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. The wearable cough monitoring method comprises: collecting a physiological signal data set of a wearer; according to a preset normal physiological parameter range, determining whether an abnormal parameter is present for a real-time respiratory rate or a real-time heart rate in the physiological signal data set, and determining real-time cough audio information in the physiological signal data set corresponding to the abnormal parameter; and according to preset standard information, analyzing the cough audio information, so as to determine whether to alert the wearer. According to the present invention, by means of real-time monitoring and analysis of the physiological signal data of the wearer, it can be determined early whether the body is abnormal, and under abnormal conditions, cough audio is analyzed , so as to determine whether the wearer needs to be alerted for treatment, thereby helping to improve the accuracy and real-time performance of cough monitoring, reducing the possibility of misdiagnosis and missed diagnosis, achieving effective utilization of medical resources, and avoiding unnecessary medical intervention.

Description

Wearable cough monitoring method and system TECHNICAL FIELD

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

[0002] Cough is a common symptom of respiratory diseases, and changes in its frequency, intensity, tone and other parameters can reflect the severity, progression and treatment effect of the disease. Accurate understanding of the patient's coughing situation is crucial for disease diagnosis, treatment and prognosis evaluation. Generally, doctors mainly obtain cough information by asking patients, but patients have great differences in cultural level, medical knowledge and language expression ability, making it difficult to accurately describe the coughing situation and record the whole day's coughing situation. Especially in the early stage of the disease and the recovery period, doctors have difficulty in fully understanding the patient's coughing situation and treatment.

[0003] The patent document with publication number CN110115584A discloses a cough and respiratory monitoring system, which comprises a PVDF piezoelectric film waistband, a signal conditioning module, a single-chip microcomputer and a Bluetooth wireless transmission module. The PVDF piezoelectric film waistband 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 upper computer through the Bluetooth wireless transmission module.

[0004] It can be seen that in the actual use process of the prior art, the monitoring of the patient's cough cannot be monitored all day long through detailed data, and the patient cannot be warned for treatment according to the patient's coughing condition, and whether the treatment is effective can be judged in time according to the subsequent monitoring situation. TECHNICAL SOLUTION

[0005] Therefore, the present application provides a wearable cough monitoring method and system to overcome the problem that in the actual use process of the prior art, the monitoring of the patient's cough cannot be monitored all day long through detailed data, and the patient cannot be warned for treatment according to the patient's coughing condition, and whether the treatment is effective can be judged in time according to the subsequent monitoring situation.

[0006] To achieve the above-mentioned purpose, the present application 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 set has an abnormal parameter according to a pre-set normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data set corresponding to the abnormal parameter;

[0010] Step S3, analyzing the cough audio information according to a pre-set standard information to determine whether to give a warning to the wearer, wherein,

[0011] comparing the real-time cough frequency in the cough audio information with a pre-set cough frequency to determine whether to give a warning for treatment;

[0012] calculating the difference between the real-time cough intensity in the cough audio information and a pre-set cough intensity to obtain a real-time cough intensity fluctuation difference, and comparing the real-time cough intensity fluctuation difference with a pre-set cough intensity fluctuation difference to determine whether to give a warning for treatment.

[0013] Further, in the step S1, the real-time respiratory frequency of the wearer is collected by a respiratory frequency collection unit, the real-time heart rate of the wearer is collected by a real-time heart rate collection unit, and the real-time cough audio information of the wearer is obtained by a real-time audio collection unit.

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

[0015] Further, in the step S2, a pre-set normal physiological parameter range is provided, and the real-time respiratory frequency and the real-time heart rate are compared with corresponding normal ranges in the pre-set normal physiological parameter range by a data analysis module. If the real-time physiological parameters in the physiological signal data set do not fall within the corresponding normal ranges, it is determined that they are abnormal, and the real-time physiological parameters corresponding thereto are marked as the abnormal parameters.

[0016] The pre-set normal physiological parameter range includes a pre-set normal respiratory frequency range and a pre-set normal heart rate range.

[0017] Further, in the 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 compared with the pre-set cough frequency.

[0018] If the real-time cough frequency is higher than the pre-set cough frequency, the frequency spectrum characteristics of the cough audio are further analyzed.

[0019] If the real-time cough frequency is not higher than the pre-set cough frequency, no further analysis is needed.

[0020] Further, 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 audio analysis unit is used to obtain the spectrum characteristics of the cough audio, the spectrum characteristics including peak frequency and peak amplitude, in the step S3, a preset normal cough spectrum characteristic is further provided, the actual cough spectrum characteristic is compared with the preset normal cough spectrum characteristic to determine whether there is an abnormal spectrum characteristic;

[0021] If the abnormal spectrum characteristic exists, a warning is sent to the wearer for treatment;

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

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

[0024] Further, the corrected preset cough frequency is used as a new evaluation standard to evaluate the subsequent collected real-time cough frequency and obtain a subsequent evaluation result, if the subsequent evaluation result still shows abnormality, a warning is sent to the wearer for treatment.

[0025] Further, in the step S3, the preset cough intensity value and the preset cough intensity fluctuation difference are provided, if the abnormal parameter is the real-time heart rate, the real-time cough intensity value is calculated with the preset cough intensity value 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 needed;

[0027] If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a warning is given;

[0028] 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.

[0029] Further, 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, then the real-time cough intensity value and the preset cough intensity value are calculated to obtain a cough intensity deviation coefficient, and different early warnings are performed based on the size of the cough deviation coefficient.

[0030] Wherein, K=I2 / I1, wherein K is the cough intensity deviation coefficient.

[0031] Further, after the wearer is warned, the cough condition of the wearer is continuously monitored to obtain a subsequent real-time cough intensity value, the subsequent real-time cough intensity value is calculated with the preset cough intensity value to obtain a new real-time cough intensity fluctuation difference, 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, it is warned that the treatment is invalid, and the wearer needs to be further examined and treated.

[0033] The application also provides a wearable cough monitoring system suitable for the control method, comprising,

[0034] A data acquisition module is configured to acquire real-time physiological data of the wearer, including a breathing frequency 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 is connected with the data acquisition module and configured to analyze the real-time physiological data.

[0036] A warning module is connected with the data analysis module and configured to warn the wearer according to the analysis result.

[0037] A mobile terminal is connected with the data acquisition module, the data analysis module and the warning module respectively, configured to store and display data information, and the mobile terminal can receive the warning from the warning module and send a reminder to the wearer. Advantages

[0038] Compared with the prior art, the beneficial effects of the present application are that by monitoring the physiological signal data of the wearer in real time, including real-time respiratory rate, real-time heart rate and real-time cough audio information, the body abnormality can be found early, through analysis of the physiological signal data, it can be determined whether the body is abnormal, and in the abnormal case, the cough audio is analyzed to determine whether the wearer needs to be warned for treatment, which helps to improve the accuracy and real-time of cough monitoring, reduces the possibility of misdiagnosis and missed diagnosis, and the wearer can be warned for treatment as soon as possible when the wearer coughs abnormally, and specific treatment is not necessary when normal, so that the medical resources are effectively utilized and unnecessary medical intervention is avoided.

[0039] Further, by simultaneously collecting multiple physiological indicators of the wearer through multiple collection units, the health status of the wearer is comprehensively monitored, and the accuracy and comprehensiveness of the monitoring are improved. The real-time monitoring of respiratory rate and heart rate can reflect the overall physiological state of the wearer, and the collection of cough audio information can specifically evaluate the severity of cough. Multi-dimensional data collection helps better analyze the cough condition of the wearer.

[0040] Further, by setting the normal physiological parameter range as a reference standard, the collected real-time physiological data is preliminarily screened to quickly identify possible abnormal conditions, which can effectively analyze further when abnormal, improve the accuracy and efficiency of monitoring, and at the same time, by marking abnormal parameters, a clear direction is provided for subsequent in-depth analysis and treatment.

[0041] Further, by analyzing the cough frequency to further evaluate the health status of the wearer in the case of abnormal respiratory rate, this multi-level analysis method can more comprehensively understand the health status of the wearer, avoiding misjudgment that may be caused by a single indicator. At the same time, by setting a preset cough frequency as a threshold, conditions that need further attention can be effectively screened, improving the efficiency and accuracy of monitoring.

[0042] Further, by monitoring the cough frequency and respiratory rate in real time, the frequency spectrum characteristics of the cough audio are obtained through the audio analysis unit, and compared with the preset normal cough frequency spectrum characteristics to determine whether there are abnormal frequency spectrum characteristics, which improves the accuracy of cough feature recognition. When the cough frequency spectrum is normal, the preset cough frequency value is corrected according to the respiratory rate deviation coefficient, so that the evaluation standard can be dynamically adjusted according to the real-time respiratory condition of the wearer, which helps to monitor the wearer individually.

[0043] Further, by dynamically adjusting the evaluation standard, the adaptability and accuracy of the monitoring method are improved. Through multiple evaluations and comparisons, misjudgment caused by occasional abnormalities can be effectively reduced, and at the same time, the wearer's persistent health problems can be found in time to warn the wearer for treatment, which helps to discover and handle potential health problems as soon as possible.

[0044] Further, 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 realizing early detection and early warning of cough abnormalities. By monitoring the cough intensity in real time, detecting cough abnormalities, realizing early warning and treatment, and improving the accuracy and reliability of cough abnormality detection.

[0045] Further, this grading recommendation method can provide more accurate and targeted warnings for the wearer according to the degree of cough intensity abnormalities, which helps the wearer to take appropriate measures to protect their own health.

[0046] Further, 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, which provides a basis for whether the wearer needs further examination and treatment, and helps to continuously monitor and evaluate the cough condition, discover changes in the disease condition in a timely manner, prevent the disease condition from worsening, and improve the targeting and effectiveness of treatment. BRIEF DESCRIPTION OF DRAWINGS

[0047] Fig. 1 is a flowchart of the wearable cough monitoring method of the embodiment of the present application;

[0048] Fig. 2 is a warning judgment logic diagram when the abnormal parameter is real-time respiratory rate in the embodiment of the present application;

[0049] Fig. 3 is a warning judgment logic diagram when the abnormal parameter is real-time heart rate in the embodiment of the present application;

[0050] Fig. 4 is a system framework diagram of the wearable cough monitoring system of the embodiment of the present application;

[0051] Fig. 5 is a structural schematic diagram of the data acquisition module of the embodiment of the present application. Embodiment of the present application

[0052] In order to make the purpose and advantages of the present application clearer and more apparent, the present application will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0053] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and do not limit the protection scope of the present application.

[0054] It should be noted that in the description of the present application, the terms of direction or position relationship indicated by "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or position relationship shown in the drawings, which is only for the convenience of description, and does not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0055] In addition, it should be further pointed out that in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0056] Please refer to Fig. 1, which is a flow chart of the wearing type cough monitoring method according to the embodiment of the present application;

[0057] Specifically, the wearing type cough monitoring method provided by the embodiment of the present application comprises,

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

[0059] The physiological signal data set comprises real-time respiratory frequency, 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 set has an abnormal parameter according to a pre-set normal physiological parameter range, and determining the real-time cough audio information in the physiological signal data set corresponding to the abnormal parameter;

[0061] Step S3, analyzing the cough audio information according to pre-set standard information to determine whether to give a warning to the wearer, wherein,

[0062] By comparing the real-time cough frequency in the cough audio information with a pre-set cough frequency, it is determined whether a warning for treatment is needed;

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

[0064] Specifically, the real-time respiratory frequency and real-time heart rate during coughing are determined by the preset normal respiratory frequency range and the preset normal heart rate range to determine whether the body is abnormal, and the cough audio is analyzed in the abnormal case to determine whether the wearer needs to be warned for treatment.

[0065] Specifically, by monitoring the physiological signal data of the wearer in real time, including real-time respiratory frequency, real-time heart rate and real-time cough audio information, the body abnormality can be detected early, and by analyzing the physiological signal data, it can be determined whether the body is abnormal, and the cough audio is analyzed in the abnormal case to determine whether the wearer needs to be warned for treatment, which helps to improve the accuracy and real-time of cough monitoring, reduce the possibility of misdiagnosis and missed diagnosis, and quickly warn and treat the wearer when coughing abnormally, without specific treatment when normal, realizing the effective use of medical resources and avoiding unnecessary medical intervention.

[0066] Specifically, in the 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 obtained 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 collection unit can be various types of respiratory sensors to monitor and record the number of breaths per unit time, the real-time heart rate collection unit can be various types of heart rate sensors to monitor and record the number of heartbeats per unit time, and the real-time audio collection unit records the cough audio during coughing and analyzes to obtain the real-time cough frequency and real-time cough intensity value during coughing.

[0069] Specifically, by simultaneously collecting multiple physiological indicators of the wearer through multiple collection units, the health status of the wearer is comprehensively monitored, and the accuracy and comprehensiveness of the monitoring are improved. The real-time monitoring of respiratory frequency and heart rate can reflect the overall physiological state of the wearer, and the collection of cough audio information can specifically evaluate the severity of coughing. Multi-dimensional data collection helps better analyze the coughing condition of the wearer.

[0070] Specifically, in the step S2, a preset normal physiological parameter range is set, 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 by the data analysis module, if the real-time physiological parameter in the physiological signal data set 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] The preset normal physiological parameter range includes a preset normal respiratory frequency range and a preset normal heart rate range.

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

[0073] Specifically, by taking the preset normal physiological parameter range as a reference standard, the collected real-time physiological data is preliminarily screened, and possible abnormal conditions are quickly identified, which can effectively further analyze the abnormality, improve the accuracy and efficiency of monitoring, and at the same time, by marking the abnormal parameter, a clear direction is provided for subsequent in-depth analysis and treatment.

[0074] Please continue to refer to FIG. 2, which is a warning determination logic diagram when the abnormal parameter is real-time respiratory frequency in the embodiment of the application;

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

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

[0077] If the real-time cough frequency is not higher than the preset cough frequency, further analysis is not needed.

[0078] In 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, and if the real-time cough frequency is not higher than 4 times per hour, no further analysis is performed.

[0079] Specifically, by analyzing the cough frequency for the case of abnormal respiratory frequency, the health status of the wearer is further evaluated, and this multi-level analysis method can more comprehensively understand the health status of the wearer, avoid misjudgment caused by a single indicator, and at the same time, by setting the preset cough frequency as a threshold, the situation that needs further attention can be effectively screened, and the efficiency and accuracy of monitoring are improved.

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

[0081] If the abnormal spectrum characteristic exists, a warning is sent to the wearer for treatment.

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

[0083] Wherein, K=F1 / F2, K is the breathing frequency deviation coefficient, F1 is the maximum value of the preset normal breathing frequency range, F2 is the real-time breathing frequency 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, and obtains the preset normal peak frequency P0 and the normal peak amplitude H0. When P≤P0 and T≤T0, it is determined that there is no abnormal spectrum characteristic, otherwise it is determined that there is an abnormal spectrum characteristic.

[0085] If there is no abnormal spectrum characteristic, in a specific implementation, the normal breathing frequency range is 12-20 times per minute, the maximum value of the normal breathing frequency range F1=20, the real-time breathing frequency value F2=25, the breathing frequency deviation coefficient K=F1 / F2=0.8, 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 the breathing frequency in real time, the spectrum characteristics of the cough audio are obtained through the audio analysis unit and compared with the preset normal cough spectrum characteristic to determine whether there is an abnormal spectrum characteristic, which improves the accuracy of cough feature recognition. When the cough spectrum is normal, 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 real-time breathing condition of the wearer, which is helpful for personalized monitoring of the wearer.

[0087] Specifically, the modified preset cough frequency is used as a new evaluation standard to evaluate the subsequent real-time cough frequency and obtain a subsequent evaluation result. If the subsequent evaluation result still shows an abnormality, a warning is sent to the wearer for treatment.

[0088] Specifically, the modified preset cough frequency is used as a new evaluation standard to evaluate the subsequent real-time cough frequency and obtain a subsequent evaluation result. If the subsequent evaluation result still shows an abnormality, a warning is sent to the wearer for treatment.

[0089] Specifically, the modified preset cough frequency is used as a new evaluation standard to evaluate the subsequent real-time cough frequency and obtain a subsequent evaluation result. If the subsequent evaluation result still shows an abnormality, a warning is sent to the wearer for treatment.

[0090] Please continue to refer to FIG. 3, which is a warning judgment logic diagram of the embodiment of the present application when the abnormal parameter is real-time heart rate;

[0091] Specifically, in the 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 calculated with the preset cough intensity value, the real-time cough intensity fluctuation difference is obtained, 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 needed.

[0093] If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a warning is needed.

[0094] 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.

[0095] Specifically, the cough sound size represents the cough intensity. In the specific implementation, the preset cough intensity value is I2 = 70, the preset cough intensity fluctuation difference is ΔIs0 = 10, when the real-time cough intensity value is I1 = 75, ΔIs = 5, the real-time cough intensity fluctuation difference is less than the preset cough intensity fluctuation difference, and no warning is needed.

[0096] When the real-time cough intensity value is I1 = 90, ΔIs = 20, the real-time cough intensity fluctuation difference is greater than the preset cough fluctuation difference, and a warning is needed.

[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 realizing early detection and early warning of cough abnormalities. By monitoring the cough intensity in real time, detecting cough abnormalities, realizing early warning and treatment, and improving the accuracy and reliability of cough abnormality 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, the real-time cough intensity value is calculated based on the preset cough intensity value to obtain a cough intensity deviation coefficient. Different warnings are given based on the size of the cough deviation coefficient.

[0099] Wherein, K = I2 / I1, wherein K is the cough intensity deviation coefficient.

[0100] Specifically, in specific implementation, different warnings are given according to the size of the cough intensity deviation coefficient. If k ≥ 0.8, the wearer is warned to take simple personal conditioning. If K < 0.8, the wearer is warned to take professional examination and timely treatment.

[0101] Specifically, this grading suggestion method can provide more accurate and targeted warnings for the wearer according to the degree of cough intensity abnormality, which helps the wearer to take appropriate measures to protect their own health.

[0102] Specifically, after warning the wearer, the cough condition of the wearer is continuously monitored to obtain subsequent real-time cough intensity values. The subsequent real-time cough intensity values are calculated based on the preset cough intensity value to obtain a new real-time cough intensity fluctuation difference. 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, it is warned that the treatment is ineffective, and the wearer needs to be further examined and treated.

[0104] Specifically, after warning the wearer, the subsequent monitoring of 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, which indicates 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 the treatment can be evaluated in real time, which provides a basis for whether the wearer needs further examination and treatment. Continuous monitoring and evaluation of the cough condition helps to discover changes in the disease condition in a timely manner, prevent the disease from worsening, and improve the effectiveness of the treatment.

[0106] Please continue to refer to Figures 4 and 5, as shown in Figures 4 and 5, wherein Figure 4 is a system framework diagram of the wearable cough monitoring system according to the embodiment of the present application, and Figure 5 is a structural schematic diagram of the data acquisition module according to the embodiment of the present application;

[0107] In another aspect, the present application provides a wearable cough monitoring system suitable for the control method described above, comprising,

[0108] a data acquisition module, configured to acquire real-time physiological data of the wearer, including a respiratory frequency 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, configured to analyze the real-time physiological data;

[0110] a warning module, connected to the data analysis module, configured to warn the wearer according to the analysis result;

[0111] a mobile terminal, connected to the data acquisition module, the data analysis module and the warning module respectively, configured to store and display the data information, and the mobile terminal can receive the warning from the warning module and send a reminder to the wearer.

[0112] Specifically, the wearable cough monitoring method provided by the embodiment of the present application can be applied to the wearable cough monitoring system described above to achieve the same technical effects, which will not be described here.

[0113] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

[0114] The above description is only the preferred embodiments of the present application and is not intended to limit the present application; for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of wearable cough monitoring, the method comprising: Comprising, Step S1, collecting the 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, according to the pre-set normal physiological parameter range, determine whether the real-time respiratory rate or the real-time heart rate in the physiological signal data set has abnormal parameter, and determine the real-time cough audio information in the physiological signal data set corresponding to the abnormal parameter; Step S3, according to the preset standard information, analyze the cough audio 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 the treatment needs to be warned; 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 the treatment needs to be warned.

2. The method of claim 1, wherein, In the step S1, the real-time respiratory rate of the wearer is collected by the respiratory rate acquisition unit, the real-time heart rate of the wearer is collected by the real-time heart rate acquisition unit, and the real-time cough audio information of the wearer is obtained by the real-time audio acquisition unit; Wherein, the real-time cough audio information includes real-time cough frequency and real-time cough intensity value.

3. The method of claim 1, wherein, In the step S2, the preset normal physiological parameter range is set, 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 by the data analysis module, if the real-time physiological parameter in the physiological signal data set does not fall within the corresponding normal range, it is determined that it has abnormality, and the corresponding real-time physiological parameter is marked as the abnormal parameter; Wherein, the preset normal physiological parameter range includes preset normal respiratory rate range and preset normal heart rate range.

4. The method of claim 1, wherein, In the step S3, if the abnormal parameter is real-time respiratory rate, the real-time cough frequency 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, the frequency spectrum characteristics of the cough audio are further analyzed; If the real-time cough frequency is not higher than the preset cough frequency, further analysis is not needed.

5. The method of claim 1, wherein, In the step S1, the 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 by the audio analysis unit, the frequency spectrum characteristics include peak frequency and peak amplitude, in the step S3, the preset normal cough frequency spectrum characteristics are also provided, the actual cough frequency spectrum characteristics are compared with the preset normal cough frequency spectrum characteristics to determine whether there is abnormal frequency spectrum characteristics; If there is the abnormal frequency spectrum characteristics, the wearer is warned to treat; If there is no abnormal frequency spectrum characteristics, the respiratory rate deviation coefficient is calculated according to the maximum value of the preset normal respiratory rate range and the real-time respiratory rate value, and the preset cough frequency value is corrected according to the respiratory rate deviation coefficient to obtain the corrected preset cough frequency value as the subsequent evaluation standard; Wherein, K=F1 / F2, K is the respiratory rate deviation coefficient, F1 is the preset normal respiratory rate range maximum value, F2 is the real-time respiratory rate value, V2=V1 / K, V1 is the preset cough frequency value, V2 is the corrected preset cough frequency value.

6. The method of claim 1, wherein, The corrected preset cough frequency is used as a new evaluation standard to evaluate the subsequent real-time cough frequency, and a subsequent evaluation result is obtained; if the subsequent evaluation result still shows an abnormality, a warning is sent to the wearer for treatment.

7. The method of claim 1, wherein, In the 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 compared with the preset cough intensity value, the real-time cough intensity fluctuation difference is obtained and 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 needed; If the real-time cough intensity fluctuation difference is greater than the preset cough intensity fluctuation difference, a warning is given; Wherein, ΔIs=I1-I2, ΔIs is the real-time cough intensity fluctuation difference, I1 is the real-time cough intensity value, I2 is the preset cough intensity value.

8. The method of claim 1, wherein, 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, the real-time cough intensity value is calculated according to the preset cough intensity value, a cough intensity deviation coefficient is obtained, and different warnings are given based on the size of the cough deviation coefficient; Wherein, K=I2 / I1, K is the cough intensity deviation coefficient.

9. The method of claim 1, wherein, After the wearer is warned, the cough condition 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; If the new real-time cough intensity fluctuation difference is still greater than the preset cough intensity fluctuation difference, the warning treatment is invalid, and the wearer needs to be further examined and treated.

10. A wearable cough monitoring system based on the wearable cough monitoring method of any one of claims 1-9, characterized in that, Comprising, The data acquisition module is used to acquire the 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; The data analysis module is connected with the data acquisition module to analyze the real-time physiological data; The warning module is connected with the data analysis module to warn the wearer according to the analysis result; The mobile terminal is connected with the data acquisition module, the data analysis module and the warning module respectively to store and display the data information, and the mobile terminal can receive the warning from the warning module and send a reminder to the wearer.

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