Wearable cough monitoring method and system

Abstract

The present invention relates to the field of cough monitoring, and in particular to a wearable cough monitoring method and system, including collecting a physiological signal data group of the wearer; determining whether the real-time respiratory frequency or the real-time heart rate in the physiological signal data group has abnormal parameters according to a preset normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data group corresponding to the abnormal parameters; analyzing the cough audio information according to preset standard information to determine whether to warn the wearer. The present invention can determine whether the body is abnormal at an early stage by real-time monitoring and analyzing the wearer's physiological signal data, and analyze the cough audio in abnormal situations to determine whether the wearer needs to be warned for treatment, which helps to improve the accuracy and real-time nature of cough monitoring, reduce the possibility of misdiagnosis and missed diagnosis, realize the effective use of medical resources, and avoid unnecessary medical intervention.

Description

Technical Field

[0001] The present invention relates to the field of cough monitoring, and in particular to a wearable cough monitoring method and system. Background Art

[0002] Cough is a common symptom of respiratory diseases. Changes in its frequency, intensity, pitch and other parameters can reflect the severity, progression and treatment effect of the disease. Accurately understanding the patient's cough condition is crucial for disease diagnosis, treatment and prognosis assessment. Generally speaking, doctors mainly obtain cough information by asking patients, but patients' cultural level, medical knowledge and language expression ability vary greatly, making it difficult to accurately describe the cough condition and to fully record the cough condition around the clock, especially in the early stages of the disease and the recovery period. It is difficult for doctors to fully understand the patient's cough condition and treatment.

[0003] The patent document with publication number CN110115584A discloses a cough and breathing monitoring system, including a PVDF piezoelectric film belt, a signal conditioning module, a single-chip microcomputer and a Bluetooth wireless transmission module. The PVDF piezoelectric film belt collects human body signals and transmits them to the signal conditioning module. The signal conditioning module converts and processes the input signals and then transmits them to the single-chip microcomputer. The single-chip microcomputer also transmits the signals to the host computer through the Bluetooth wireless transmission module.

[0004] It can be seen that in the actual use of the existing technology, the monitoring of the patient's cough cannot be carried out through detailed data to monitor the patient around the clock, and the patient is warned and treated according to the patient's coughing condition, and whether the treatment is effective is judged in time according to the subsequent monitoring situation. Summary of the invention

[0005] To this end, the present invention provides a wearable cough monitoring method and system to overcome the problem that the existing technology cannot monitor the patient's cough around the clock through detailed data during actual use, and cannot provide early warning and treatment to the patient according to the patient's cough condition, and can promptly determine whether the treatment is effective based on subsequent monitoring results.

[0006] To achieve the above object, the present invention provides a wearable cough monitoring method, comprising:

[0007] Step S1, collecting a physiological signal data set of the wearer;

[0008] The physiological signal data set includes real-time respiratory rate, real-time heart rate and real-time cough audio information;

[0009] Step S2, determining whether the real-time respiratory frequency or the real-time heart rate in the physiological signal data group has abnormal parameters according to a preset normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data group corresponding to the abnormal parameters;

[0010] Step S3, analyzing the cough audio information according to preset standard information to determine whether to warn the wearer, wherein:

[0011] By comparing the real-time cough frequency in the cough audio information with the preset cough frequency, it is determined whether early warning and treatment are needed;

[0012] By calculating the difference between the real-time cough intensity in the cough audio information and the preset cough intensity, the real-time cough intensity fluctuation difference is obtained, and by comparing the real-time cough intensity fluctuation difference with the preset cough intensity fluctuation difference, it is determined whether early warning is needed for treatment.

[0013] Furthermore, in step S1, the real-time respiratory frequency of the wearer is collected by the respiratory frequency collection unit, the real-time heart rate of the wearer is collected by the real-time heart rate collection unit, and the real-time cough audio information of the wearer is acquired by the real-time audio collection unit;

[0014] The real-time cough audio information includes real-time cough frequency and real-time cough intensity value.

[0015] Further, in the step S2, a preset normal physiological parameter range is set, and the real-time respiratory frequency and the real-time heart rate are compared with the corresponding normal range in the preset normal physiological parameter range through the data analysis module. If the real-time physiological parameter in the physiological signal data group does not fall within the corresponding normal range, it is determined that it is abnormal, and the corresponding real-time physiological parameter is marked as the abnormal parameter;

[0016] Wherein, the preset normal physiological parameter range includes a preset normal breathing frequency range and a preset normal heart rate range.

[0017] Furthermore, in step S3, if the abnormal parameter is the real-time respiratory frequency, the real-time cough frequency obtained in the real-time cough audio information is compared with the preset cough frequency;

[0018] If the real-time cough frequency is higher than the preset cough frequency, further analyzing the frequency spectrum characteristics of the cough audio;

[0019] If the real-time cough frequency is not higher than the preset cough frequency, no further analysis is required.

[0020] Furthermore, in step S1, an audio analysis unit is also provided. If the real-time cough frequency is higher than the preset cough frequency, the frequency spectrum characteristics of the cough audio are obtained through the audio analysis unit. The frequency spectrum characteristics include peak frequency and peak amplitude. In step S3, a preset normal cough frequency spectrum characteristic is also provided. The actual cough frequency spectrum characteristic is compared with the preset normal cough frequency spectrum characteristic to determine whether there is an abnormal frequency spectrum characteristic.

[0021] If the abnormal spectrum characteristics exist, an early warning is issued to the wearer for treatment;

[0022] If the abnormal spectrum feature does not exist, the respiratory frequency deviation coefficient is calculated according to the maximum value of the preset normal respiratory frequency range and the real-time respiratory frequency value, and the preset cough frequency value is corrected according to the respiratory frequency deviation coefficient to obtain the corrected preset cough frequency value as a subsequent evaluation standard;

[0023] Among them, K=F1 / F2, K is the respiratory rate deviation coefficient, F1 is the maximum value of the preset normal respiratory rate range, F2 is the real-time respiratory rate value, V2=V1 / K, V1 is the preset cough frequency value, and V2 is the corrected preset cough frequency value.

[0024] Furthermore, the corrected preset cough frequency is used as a new evaluation standard to evaluate the subsequently collected real-time cough frequency, and obtain subsequent evaluation results; if the subsequent evaluation results still show abnormalities, an early warning is issued to the wearer for treatment.

[0025] Further, in step S3, the preset cough intensity value and the preset cough intensity fluctuation difference are set. If the abnormal parameter is the real-time heart rate, the real-time cough intensity value is obtained and the preset cough intensity value is calculated to obtain the real-time cough intensity fluctuation difference, and the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference;

[0026] If the real-time cough intensity fluctuation difference is less than or equal to the preset cough intensity fluctuation difference, no warning is required;

[0027] If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, an early warning is issued;

[0028] Wherein, ΔI s=I 1-I 2, ΔI s is the real-time cough intensity fluctuation difference, I 1 is the real-time cough intensity value, and I 2 is the preset cough intensity value.

[0029] Furthermore, the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference. If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a cough intensity deviation coefficient is obtained by calculation based on the real-time cough intensity value and the preset cough intensity value, and different warnings are given based on the size of the cough deviation coefficient;

[0030] Among them, K = I2 / I1, where K is the cough intensity deviation coefficient.

[0031] Further, after the wearer is warned, the coughing of the wearer is continuously monitored, a subsequent real-time cough intensity value is obtained, the subsequent real-time cough intensity value is calculated with the preset cough intensity value, a new real-time cough intensity fluctuation difference is obtained, and the new real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference;

[0032] If the new real-time cough intensity fluctuation difference is still greater than the preset cough intensity fluctuation difference, the early warning treatment is invalid and the wearer needs to undergo further examination and treatment.

[0033] The present invention also provides a wearable cough monitoring system applicable to any one of the above control methods, comprising:

[0034] A data acquisition module, used to collect real-time physiological data of the wearer, including a respiratory rate acquisition unit, a real-time heart rate acquisition unit, a real-time audio acquisition unit and an audio analysis unit;

[0035] A data analysis module, connected to the data acquisition module, for analyzing the real-time physiological data;

[0036] An early warning module, which is connected to the data analysis module and is used to warn the wearer according to the analysis results;

[0037] The mobile terminal is connected to the data acquisition module, the data analysis module and the early warning module respectively, and is used to store and display data information. At the same time, the mobile terminal can receive early warnings from the early warning module and send reminders to the wearer.

[0038] Compared with the prior art, the beneficial effect of the present invention lies in that, by real-time monitoring of the wearer's physiological signal data, including real-time respiratory rate, real-time heart rate and real-time cough audio information, physical abnormalities can be detected early. By analyzing the physiological signal data, it can be determined whether the body is abnormal, and the cough audio can be analyzed under abnormal circumstances to determine whether it is necessary to warn the wearer for treatment, which helps to improve the accuracy and real-time nature of cough monitoring, reduce the possibility of misdiagnosis and missed diagnosis, and carry out early warning treatment as soon as the wearer's cough is abnormal. When the wearer coughs normally, no specific treatment is required, thereby realizing the effective use of medical resources and avoiding unnecessary medical intervention.

[0039] Furthermore, multiple physiological indicators of the wearer are collected simultaneously by multiple collection units to comprehensively monitor the wearer's health status, thereby improving the accuracy and comprehensiveness of the monitoring. Real-time monitoring of respiratory rate and heart rate can reflect the wearer's overall physiological state, while the collection of cough audio information can specifically evaluate the severity of the cough. Multi-dimensional data collection helps to better analyze the wearer's coughing condition.

[0040] Furthermore, by using the pre-set normal physiological parameter range as a reference standard, the collected real-time physiological data can be initially screened and possible abnormal conditions can be quickly identified. Further analysis can be effectively performed when abnormalities occur, thereby improving the accuracy and efficiency of monitoring. At the same time, by marking abnormal parameters, a clear direction is provided for subsequent in-depth analysis and treatment.

[0041] Furthermore, by analyzing the coughing frequency in response to abnormal breathing rate, the wearer's health status can be further evaluated. This multi-level analysis method can provide a more comprehensive understanding of the wearer's health status and avoid misjudgment caused by a single indicator. At the same time, by setting a preset coughing frequency as a threshold, situations that require further attention can be effectively screened out, thereby improving the efficiency and accuracy of monitoring.

[0042] Furthermore, by monitoring the cough frequency and respiratory rate in real time, the spectral characteristics of the cough audio are obtained through the audio analysis unit and compared with the preset normal cough spectral characteristics to determine whether there are abnormal spectral characteristics, thereby improving the accuracy of cough feature recognition. When there is no abnormality in the cough spectrum, the preset cough frequency value is corrected according to the respiratory frequency deviation coefficient, so that the evaluation standard can be dynamically adjusted according to the wearer's real-time breathing condition, which is helpful for personalized monitoring of the wearer.

[0043] Furthermore, by dynamically adjusting the evaluation criteria, the adaptability and accuracy of the monitoring method are improved. Through multiple evaluations and comparisons, the misjudgment caused by occasional abnormalities can be effectively reduced. At the same time, the wearer's persistent health problems can be discovered in time, and the wearer can be warned for treatment, which helps to detect and deal with potential health problems early.

[0044] Furthermore, by monitoring the cough intensity in real time and comparing it with the preset cough intensity value and the preset cough intensity fluctuation difference, it is determined whether there is an abnormal cough intensity fluctuation difference, thereby achieving early detection and early warning of abnormal coughs. By monitoring the cough intensity in real time and detecting abnormal coughs, early warning and treatment can be achieved, thereby improving the accuracy and reliability of abnormal cough detection.

[0045] Furthermore, this graded recommendation method can provide the wearer with more accurate and targeted warnings based on the abnormal degree of cough intensity, helping the wearer to take appropriate measures to protect their health.

[0046] Furthermore, by comparing the new real-time cough intensity fluctuation difference with the preset cough intensity fluctuation difference, the effect of treatment can be evaluated in real time, providing a basis for whether the wearer needs further examination and treatment, and continuously monitoring and evaluating the coughing situation, which helps to promptly detect changes in the condition, prevent the condition from worsening, and improve the targetedness and effectiveness of treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a wearable cough monitoring method according to an embodiment of the present invention;

[0048] Figure 2 This is a warning judgment logic diagram for an embodiment of the present invention when the abnormal parameter is the real-time respiratory frequency;

[0049] Figure 3 This is a warning judgment logic diagram for an embodiment of the present invention when the abnormal parameter is a real-time heart rate;

[0050] Figure 4 This is a system framework diagram of a wearable cough monitoring system according to an embodiment of the present invention;

[0051] Figure 5 It is a structural schematic diagram of a data acquisition module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0054] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0055] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", 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 a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] See also Figure 1 ,like Figure 1 As shown, it is a flow chart of the wearable cough monitoring method according to an embodiment of the present invention;

[0057] Specifically, the wearable cough monitoring method provided by the embodiment of the present invention includes:

[0058] Step S1, collecting a physiological signal data set of the wearer;

[0059] The physiological signal data set includes real-time respiratory rate, real-time heart rate and real-time cough audio information;

[0060] Step S2, determining whether the real-time respiratory frequency or the real-time heart rate in the physiological signal data group has abnormal parameters according to a preset normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data group corresponding to the abnormal parameters;

[0061] Step S3, analyzing the cough audio information according to preset standard information to determine whether to warn the wearer, wherein:

[0062] By comparing the real-time cough frequency in the cough audio information with the preset cough frequency, it is determined whether early warning and treatment are needed;

[0063] By calculating the difference between the real-time cough intensity in the cough audio information and the preset cough intensity, the real-time cough intensity fluctuation difference is obtained, and by comparing the real-time cough intensity fluctuation difference with the preset cough intensity fluctuation difference, it is determined whether early warning is needed for treatment.

[0064] Specifically, the real-time breathing frequency and real-time heart rate during coughing are judged by the preset normal breathing frequency range and the preset normal heart rate range to determine whether the body is abnormal. In abnormal cases, the coughing audio is analyzed to determine whether the wearer needs to be warned for treatment.

[0065] Specifically, by real-time monitoring of the wearer's physiological signal data, including real-time respiratory rate, real-time heart rate and real-time cough audio information, physical abnormalities can be detected early. By analyzing the physiological signal data, it can be determined whether the body is abnormal, and the cough audio can be analyzed under abnormal conditions to determine whether the wearer needs to be warned for treatment. This helps to improve the accuracy and real-time nature of cough monitoring, reduce the possibility of misdiagnosis and missed diagnosis, and provide early warning treatment as soon as the wearer's cough is abnormal. When the wearer coughs normally, no specific treatment is required, thereby achieving effective use of medical resources and avoiding unnecessary medical intervention.

[0066] Specifically, in step S1, the real-time respiratory frequency of the wearer is collected by the respiratory frequency collection unit, the real-time heart rate of the wearer is collected by the real-time heart rate collection unit, and the real-time cough audio information of the wearer is acquired by the real-time audio collection unit;

[0067] The real-time cough audio information includes real-time cough frequency and real-time cough intensity value.

[0068] Specifically, the respiratory frequency acquisition unit can be various types of respiratory sensors for monitoring and recording the number of breaths per unit time. The real-time heart rate acquisition unit can be various types of heart rate sensors for monitoring and recording the number of heartbeats per unit time. The real-time audio acquisition unit records the cough audio during coughing and analyzes it to obtain the real-time cough frequency and real-time cough intensity values ​​during coughing.

[0069] Specifically, multiple physiological indicators of the wearer are collected simultaneously by multiple collection units to comprehensively monitor the wearer's health status, which improves the accuracy and comprehensiveness of the monitoring. Real-time monitoring of respiratory rate and heart rate can reflect the wearer's overall physiological state, while the collection of cough audio information can specifically evaluate the severity of the cough. Multi-dimensional data collection helps to better analyze the wearer's coughing condition.

[0070] Specifically, in step S2, a preset normal physiological parameter range is set, and the real-time respiratory rate and the real-time heart rate are compared with the corresponding normal range in the preset normal physiological parameter range through the data analysis module. If the real-time physiological parameter in the physiological signal data group does not fall within the corresponding normal range, it is determined that it is abnormal, and the corresponding real-time physiological parameter is marked as the abnormal parameter;

[0071] Wherein, the preset normal physiological parameter range includes a preset normal breathing frequency range and a preset normal heart rate range.

[0072] During the specific implementation process, the normal breathing rate range is preset to 12-20 times per minute. When the real-time breathing rate acquisition unit records the real-time breathing rate as 25 times per minute, the data analysis module determines that there is an abnormality at this time, and marks the real-time breathing rate as an abnormal parameter. The normal heart rate range is preset to 60-100 times. When the real-time heart rate acquisition unit records the real-time heart rate as 120 times, the data analysis module determines that there is an abnormality at this time, and marks the real-time heart rate as an abnormal parameter.

[0073] Specifically, by using the pre-set normal physiological parameter range as a reference standard, the collected real-time physiological data can be initially screened to quickly identify possible abnormal conditions. Further analysis can be effectively performed when abnormalities occur, thereby improving the accuracy and efficiency of monitoring. At the same time, by marking abnormal parameters, a clear direction is provided for subsequent in-depth analysis and treatment.

[0074] Please continue reading Figure 2 ,like Figure 2 As shown, it is a warning determination logic diagram for an embodiment of the present invention when the abnormal parameter is the real-time respiratory frequency;

[0075] Specifically, in step S3, if the abnormal parameter is the real-time respiratory frequency, the real-time cough frequency in the real-time cough audio information is obtained and compared with the preset cough frequency;

[0076] If the real-time cough frequency is higher than the preset cough frequency, further analyzing the frequency spectrum characteristics of the cough audio;

[0077] If the real-time cough frequency is not higher than the preset cough frequency, no further analysis is required.

[0078] During the specific implementation process, the preset cough frequency is 4 times per hour. When the real-time respiratory frequency is an abnormal parameter, if the real-time cough frequency is higher than 4 times per hour, the spectral characteristics of the cough audio are further analyzed. If the real-time cough frequency is not higher than 4 times per hour, no further analysis is performed.

[0079] Specifically, by analyzing the coughing frequency in response to abnormal breathing rate, the wearer's health status can be further assessed. This multi-level analysis method can provide a more comprehensive understanding of the wearer's health status and avoid misjudgment caused by a single indicator. At the same time, by setting a preset coughing frequency as a threshold, situations that require further attention can be effectively screened out, thereby improving monitoring efficiency and accuracy.

[0080] Specifically, in step S1, an audio analysis unit is further provided. If the real-time cough frequency is higher than the preset cough frequency, the frequency spectrum characteristics of the cough audio are obtained through the audio analysis unit. The frequency spectrum characteristics include peak frequency and peak amplitude. In step S3, a preset normal cough frequency spectrum characteristic is also provided. The actual cough frequency spectrum characteristic is compared with the preset normal cough frequency spectrum characteristic to determine whether there is an abnormal frequency spectrum characteristic.

[0081] If the abnormal spectrum characteristics exist, an early warning is issued to the wearer for treatment;

[0082] If the abnormal spectrum feature does not exist, the respiratory frequency deviation coefficient is calculated according to the maximum value of the preset normal respiratory frequency range and the real-time respiratory frequency value, and the preset cough frequency value is corrected according to the respiratory frequency deviation coefficient to obtain the corrected preset cough frequency value as a subsequent evaluation standard;

[0083] Among them, K=F1 / F2, K is the respiratory rate deviation coefficient, F1 is the maximum value of the preset normal respiratory rate range, F2 is the real-time respiratory rate value, V2=V1 / K, V1 is the preset cough frequency value, and V2 is the corrected preset cough frequency value.

[0084] Specifically, when the real-time cough frequency is higher than the preset cough frequency, the audio analysis unit obtains the real-time peak frequency P and the real-time peak amplitude H through spectrum analysis of the real-time cough, presets the normal peak frequency P0 and the normal peak amplitude H0, and determines that there is no abnormal spectrum feature when P≤P0 and T≤T0, otherwise it is determined that there is an abnormal spectrum feature,

[0085] If there is no abnormal spectral feature, in the specific implementation, the normal breathing frequency range is 12-20 times per minute, the maximum value of the normal breathing frequency range is F1=20, the real-time breathing frequency value is F2=25, the breathing frequency deviation coefficient is K=F1 / F2=0.8, and the preset cough frequency value V1=4 is corrected to obtain the corrected preset cough frequency value V2=V1 / K=5, and the corrected preset cough frequency value is used as the subsequent evaluation standard.

[0086] Specifically, by monitoring the cough frequency and breathing frequency in real time, the spectral characteristics of the cough audio are obtained through the audio analysis unit and compared with the preset normal cough spectral characteristics to determine whether there are abnormal spectral characteristics, thereby improving the accuracy of cough feature recognition. When there is no abnormality in the cough spectrum, the preset cough frequency value is corrected according to the breathing frequency deviation coefficient, so that the evaluation standard can be dynamically adjusted according to the wearer's real-time breathing condition, which is helpful for personalized monitoring of the wearer.

[0087] Specifically, the corrected preset cough frequency is used as a new evaluation standard, the real-time cough frequency collected subsequently is evaluated, and subsequent evaluation results are obtained; if the subsequent evaluation results still show abnormalities, an early warning is issued to the wearer for treatment.

[0088] Specifically, the corrected preset cough frequency is used to evaluate the subsequent real-time cough frequency. If the subsequent cough frequency is greater than the corrected preset cough frequency, it means that the wearer's coughing degree is worsening, and an early warning is issued to the wearer for treatment. If the subsequent cough frequency is not greater than the corrected preset cough frequency, it means that the wearer is in good condition and no early warning is needed.

[0089] Specifically, by dynamically adjusting the evaluation criteria, the adaptability and accuracy of the monitoring method are improved. Through multiple evaluations and comparisons, the misjudgment caused by occasional abnormalities can be effectively reduced. At the same time, the wearer's persistent health problems can be discovered in time, and the wearer can be warned for treatment, which helps to detect and deal with potential health problems early.

[0090] Please continue reading Figure 3 ,like Figure 3 As shown, it is a warning determination logic diagram for an embodiment of the present invention when the abnormal parameter is a real-time heart rate;

[0091] Specifically, in step S3, the preset cough intensity value and the preset cough intensity fluctuation difference are set. If the abnormal parameter is the real-time heart rate, the real-time cough intensity value is obtained and the preset cough intensity value is calculated to obtain the real-time cough intensity fluctuation difference, and the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference;

[0092] If the real-time cough intensity fluctuation difference is less than or equal to the preset cough intensity fluctuation difference, no warning is required;

[0093] If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, an early warning is issued;

[0094] Wherein, ΔI s=I 1-I 2, ΔI s is the real-time cough intensity fluctuation difference, I 1 is the real-time cough intensity value, and I 2 is the preset cough intensity value.

[0095] Specifically, the size of the cough sound represents the cough intensity. In a specific implementation, the preset cough intensity value is I2=70, and the preset cough intensity fluctuation difference is ΔI s0=10. When the real-time cough intensity value is I1=75, then ΔI s=5, and the real-time cough intensity fluctuation difference is less than the preset cough intensity fluctuation difference, and no warning is required.

[0096] When the real-time cough intensity value is I1=90, then ΔI s=20, the real-time cough intensity fluctuation difference is greater than the preset cough fluctuation difference, and an early warning is issued.

[0097] Specifically, by monitoring the cough intensity in real time and comparing it with the preset cough intensity value and the preset cough intensity fluctuation difference, it is determined whether there is an abnormal cough intensity fluctuation difference, thereby achieving early detection and warning of abnormal coughs. By monitoring the cough intensity in real time and detecting abnormal coughs, early warning and treatment can be achieved, thereby improving the accuracy and reliability of abnormal cough detection.

[0098] Specifically, the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference. If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a cough intensity deviation coefficient is obtained by calculation based on the real-time cough intensity value and the preset cough intensity value, and different warnings are given based on the size of the cough deviation coefficient.

[0099] Among them, K = I2 / I1, where K is the cough intensity deviation coefficient.

[0100] Specifically, in the actual implementation, different warnings are issued according to the size of the cough intensity deviation coefficient. If k ≥ 0.8, the wearer is warned to perform simple personal care; if K < 0.8, the wearer is warned to perform professional examinations and receive timely treatment.

[0101] Specifically, this graded recommendation method can provide the wearer with more accurate and targeted warnings based on the abnormal degree of cough intensity, helping the wearer to take appropriate measures to protect their own health.

[0102] Specifically, after the wearer is warned, the coughing of the wearer is continuously monitored, a subsequent real-time cough intensity value is obtained, the subsequent real-time cough intensity value is calculated with the preset cough intensity value, a new real-time cough intensity fluctuation difference is obtained, and the new real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference;

[0103] If the new real-time cough intensity fluctuation difference is still greater than the preset cough intensity fluctuation difference, the early warning treatment is invalid and the wearer needs to undergo further examination and treatment.

[0104] Specifically, after the wearer is warned, if the subsequent monitoring shows that the wearer's new real-time cough intensity fluctuation difference is less than the preset cough fluctuation difference, and the real-time cough intensity fluctuation difference continues to decrease, it means that the treatment is effective.

[0105] Specifically, by comparing the new real-time cough intensity fluctuation difference with the preset cough intensity fluctuation difference, the effect of treatment can be evaluated in real time, providing a basis for whether the wearer needs further examination and treatment, and continuously monitoring and evaluating the coughing situation, which helps to promptly detect changes in the condition, prevent the condition from worsening, and improve the targetedness and effectiveness of treatment.

[0106] Please continue reading Figure 4 and Figure 5 ,like Figure 4 and Figure 5 As shown, Figure 4 is a system framework diagram of a wearable cough monitoring system according to an embodiment of the present invention, Figure 5 This is a structural diagram of a data acquisition module according to an embodiment of the present invention;

[0107] Another aspect of the present invention provides a wearable cough monitoring system applicable to any one of the above control methods, comprising:

[0108] A data acquisition module, used to collect real-time physiological data of the wearer, including a respiratory rate acquisition unit, a real-time heart rate acquisition unit, a real-time audio acquisition unit and an audio analysis unit;

[0109] A data analysis module, connected to the data acquisition module, for analyzing the real-time physiological data;

[0110] An early warning module, which is connected to the data analysis module and is used to warn the wearer according to the analysis results;

[0111] The mobile terminal is connected to the data acquisition module, the data analysis module and the early warning module respectively, and is used to store and display data information. At the same time, the mobile terminal can receive early warnings from the early warning module and send reminders to the wearer.

[0112] Specifically, the wearable cough monitoring method provided in the embodiment of the present invention can be applied to the above-mentioned wearable cough monitoring system to achieve the same technical effect, which will not be repeated here.

[0113] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A wearable cough monitoring method, characterized in that: include, Step S1, collecting a physiological signal data set of the wearer; The physiological signal data set includes real-time respiratory rate, real-time heart rate and real-time cough audio information; Step S2, determining whether the real-time respiratory frequency or the real-time heart rate in the physiological signal data group has abnormal parameters according to a preset normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data group corresponding to the abnormal parameters; Step S3, analyzing the cough audio information according to preset standard information to determine whether to warn the wearer, wherein: By comparing the real-time cough frequency in the cough audio information with the preset cough frequency, it is determined whether early warning and treatment are needed; The difference between the real-time cough intensity in the cough audio information and the preset cough intensity is calculated to obtain the real-time cough intensity fluctuation difference, and the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference to determine whether early warning is needed for treatment: In the step S1, an audio analysis unit is further provided. If the real-time cough frequency is higher than the preset cough frequency, the frequency spectrum characteristics of the cough audio are obtained through the audio analysis unit. The frequency spectrum characteristics include peak frequency and peak amplitude. In the step S3, a preset normal cough frequency spectrum characteristic is further provided. The real-time cough frequency spectrum characteristic is compared with the preset normal cough frequency spectrum characteristic to determine whether there is an abnormal frequency spectrum characteristic. If the abnormal spectrum characteristics exist, an early warning is issued to the wearer for treatment; If the abnormal spectrum feature does not exist, the respiratory frequency deviation coefficient is calculated according to the maximum value of the preset normal respiratory frequency range and the real-time respiratory frequency value, and the preset cough frequency value is corrected according to the respiratory frequency deviation coefficient to obtain the corrected preset cough frequency value as a subsequent evaluation standard; Among them, K=F1 / F2, K is the respiratory rate deviation coefficient, F1 is the maximum value of the preset normal respiratory rate range, F2 is the real-time respiratory rate value, V2=V1 / K, V1 is the preset cough frequency value, and V2 is the corrected preset cough frequency value.

2. The wearable cough monitoring method according to claim 1, characterized in that: In step S1, the real-time respiratory frequency of the wearer is collected by the respiratory frequency collection unit, the real-time heart rate of the wearer is collected by the real-time heart rate collection unit, and the real-time cough audio information of the wearer is acquired by the real-time audio collection unit; The real-time cough audio information includes real-time cough frequency and real-time cough intensity value.

3. The wearable cough monitoring method according to claim 1, characterized in that: In the step S2, a preset normal physiological parameter range is set, and the real-time respiratory frequency and the real-time heart rate are compared with the corresponding normal range in the preset normal physiological parameter range through the data analysis module. If the real-time physiological parameter in the physiological signal data group does not fall within the corresponding normal range, it is determined that it is abnormal, and the corresponding real-time physiological parameter is marked as the abnormal parameter; Wherein, the preset normal physiological parameter range includes a preset normal breathing frequency range and a preset normal heart rate range.

4. The wearable cough monitoring method according to claim 1, characterized in that: In step S3, if the abnormal parameter is the real-time respiratory frequency, the real-time cough frequency obtained in the real-time cough audio information is compared with the preset cough frequency; If the real-time cough frequency is higher than the preset cough frequency, further analyzing the frequency spectrum characteristics of the cough audio; If the real-time cough frequency is not higher than the preset cough frequency, no further analysis is required.

5. The wearable cough monitoring method according to claim 1, characterized in that: The corrected preset cough frequency is used as a new evaluation standard to evaluate the real-time cough frequency collected subsequently, and obtain subsequent evaluation results; if the subsequent evaluation results still show abnormalities, an early warning is issued to the wearer for treatment.

6. The wearable cough monitoring method according to claim 1, characterized in that: In step S3, the preset cough intensity value and the preset cough intensity fluctuation difference are set. If the abnormal parameter is the real-time heart rate, the real-time cough intensity value is obtained and the preset cough intensity value is calculated to obtain the real-time cough intensity fluctuation difference, and the real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference; If the real-time cough intensity fluctuation difference is less than or equal to the preset cough intensity fluctuation difference, no warning is required; If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, an early warning is issued; Wherein, ΔIs=I1-I2, ΔIs is the real-time cough intensity fluctuation difference, I1 is the real-time cough intensity value, and I2 is the preset cough intensity value.

7. The wearable cough monitoring method according to claim 1, characterized in that: The real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference. If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a cough intensity deviation coefficient is obtained by calculation based on the real-time cough intensity value and the preset cough intensity value, and different warnings are given based on the size of the cough deviation coefficient; Among them, K = I2 / I1, where K is the cough intensity deviation coefficient.

8. The wearable cough monitoring method according to claim 1, characterized in that: After the wearer is warned, the wearer's coughing condition is continued to be monitored, a subsequent real-time cough intensity value is obtained, the subsequent real-time cough intensity value is calculated with the preset cough intensity value, a new real-time cough intensity fluctuation difference is obtained, and the new real-time cough intensity fluctuation difference is compared with the preset cough intensity fluctuation difference; If the new real-time cough intensity fluctuation difference is still greater than the preset cough intensity fluctuation difference, the early warning treatment is invalid and the wearer needs to undergo further examination and treatment.

9. A wearable cough monitoring system, based on the wearable cough monitoring method according to any one of claims 1 to 8, characterized in that: include, A data acquisition module, used to collect real-time physiological data of the wearer, including a respiratory rate acquisition unit, a real-time heart rate acquisition unit, a real-time audio acquisition unit and an audio analysis unit; A data analysis module, connected to the data acquisition module, for analyzing the real-time physiological data; An early warning module, which is connected to the data analysis module and is used to warn the wearer according to the analysis results; The mobile terminal is connected to the data acquisition module, the data analysis module and the early warning module respectively, and is used to store and display data information. At the same time, the mobile terminal can receive early warnings from the early warning module and send reminders to the wearer.

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