Therefore, the normal lung lobe respiration sound wave signal may be preset, and at this time, the determining of the function status of each lung lobe according to the waveform of each separated lung lobe respiration sound wave signal may specifically include comparing the waveform of each separated lung lobe respiration sound wave signal with the waveform of the preset normal lung lobe respiration sound wave signal, and determining whether or not each lung lobe function is abnormal according to the comparison result. The specific judgment principle may be that the similarity between the waveform of each lung lobe breathing sound wave signal and the waveform of a preset normal lung lobe breathing sound wave signal is judged through waveform comparison, and for any lung lobe breathing sound wave signal, if the waveform similarity between the waveform of the lung lobe breathing sound wave signal and the waveform of the preset normal lung lobe breathing sound wave signal reaches a preset value (for example, 95%), it indicates that the lung lobe breathing sound wave signal is normal, the lung lobe function is normal, otherwise, it indicates that the lung lobe function is abnormal. The invention overcomes the problem that the specific position of the lung lesion can not be determined by the method for monitoring the integral function status of the lung in the prior art, can position the lung lesion part to the specific lung lobe, provides more accurate detection results for clinical diagnosis and treatment, and improves the diagnosis and treatment level of the lung disease.
Different types of lung abnormalities can be represented as lung sound waves with different characteristics, for each lung lobe of the lung, when a certain type of abnormality occurs to the lung lobe, the breathing sound wave of the lung lobe also has waveform characteristics corresponding to the type of abnormality, and different types of abnormalities can be represented as lung lobe breathing sound waves with different waveform characteristics. Therefore, when it is determined that there is abnormality in the lung function, it is necessary to further determine the type of abnormality. Therefore, the correspondence relationship between the abnormal lung lobe breathing sound wave signal and the lung lobe abnormality type, that is, what kind of abnormal lung lobe breathing sound wave signal corresponds to what kind of lung lobe abnormality type may be set in advance. On the basis, the method for judging the function status of each lung lobe according to the waveform of the separated lung lobe respiration sound wave signal may further include:
and comparing the waveform of the respiratory sound wave signal of the lung lobe with abnormal function with the preset waveforms of the respiratory sound wave signals of different lung lobes, and determining the abnormal lung lobe respiratory sound wave signal with the highest similarity between the waveform and the respiratory sound wave signal of the lung lobe with abnormal function according to the comparison result. And then according to the corresponding relation between the pre-stored abnormal lung lobe breathing sound wave signal and the abnormal lung lobe type, taking the abnormal lung lobe type corresponding to the abnormal lung lobe breathing sound wave signal with the highest similarity between the waveform and the breathing sound wave signal of the lung lobe with the abnormal function as the abnormal type of the lung lobe with the abnormal function. Therefore, whether each lung lobe function is normal or not can be judged, and the abnormal type can be further judged when the abnormal function of the lung lobes is detected. Of course, the calculation device 2 may list the probability that the lung lobe with the abnormal function is of the abnormal type according to the specific similarity between the respiratory sound wave signal of the lung lobe with the abnormal function and the respiratory sound wave signal of each abnormal lung lobe, and the higher the similarity with the respiratory sound wave signal of a certain abnormal lung lobe is, the higher the probability that the lung lobe with the abnormal function is of the abnormal type corresponding to the respiratory sound wave signal of the abnormal lung lobe is.
When each lung lobe breathes, gas exchange is carried out through the lobe bronchus, and the function condition of the lung lobe directly influences the waveform characteristic of the sound wave signal at the lobe bronchus, so the waveform characteristic of the sound wave signal at the lobe bronchus can reflect the main function condition of the lung lobe. Accordingly, the sound wave detection device 1 can detect a sound wave signal at the lobar bronchus of the lung lobe, and at this time, the lung lobe is located at the lobar bronchus of the lung lobe, and the lung lobe breathing sound wave signal is a lobar bronchus breathing sound wave signal of the lung lobe.
When the lung lobes breathe, the lung lobes can simultaneously generate alveolar respiration sound waves, the alveolar respiration sound waves can cause waveform interference on the lobe bronchial respiration sound wave signals of the lung lobes, when the alveoli are abnormal, the waveform characteristics of the alveolar respiration sound waves are changed, and the waveform interference caused by the lobe bronchial respiration sound wave signals of the lung lobes is also changed, so that the alveolar function condition can be judged by detecting the alveolar respiration sound wave interference signals in the lobe bronchial respiration sound wave signals of the lung lobes. Namely, the determining the functional status of each lung lobe according to the waveform of the separated respiratory acoustic wave signal of each lung lobe may further include: detecting alveolar respiration sound wave interference signals in the separated leaf bronchus respiration sound wave signals of each lung lobe, and judging the alveolar function condition of each lung lobe according to the waveform characteristics of the alveolar respiration sound wave interference signals.
As shown in fig. 2, each of the sound wave detection devices 1 may include two sound wave sensors 8, and each of the lung lobe breathing sound wave signals is a lung lobe breathing sound wave signal having a large intensity separated from the sound wave signals detected by the two sound wave sensors 8 in the sound wave detection device 1 corresponding to each of the lung lobes. By providing each sound wave detecting device 1 including two sound wave sensors 8 instead of one, it is possible to more accurately detect each lung lobe breathing sound wave signal. Compared with the existing monitoring means used clinically, the sound wave sensor 8 can obtain more sensitive monitoring performance, and the fine sound waves of the lung can be monitored, so that the functional status of the lung can be monitored more accurately.
The system can realize the monitoring of the following signals:
1. bronchial respiratory sounds
The sound produced by turbulence in the glottis, trachea or main trachea for the flow of breathing gas is the same as the "ha" sound produced by lifting the tongue up for oral exhalation. Bronchial respiration is high in tone and strong in sound. Compared with inspiration and expiration, the expiration sound is stronger than the inspiration sound, the tone is higher and the time is longer. Normal persons can hear bronchial respiratory sounds in the throat, suprasternal fossa, 6 th and 7 th cervical vertebrae and in the vicinity of 1 st and 2 nd thoracic vertebrae of the back.
2. Alveolar breath sound
Resulting from the flow of respiratory gases in and out of the bronchioles and alveoli. When breathing in, air flows through the bronchus and enters the alveoli, so that the alveoli are changed from slack to tense, and when breathing out, the alveoli are changed from tense to slack. The alveolar breath sound is similar to the fu sound generated when the upper teeth bite the lower lip to inhale, is soft and blowing-like, and has low tone and weak sound. Compared with inhalation and exhalation, the inhalation sound is stronger than the exhalation sound, higher in tone and longer in time. The respiratory sounds of the lung alveoli are heard in the chest of normal people except the respiratory sounds of the bronchus and the respiratory sounds of the lung alveoli.
3. Low-level conditioning
Also known as snore sound. The pitch is low, and the pitch frequency is about 100-200 Hz, such as snore in sleep, which mostly occurs in the trachea or main bronchus.
4. Coarse wetting
Also known as big water bubble sound. It occurs in the trachea, main bronchi or cavities, and is mostly seen in the early stages of inspiration. It is seen in bronchiectasis, severe pulmonary edema, and pulmonary tuberculosis or lung abscess cavity. Unconscious or dying patients can hear the airway secretion due to their inability to discharge the airway secretion.
5. Middle-wet
It is also called as middle-water bubble sound, which occurs in the middle stage of inspiration, usually in the middle bronchi of middle size. Seen in bronchitis or bronchopneumonia, etc.
6. Dampness of thin type
Also known as small bubble sound. It occurs in the small bronchi, and it mostly occurs in the late phase of inspiration. It is commonly seen in bronchiolitis, bronchopneumonia, pulmonary congestion, pulmonary infarction, etc.
Since the heart beat sound wave signals are separated from the sound wave signals at the lung lobes, the lung function monitoring system can monitor the heart functions in addition to the lung functions, and specifically, the heart beat sound wave signals can be analyzed to judge the heart function status. Since the heart is closer to the left side of the lung, the computing means 2 can determine the heart function status from the waveform of the heart beating sound wave signal having the greatest intensity separated from the sound wave signals at the lower lobe 7 and the upper lobe 6 of the left lung. By combining with the lung function monitoring, the system can realize comprehensive and integrated monitoring on the cardiopulmonary function, and help doctors and patients to accurately master the cardiopulmonary function status.
In terms of the structural form of the sound wave detection devices 1, the sound wave detection devices 1 may be arranged on a flexible patch, the position relationship between the sound wave detection devices 1 is consistent with the position relationship between the lobar bronchi of each pulmonary lobe of the lung, and when the flexible patch is attached to a proper position on the back or the chest of a human body, the sound wave detection devices 1 correspond to the lobar bronchi of each pulmonary lobe of the lung of the human body one to one. The distance and the position relationship between the sound wave sensors 8 on the flexible patch can be determined by analyzing a certain number of human body samples to determine the general size of a lung and the position relationship between the lobar bronchi of each lung lobe, so as to correspond to the distance and the position relationship between the lobar bronchi of each lung lobe of the lung. When the lung function monitoring patch is used, the flexible patch is attached to the position, corresponding to the lung, of the back or the front chest at an angle approximately matched with the position of the lobe bronchus of each lung lobe, and accordingly lung function related monitoring can be achieved, and carrying and use are facilitated. Of course, if the detection of the respiratory sound waves of the lung lobes is to be more accurately realized, more dense sound wave detection devices 1 may be arranged, for example, double sound wave detection devices 1 may be arranged, two sound wave detection devices are respectively arranged on the left lung superior lobe 6 and the left lung inferior lobe 7, two sound wave detection devices are respectively arranged on the right lung superior lobe 3, the right lung medial lobe 4 and the right lung inferior lobe 5, and each sound wave detection device 1 further includes two sound wave sensors 8, so that a more dense sound wave sensor 8 array is formed, and the detection of the respiratory sound wave signals of the lung lobes can be more accurately realized. A more densely arranged array of sonic sensors 8 also facilitates accurate detection of heart beat sonic signals.
The computing device 2 can be internally provided with a Bluetooth or Wi-Fi chip, various analysis result data are sent to a mobile intelligent terminal such as a smart phone through the Bluetooth or Wi-Fi chip, and an analysis judgment result is displayed on a display screen of the mobile intelligent terminal. A touch display screen can be arranged on the computing device 2, detection and analysis judgment data can be displayed in real time through the touch display screen, and meanwhile, relevant setting of detection parameters can be carried out through the touch display screen.
Based on the lung function monitoring device, the embodiment of the invention also provides a lung function monitoring method, which is applied to the computing device 2 in the lung function monitoring system. The lung function monitoring system comprises a lung sound wave detection device 1 and a calculation device 2, wherein the lung sound wave detection device 1 comprises a plurality of sound wave detection devices 1, the sound wave detection devices 1 are in one-to-one correspondence with lung lobes, and the sound wave detection devices 1 are used for detecting sound wave signals at the lung lobes corresponding to the sound wave detection devices and sending the detected sound wave signals to the calculation device 2. The method comprises the steps of separating lung lobe breathing sound wave signals, heart beating sound wave signals and background noise sound wave signals in the received sound wave signals through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judging the functional status of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal. The specific technical solution in the method is described in detail in the above-mentioned lung function monitoring device, and is not described herein again.
An embodiment of the present invention further provides an electronic apparatus, which includes a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the method for monitoring lung function as described above is implemented.
The above-described embodiments are merely preferred embodiments, which are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A lung function monitoring system is used for monitoring lung functions and is characterized by comprising a lung sound wave detection device and a calculation device, wherein the lung sound wave detection device comprises a plurality of sound wave detection devices, the sound wave detection devices correspond to lung lobes of a lung one by one, and the sound wave detection devices are used for detecting sound wave signals at the corresponding lung lobes and sending the detected sound wave signals to the calculation device;
the computing device is configured to separate lung lobe breathing sound wave signals, heart beating sound wave signals and background noise sound wave signals in the received sound wave signals through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judge the function condition of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal.
2. The lung function monitoring system according to claim 1, wherein the determining the function status of each lung lobe according to the waveform of the separated respiratory sound wave signal of each lung lobe comprises:
and comparing the waveform of each separated lung lobe respiration sound wave signal with the waveform of a preset normal lung lobe respiration sound wave signal, and judging whether the function of each lung lobe is abnormal or not according to a comparison result.
3. The lung function monitoring system according to claim 2, wherein the determining the function status of each lung lobe according to the waveform of the separated respiratory sound wave signal of each lung lobe further comprises:
comparing the waveform of the respiratory sound wave signal of the lung lobe with abnormal function with the preset waveforms of the respiratory sound wave signals of different lung lobes, and determining the abnormal lung lobe respiratory sound wave signal with the highest similarity between the waveform and the respiratory sound wave signal of the lung lobe with abnormal function according to the comparison result;
and according to the corresponding relation between the pre-stored abnormal lung lobe breathing sound wave signal and the abnormal type of the lung lobe, taking the abnormal type of the lung lobe corresponding to the abnormal lung lobe breathing sound wave signal with the highest similarity between the waveform and the breathing sound wave signal of the lung lobe with the abnormal function as the abnormal type of the lung lobe with the abnormal function.
4. The lung function monitoring system according to claim 3, wherein the lung lobe is a lobe bronchus of the lung lobe, and the lung lobe respiratory sonic signal is a lobe bronchus respiratory sonic signal of the lung lobe.
5. The lung function monitoring system according to claim 4, wherein the determining the function status of each lung lobe according to the waveform of the separated respiratory sound wave signal of each lung lobe further comprises:
detecting alveolar respiration sound wave interference signals in the separated leaf bronchus respiration sound wave signals of each lung lobe, and judging the alveolar function condition of each lung lobe according to the waveform characteristics of the alveolar respiration sound wave interference signals.
6. The lung function monitoring system according to claim 1, wherein each of the sound wave detection devices includes two sound wave sensors, and each of the lung lobe breathing sound wave signals is a lung lobe breathing sound wave signal having a relatively large intensity separated from the sound wave signals detected by the two sound wave sensors in the sound wave detection device corresponding to each of the lung lobes.
7. The pulmonary function monitoring system of claim 1, wherein the computing device is further configured to determine the cardiac function status based on a waveform of a heart beating sound wave signal of maximum intensity separated from sound wave signals at a lower lobe and an upper lobe of the left lung of the lung.
8. The lung function monitoring system according to any one of claims 4 to 7, wherein the plurality of sound wave detection devices are mounted on a flexible patch, and the positional relationship between the sound wave detection devices is identical to the positional relationship between the lobar bronchi of each lobe of the lung, and when the flexible patch is attached to a proper position on the back or the chest of the human body, each sound wave detection device corresponds to the position of the lobar bronchi of each lobe of the lung of the human body one-to-one.
9. A lung function monitoring method is applied to a computing device in the lung function monitoring system, and is characterized in that the lung function monitoring system comprises a lung sound wave detection device and a computing device, the lung sound wave detection device comprises a plurality of sound wave detection devices, the sound wave detection devices are in one-to-one correspondence with lung lobes of a lung, and the sound wave detection devices are used for detecting sound wave signals at the lung lobes corresponding to the sound wave detection devices and sending the detected sound wave signals to the computing device;
the method comprises the steps of separating lung lobe breathing sound wave signals, heart beating sound wave signals and background noise sound wave signals in the received sound wave signals through frequency analysis according to a preset breathing frequency range, a heartbeat frequency range and a background noise frequency range, and judging the functional status of each lung lobe according to the waveform of each separated lung lobe breathing sound wave signal.
10. An electronic device comprising a processor and a memory, the memory having stored thereon a computer program, wherein the computer program, when executed by the processor, implements a lung function monitoring method as defined in claim 9.
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