Disease data acquisition and analysis method and systemTechnical Field
The invention relates to the technical field of disease data acquisition and analysis, in particular to a disease data acquisition and analysis method and an acquisition and analysis system.
Background
Along with the rapid development of science and technology, the application fields of data acquisition and analysis become wider, wherein the most remarkable is the data acquisition and data analysis of diseases, and the characteristics of intellectualization, high efficiency and the like provide more convenient and effective diagnosis results for patients, thereby becoming an important diagnosis mode for keeping population healthy.
Because of the influence of social working environment and living environment, many patients do not pay attention to the rhinitis of the patients, so that the rhinitis of the patients is aggravated, a series of diseases are caused, and the importance of rhinitis data acquisition and analysis is highlighted.
At present, when rhinitis data of a patient are acquired, the inside of the nasal cavity of the patient is mainly detected, the rhinitis type diagnosis is carried out on the patient based on the nasal cavity internal data of the patient, the inspection process is complicated, the intelligent and high-efficiency analysis of the rhinitis type corresponding to the patient cannot be realized, and the diagnosis period of the patient is further prolonged.
At present, when the severity degree of rhinitis of a patient is analyzed, the nasal cavity data of the patient is mainly diagnosed and analyzed by a doctor, the breathing state data of the patient is ignored, the one-sided and subjective performance of the analysis of the severity degree of rhinitis of the patient are caused, meanwhile, the scientific data support is lacked, and a certain influence is generated for the follow-up treatment of the patient to a certain extent.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a disease data acquisition and analysis method and a disease data acquisition and analysis system, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: the first aspect of the invention provides a disease data acquisition and analysis method, comprising the following steps: 1. collecting and analyzing nasal secretion information of a patient: the facial state videos of the target patient corresponding to the set period are collected, facial state sub-videos of the target patient corresponding to the nasal discharge behaviors are obtained, and meanwhile nasal secretion information of the target patient corresponding to the nasal discharge behaviors is extracted and analyzed to obtain the specific rhinitis type corresponding to the target patient.
2. Patient nasal mucosa status collection analysis: the method comprises the steps of collecting the internal information of the nasal cavity of each collecting time point in the corresponding setting period of a target patient to obtain a nasal cavity internal information set of the target patient corresponding to each collecting time point, and analyzing a nasal cavity internal state evaluation index of the target patient corresponding to each collecting time point.
3. Patient respiratory information acquisition and analysis: and acquiring the respiratory information of each acquisition time point in the corresponding setting period of the target patient to obtain a respiratory information set of each acquisition time point of the target patient, and analyzing respiratory state evaluation indexes of each acquisition time point of the target patient.
4. Patient rhinitis severity analysis: and analyzing the rhinitis severity evaluation coefficient corresponding to the target patient to obtain the rhinitis severity evaluation coefficient corresponding to the target patient, and analyzing the rhinitis severity level corresponding to the target patient.
5. Rhinitis severity display and treatment: and displaying the rhinitis severity level corresponding to the target patient, and performing corresponding treatment.
As a preferred scheme of the invention, in the first step, nasal secretion information corresponding to each nasal discharge behavior of a target patient is extracted and analyzed, and the specific extraction and analysis steps are as follows: 101: image segmentation is carried out on the facial state sub-video corresponding to each nasal discharge behavior of the target patient, so that a facial state sub-image set corresponding to each nasal discharge behavior of the target patient is obtained, and the nasal cavity part of the facial state sub-image set corresponding to each nasal discharge behavior of the target patient is focused and amplified, so that a nasal cavity part sub-image set corresponding to each nasal discharge behavior of the target patient after focusing and amplifying is obtained.
102: extracting nasal secretion images corresponding to the first nasal discharge behaviors of the target patient from the nasal cavity position sub-image collection corresponding to the first nasal discharge behaviors of the target patient after focusing and amplifying, extracting nasal secretion images corresponding to the first nasal discharge behaviors of the target patient from the nasal secretion images corresponding to the first nasal discharge behaviors of the target patient, matching the nasal secretion images corresponding to the first nasal discharge behaviors of the target patient with the stored nasal secretion images corresponding to the various secretion states to obtain secretion states corresponding to the first nasal discharge behaviors of the target patient, executing 103 if the secretion states corresponding to the first nasal discharge behaviors of the target patient are thick, and executing 104 if the secretion states corresponding to the first nasal discharge behaviors of the target patient are clear water states.
103: and matching the thick state of the first nasal discharge behavior corresponding to the target patient with the specific rhinitis type of the thick state corresponding to the stored first nasal discharge secretion to obtain the specific rhinitis type of the first nasal discharge behavior corresponding to the target patient, and taking the specific rhinitis type corresponding to the target patient as the specific rhinitis type corresponding to the target patient.
104: the nasal secretion image corresponding to the first nasal discharge behavior of the target patient and the nasal secretion image corresponding to each nasal discharge behavior of the target patient are compared with each other, if the nasal secretion image corresponding to a certain nasal discharge behavior of the target patient is inconsistent with the nasal secretion image corresponding to the first nasal discharge behavior, the processing is performed 105, and if the nasal secretion image corresponding to each nasal discharge behavior of the target patient is consistent with the nasal secretion image corresponding to the first nasal discharge behavior, the processing is performed 106.
105: extracting nasal secretion images of the secondary nasal discharge behaviors, recording the nasal secretion images as nasal secretion images of the subsequent nasal discharge behaviors, simultaneously matching the nasal secretion images with the stored nasal secretion images corresponding to various secretion states to obtain secretion states of the subsequent nasal discharge behaviors corresponding to the target patient, and matching the thick state of the subsequent nasal discharge behaviors corresponding to the target patient with the specific rhinitis type of the stored subsequent nasal discharge corresponding to the thick state if the secretion states of the subsequent nasal discharge behaviors corresponding to the target patient are thick, so as to obtain the specific rhinitis type of the subsequent nasal discharge behaviors corresponding to the target patient, and taking the specific rhinitis type as the specific rhinitis type corresponding to the target patient.
106: and (3) marking the nasal secretion image corresponding to each nasal discharge behavior of the target patient as a consistent nasal secretion image, taking the secretion state corresponding to the first nasal discharge behavior of the target patient as the secretion state corresponding to the subsequent nasal discharge behavior of the target patient, and simultaneously matching the secretion state with the stored specified rhinitis type corresponding to the subsequent nasal discharge to the clear water state to obtain the specified rhinitis type corresponding to the subsequent nasal discharge behavior of the target patient as the specified rhinitis type corresponding to the target patient.
As a preferred scheme of the present invention, in the second step, the nasal cavity internal information of each collection time point in the corresponding setting period of the target patient is collected, and the specific collection mode is as follows: the method comprises the steps of acquiring the internal nasal cavity images of all acquisition time points in a corresponding setting period of a target patient through an electronic nasopharynx laryngoscope, and obtaining the internal nasal cavity images of all acquisition time points in the corresponding setting period of the target patient.
Extracting the nasal mucosa shape outline, the nasal secretion distribution area and the abnormal protrusion area in the nasal cavity of each acquisition time point in the corresponding setting period of the target patient from the nasal cavity internal image of each acquisition time point in the corresponding setting period of the target patient, and overlapping and comparing the nasal mucosa shape outline of each acquisition time point in the corresponding setting period of the target patient with the stored reference nasal mucosa shape outline to obtain the nasal mucosa overlapping area of each acquisition time point of the target patient.
The nasal mucosa overlapping area, the nasal secretion distribution area and the nasal cavity internal abnormal bulge area of the target patient corresponding to each acquisition time point form a nasal cavity internal information set of the target patient corresponding to each acquisition time point.
As a preferred embodiment of the present invention, in the second step, the nasal cavity internal state evaluation index of the target patient corresponding to each collection time point is analyzed in the following specific analysis manner: matching the specific rhinitis type corresponding to the target patient with the set allowable nasal cavity secretion distribution area and allowable nasal cavity internal abnormal bulge area corresponding to each specific rhinitis type to obtain the allowable nasal cavity secretion distribution area and allowable nasal cavity internal abnormal bulge area corresponding to the target patient, and respectively marking as S1 ' and S2 ′。
And matching the specified rhinitis type corresponding to the target patient with the reference nasal mucosa overlapping area corresponding to each specified rhinitis type, so as to obtain the reference nasal mucosa overlapping area corresponding to the target patient, and marking as S'.
According to the formulaCalculating the nasal cavity internal state evaluation index phi of the target patient corresponding to each acquisition time pointi Nasal internal state evaluation index expressed as the target patient corresponding to the i-th collection time point, i expressed as the number of each collection time point, i=1, 2>Respectively expressed as the nasal mucosa superposition area, the nasal secretion distribution area and the abnormal protruding area in the nasal cavity of the target patient corresponding to the ith acquisition time point, a1 、a2 、a3 The values are respectively expressed as the set influence factors corresponding to the nasal mucosa superposition area, the nasal secretion distribution area and the abnormal bulge area in the nasal cavity.
As a preferred scheme of the present invention, in the third step, the respiration information of each acquisition time point in the set period corresponding to the target patient is acquired, and the specific acquisition mode is as follows: the nasal resistance meter is used for collecting the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity and the nasal inhalation resistance value of the right nasal cavity at each collection time point in the corresponding setting period of the target patient, so that the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity and the nasal inhalation resistance value of the right nasal cavity of the target patient at each collection time point are obtained.
And acquiring the nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity at each acquisition time point in the corresponding setting period of the target patient through a nasal respiration meter to obtain the nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity of the target patient at each acquisition time point.
The respiratory information set of the target patient corresponding to each collecting time point is formed by the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal ventilation flow of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity, the nasal inhalation resistance value of the right nasal cavity and the nasal ventilation flow of the right nasal cavity of the target patient corresponding to each collecting time point.
As a preferred embodiment of the present invention, in the third step, the respiratory state evaluation index of the target patient corresponding to each acquisition time point is analyzed in the following specific analysis manner: matching the specified rhinitis type corresponding to the target patient with the set reference respiratory information set corresponding to each specified rhinitis type to obtain the reference respiratory information set corresponding to the target patient, extracting the nasal exhalation resistance value, the nasal inhalation resistance value, the nasal ventilation flow, the nasal exhalation resistance value, the nasal inhalation resistance value and the nasal ventilation flow corresponding to the target patient, which are respectively recorded as hq'Left side 、xq′Left side 、tq′Left side 、hq′Right side 、xq′Right side And tq'Right side 。
According to the formulaCalculating the corresponding acquisition time of the target patientPoint left nasal respiratory state assessment index, +.>Left nasal respiratory state evaluation index, expressed as target patient corresponding to the ith acquisition time point,/>The left nasal cavity nasal exhalation resistance value, the nasal inhalation resistance value and the nasal cavity ventilation flow rate corresponding to the ith acquisition time point of the target patient are respectively expressed as a4 、a5 、a6 The set values of the left nasal cavity nasal exhalation resistance, the left nasal cavity nasal inhalation resistance and the influence factors corresponding to the left nasal cavity ventilation flow are respectively expressed.
Calculating the right nasal cavity respiratory state evaluation index of the target patient corresponding to each acquisition time point according to a formula, and recording as
According to the formulaCalculating respiratory state evaluation indexes gamma of the target patient corresponding to each acquisition time periodi A respiratory state evaluation index, b, expressed as the target patient corresponding to the ith acquisition period1 、b2 The set left nasal cavity respiratory state evaluation index and the right nasal cavity respiratory state evaluation index are respectively expressed as weight factors corresponding to the set left nasal cavity respiratory state evaluation index and the right nasal cavity respiratory state evaluation index.
As a preferred scheme of the present invention, in the fourth step, the rhinitis severity assessment coefficient corresponding to the target patient is analyzed, and a specific analysis formula thereof is as follows:θ is expressed as a rhinitis severity evaluation coefficient corresponding to the target patient, b3 、b4 Respectively representing the set nasal cavity internal state evaluation index and the weight factor corresponding to the respiratory state evaluation index.
As a preferred scheme of the present invention, in the fourth step, the severity level of rhinitis corresponding to the target patient is analyzed, and the specific analysis method is as follows: and matching the rhinitis severity evaluation coefficient corresponding to the target patient with the rhinitis severity evaluation coefficient threshold corresponding to the set various rhinitis severity grades to obtain the rhinitis severity grade corresponding to the target patient.
A second aspect of the present invention provides a disease data acquisition analysis system, comprising: the nasal secretion information acquisition and analysis module is used for acquiring facial state videos of the target patient corresponding to a set period, obtaining facial state sub-videos of the target patient corresponding to various nasal discharge behaviors, and analyzing the appointed rhinitis type corresponding to the target patient.
The nasal mucosa state acquisition and analysis module is used for acquiring the internal information of the nasal cavity of each acquisition time point in the corresponding setting period of the target patient, and analyzing the internal state evaluation index of the nasal cavity of the target patient corresponding to each acquisition time point.
And the patient respiratory information acquisition and analysis module is used for acquiring respiratory information of each acquisition time point in the corresponding set period of the target patient and analyzing respiratory state evaluation indexes of the target patient corresponding to each acquisition time point.
And the rhinitis severity analysis module is used for analyzing the rhinitis severity assessment coefficient corresponding to the target patient and analyzing the rhinitis severity level corresponding to the target patient.
And the rhinitis severity display and processing module is used for displaying the rhinitis severity level corresponding to the target patient and performing corresponding processing.
The storage library is used for storing nasal secretion images corresponding to various secretion states, storing appointed rhinitis types corresponding to the first nasal secretion state and the thick state, storing appointed rhinitis types corresponding to the subsequent nasal secretion state and storing reference nasal mucosa shape outlines.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: the invention collects the facial state sub-videos corresponding to each time of nasal discharge behaviors of the target patient, analyzes the appointed rhinitis type corresponding to the target patient, realizes the intellectualization and high efficiency of the rhinitis type analysis corresponding to the patient, and makes up the defect of diagnosis of the rhinitis type corresponding to the patient in the current technology.
According to the invention, the nasal cavity internal information of each acquisition time point in the corresponding setting period of the target patient is acquired, and the nasal cavity internal state evaluation index of each acquisition time point of the target patient is analyzed, so that the accuracy and reliability of the nasal cavity internal state evaluation result of the target patient are ensured to the greatest extent, the persuasion of the nasal cavity internal state analysis result of the target patient is improved, and accurate and visual data are provided for the analysis of the rhinitis severity degree of the subsequent target patient.
According to the invention, the respiratory information of each acquisition time point in the corresponding setting period of the target patient is acquired, and the respiratory state evaluation index of the target patient corresponding to each acquisition time point is analyzed, so that the singleness and one-sided performance of monitoring and analyzing the severity of the rhinitis corresponding to the patient in the prior art are effectively solved, and the reliability and the accuracy of analyzing the severity of the rhinitis of the patient are increased.
According to the rhinitis severity evaluation method, the rhinitis severity evaluation coefficient corresponding to the target patient is analyzed, and the rhinitis severity grade corresponding to the target patient is obtained through analysis, so that the persuasion of the rhinitis severity analysis of the patient is improved, and the follow-up development of targeted treatment on the patient is promoted.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a flow chart of the steps of the method of the present invention.
FIG. 2 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first aspect of the present invention provides a disease data acquisition and analysis method, including the following steps: 1. collecting and analyzing nasal secretion information of a patient: the facial state videos of the target patient corresponding to the set period are collected, facial state sub-videos of the target patient corresponding to the nasal discharge behaviors are obtained, and meanwhile nasal secretion information of the target patient corresponding to the nasal discharge behaviors is extracted and analyzed to obtain the specific rhinitis type corresponding to the target patient.
As a further improvement of the present invention, in the first step, the facial status sub-video of each nasal discharge behavior of the target patient is obtained by the following specific method: and identifying whether the target patient has the runny nose behavior from the facial state video of the corresponding setting period of the target patient, if the target patient has the runny nose behavior in the corresponding setting period, marking the starting runny nose and ending runny nose corresponding to the target patient as the runny nose behavior, and counting the number of times of the runny nose behavior in the corresponding setting period of the target patient.
Extracting facial state sub-videos of the runny behaviors of the target patient in the corresponding setting period from the facial state videos of the target patient in the corresponding setting period, and obtaining the facial state sub-videos of the runny behaviors of the target patient.
As a further improvement of the present invention, in the first step, nasal secretion information corresponding to each nasal discharge behavior of the target patient is extracted and analyzed, and the specific extraction and analysis steps are as follows: 101: image segmentation is carried out on the facial state sub-video corresponding to each nasal discharge behavior of the target patient, so that a facial state sub-image set corresponding to each nasal discharge behavior of the target patient is obtained, and the nasal cavity part of the facial state sub-image set corresponding to each nasal discharge behavior of the target patient is focused and amplified, so that a nasal cavity part sub-image set corresponding to each nasal discharge behavior of the target patient after focusing and amplifying is obtained.
102: extracting nasal secretion images corresponding to the first nasal discharge behaviors of the target patient from the nasal cavity position sub-image collection corresponding to the first nasal discharge behaviors of the target patient after focusing and amplifying, extracting nasal secretion images corresponding to the first nasal discharge behaviors of the target patient from the nasal secretion images corresponding to the first nasal discharge behaviors of the target patient, matching the nasal secretion images corresponding to the first nasal discharge behaviors of the target patient with the stored nasal secretion images corresponding to the various secretion states to obtain secretion states corresponding to the first nasal discharge behaviors of the target patient, executing 103 if the secretion states corresponding to the first nasal discharge behaviors of the target patient are thick, and executing 104 if the secretion states corresponding to the first nasal discharge behaviors of the target patient are clear water states.
103: and matching the thick state of the first nasal discharge behavior corresponding to the target patient with the specific rhinitis type of the thick state corresponding to the stored first nasal discharge secretion to obtain the specific rhinitis type of the first nasal discharge behavior corresponding to the target patient, and taking the specific rhinitis type corresponding to the target patient as the specific rhinitis type corresponding to the target patient.
104: the nasal secretion image corresponding to the first nasal discharge behavior of the target patient and the nasal secretion image corresponding to each nasal discharge behavior of the target patient are compared with each other, if the nasal secretion image corresponding to a certain nasal discharge behavior of the target patient is inconsistent with the nasal secretion image corresponding to the first nasal discharge behavior, the processing is performed 105, and if the nasal secretion image corresponding to each nasal discharge behavior of the target patient is consistent with the nasal secretion image corresponding to the first nasal discharge behavior, the processing is performed 106.
105: extracting nasal secretion images of the secondary nasal discharge behaviors, recording the nasal secretion images as nasal secretion images of the subsequent nasal discharge behaviors, simultaneously matching the nasal secretion images with the stored nasal secretion images corresponding to various secretion states to obtain secretion states of the subsequent nasal discharge behaviors corresponding to the target patient, and matching the thick state of the subsequent nasal discharge behaviors corresponding to the target patient with the specific rhinitis type of the stored subsequent nasal discharge corresponding to the thick state if the secretion states of the subsequent nasal discharge behaviors corresponding to the target patient are thick, so as to obtain the specific rhinitis type of the subsequent nasal discharge behaviors corresponding to the target patient, and taking the specific rhinitis type as the specific rhinitis type corresponding to the target patient.
106: and (3) marking the nasal secretion image corresponding to each nasal discharge behavior of the target patient as a consistent nasal secretion image, taking the secretion state corresponding to the first nasal discharge behavior of the target patient as the secretion state corresponding to the subsequent nasal discharge behavior of the target patient, and simultaneously matching the secretion state with the stored specified rhinitis type corresponding to the subsequent nasal discharge to the clear water state to obtain the specified rhinitis type corresponding to the subsequent nasal discharge behavior of the target patient as the specified rhinitis type corresponding to the target patient.
In a specific embodiment, the facial state sub-videos of the corresponding nasal discharge behaviors of the target patient are collected, and the specific rhinitis types corresponding to the target patient are analyzed, so that the intelligent and efficient analysis of the rhinitis types corresponding to the patient is realized, and the defect of diagnosis of the rhinitis types corresponding to the patient in the current technology is overcome.
2. Patient nasal mucosa status collection analysis: the method comprises the steps of collecting the internal information of the nasal cavity of each collecting time point in the corresponding setting period of a target patient to obtain a nasal cavity internal information set of the target patient corresponding to each collecting time point, and analyzing a nasal cavity internal state evaluation index of the target patient corresponding to each collecting time point.
As a further improvement of the present invention, in the second step, the nasal cavity internal information of each collection time point in the corresponding setting period of the target patient is collected, and the specific collection mode is as follows: the method comprises the steps of acquiring the internal nasal cavity images of all acquisition time points in a corresponding setting period of a target patient through an electronic nasopharynx laryngoscope, and obtaining the internal nasal cavity images of all acquisition time points in the corresponding setting period of the target patient.
Extracting the nasal mucosa shape outline, the nasal secretion distribution area and the abnormal protrusion area in the nasal cavity of each acquisition time point in the corresponding setting period of the target patient from the nasal cavity internal image of each acquisition time point in the corresponding setting period of the target patient, and overlapping and comparing the nasal mucosa shape outline of each acquisition time point in the corresponding setting period of the target patient with the stored reference nasal mucosa shape outline to obtain the nasal mucosa overlapping area of each acquisition time point of the target patient.
The nasal mucosa overlapping area, the nasal secretion distribution area and the nasal cavity internal abnormal bulge area of the target patient corresponding to each acquisition time point form a nasal cavity internal information set of the target patient corresponding to each acquisition time point.
As a further improvement of the present invention, the analysis of the nasal cavity internal state evaluation index of the target patient corresponding to each collection time point in the second step is as follows: matching the specific rhinitis type corresponding to the target patient with the set allowable nasal cavity secretion distribution area and allowable nasal cavity internal abnormal bulge area corresponding to each specific rhinitis type to obtain the allowable nasal cavity secretion distribution area and allowable nasal cavity internal abnormal bulge area corresponding to the target patient, and respectively marking as S1 ' and S2 ′。
And matching the specified rhinitis type corresponding to the target patient with the reference nasal mucosa overlapping area corresponding to each specified rhinitis type, so as to obtain the reference nasal mucosa overlapping area corresponding to the target patient, and marking as S'.
According to the formulaCalculating the nasal cavity internal state evaluation index phi of the target patient corresponding to each acquisition time pointi Nasal internal state evaluation index expressed as the target patient corresponding to the i-th collection time point, i expressed as the number of each collection time point, i=1, 2>Respectively expressed as the nasal mucosa superposition area, the nasal secretion distribution area and the abnormal protruding area in the nasal cavity of the target patient corresponding to the ith acquisition time point, a1 、a2 、a3 Respectively expressed as the set nasal mucosa overlapping area, nasal secretion distribution area and abnormal bulge area in the nasal cavityInfluence factors.
In a specific embodiment, the method collects the internal information of the nasal cavity at each collection time point in the corresponding setting period of the target patient, and analyzes the internal state evaluation index of the nasal cavity at each collection time point of the target patient, so that the accuracy and the reliability of the internal state evaluation result of the nasal cavity corresponding to the target patient are guaranteed to the greatest extent, the persuasion of the internal state analysis result of the nasal cavity corresponding to the target patient is improved, and accurate and visual data are provided for the analysis of the severity of rhinitis corresponding to the subsequent target patient.
3. Patient respiratory information acquisition and analysis: and acquiring the respiratory information of each acquisition time point in the corresponding setting period of the target patient to obtain a respiratory information set of each acquisition time point of the target patient, and analyzing respiratory state evaluation indexes of each acquisition time point of the target patient.
As a further improvement of the present invention, in the third step, the respiration information of each acquisition time point in the set period corresponding to the target patient is acquired, and the specific acquisition mode is as follows: the nasal resistance meter is used for collecting the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity and the nasal inhalation resistance value of the right nasal cavity at each collection time point in the corresponding setting period of the target patient, so that the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity and the nasal inhalation resistance value of the right nasal cavity of the target patient at each collection time point are obtained.
And acquiring the nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity at each acquisition time point in the corresponding setting period of the target patient through a nasal respiration meter to obtain the nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity of the target patient at each acquisition time point.
The respiratory information set of the target patient corresponding to each collecting time point is formed by the nasal exhalation resistance value of the left nasal cavity, the nasal inhalation resistance value of the left nasal cavity, the nasal ventilation flow of the left nasal cavity, the nasal exhalation resistance value of the right nasal cavity, the nasal inhalation resistance value of the right nasal cavity and the nasal ventilation flow of the right nasal cavity of the target patient corresponding to each collecting time point.
As a further improvement of the present invention, the third step is to analyze the respiratory state evaluation index of the target patient corresponding to each acquisition time point, and the specific analysis mode is as follows: matching the specified rhinitis type corresponding to the target patient with the set reference respiratory information set corresponding to each specified rhinitis type to obtain the reference respiratory information set corresponding to the target patient, extracting the nasal exhalation resistance value, the nasal inhalation resistance value, the nasal ventilation flow, the nasal exhalation resistance value, the nasal inhalation resistance value and the nasal ventilation flow corresponding to the target patient, which are respectively recorded as hq'Left side 、xq′Left side 、tq′Left side 、hq′Right side 、xq′Right side And tq'Right side 。
According to the formulaCalculating the left nasal cavity respiratory state evaluation index of the target patient corresponding to each acquisition time point, wherein the left nasal cavity respiratory state evaluation index is->Left nasal respiratory state evaluation index, expressed as target patient corresponding to the ith acquisition time point,/>The left nasal cavity nasal exhalation resistance value, the nasal inhalation resistance value and the nasal cavity ventilation flow rate corresponding to the ith acquisition time point of the target patient are respectively expressed as a4 、a5 、a6 The set values of the left nasal cavity nasal exhalation resistance, the left nasal cavity nasal inhalation resistance and the influence factors corresponding to the left nasal cavity ventilation flow are respectively expressed.
According to the formulaCalculating the right nasal cavity respiratory state evaluation index of the target patient corresponding to each acquisition time point, wherein the right nasal cavity respiratory state evaluation index is->Right nasal respiratory state evaluation index expressed as the target patient corresponding to the ith acquisition time point, +.>The right nasal cavity nasal exhalation resistance value, the nasal inhalation resistance value and the nasal cavity ventilation flow rate corresponding to the ith acquisition time point of the target patient are respectively expressed as a7 、a8 、a9 The set values of the right nasal cavity nasal exhalation resistance, the right nasal cavity nasal inhalation resistance and the influence factors corresponding to the right nasal cavity ventilation flow are respectively expressed.
According to the formulaCalculating respiratory state evaluation indexes gamma of the target patient corresponding to each acquisition time periodi A respiratory state evaluation index, b, expressed as the target patient corresponding to the ith acquisition period1 、b2 The set left nasal cavity respiratory state evaluation index and the right nasal cavity respiratory state evaluation index are respectively expressed as weight factors corresponding to the set left nasal cavity respiratory state evaluation index and the right nasal cavity respiratory state evaluation index.
In a specific embodiment, the invention effectively solves the problems of singleness and unilateralness of monitoring and analyzing the severity of the rhinitis corresponding to the patient in the prior art by acquiring the respiratory information of each acquisition time point in the corresponding setting period of the target patient and analyzing the respiratory state evaluation index of the target patient corresponding to each acquisition time point, and increases the reliability and the accuracy of analyzing the severity of the rhinitis of the patient.
4. Patient rhinitis severity analysis: and analyzing the rhinitis severity evaluation coefficient corresponding to the target patient to obtain the rhinitis severity evaluation coefficient corresponding to the target patient, and analyzing the rhinitis severity level corresponding to the target patient.
As a further improvement of the present invention, in the fourth step, the rhinitis severity assessment coefficient corresponding to the target patient is analyzed, and a specific analysis formula thereof is as follows:θ is expressed as a rhinitis severity evaluation coefficient corresponding to the target patient, b3 、b4 Respectively representing the set nasal cavity internal state evaluation index and the weight factor corresponding to the respiratory state evaluation index.
As a further improvement of the present invention, in the fourth step, the severity level of rhinitis corresponding to the target patient is analyzed in the following specific analysis manner: and matching the rhinitis severity evaluation coefficient corresponding to the target patient with the rhinitis severity evaluation coefficient threshold corresponding to the set various rhinitis severity grades to obtain the rhinitis severity grade corresponding to the target patient.
In a specific embodiment, the rhinitis severity assessment coefficient corresponding to the target patient is analyzed, and the rhinitis severity level corresponding to the target patient is obtained through analysis, so that the persuasion of the rhinitis severity analysis of the patient is improved, and the follow-up development of targeted treatment on the patient is promoted.
5. Rhinitis severity display and treatment: and displaying the rhinitis severity level corresponding to the target patient, and performing corresponding treatment.
Referring to fig. 2, a second aspect of the present invention provides a disease data acquisition and analysis system, comprising: the nasal secretion information acquisition and analysis module of the patient, the nasal mucosa state acquisition and analysis module of the patient, the breathing information acquisition and analysis module of the patient, the rhinitis severity display and processing module and the storage library.
The nasal secretion information acquisition and analysis module of the patient is respectively connected with the nasal mucosa state acquisition and analysis module of the patient, the respiratory information acquisition and analysis module of the patient and the storage library, the nasal mucosa state acquisition and analysis module of the patient is respectively connected with the rhinitis severity analysis module of the patient and the storage library, the respiratory information acquisition and analysis module of the patient is connected with the rhinitis severity analysis module of the patient, and the rhinitis severity analysis module of the patient is connected with the rhinitis severity display and processing module.
The nasal secretion information acquisition and analysis module is used for acquiring facial state videos of the target patient corresponding to a set period, obtaining facial state sub-videos of the target patient corresponding to various nasal discharge behaviors, and analyzing the appointed rhinitis type corresponding to the target patient.
The nasal mucosa state acquisition and analysis module is used for acquiring the internal information of the nasal cavity of each acquisition time point in the corresponding setting period of the target patient, and analyzing the internal state evaluation index of the nasal cavity of the target patient corresponding to each acquisition time point.
And the patient respiratory information acquisition and analysis module is used for acquiring respiratory information of each acquisition time point in the corresponding set period of the target patient and analyzing respiratory state evaluation indexes of the target patient corresponding to each acquisition time point.
And the rhinitis severity analysis module is used for analyzing the rhinitis severity assessment coefficient corresponding to the target patient and analyzing the rhinitis severity level corresponding to the target patient.
And the rhinitis severity display and processing module is used for displaying the rhinitis severity level corresponding to the target patient and performing corresponding processing.
The storage library is used for storing nasal secretion images corresponding to various secretion states, storing appointed rhinitis types corresponding to the first nasal secretion state and the thick state, storing appointed rhinitis types corresponding to the subsequent nasal secretion state and storing reference nasal mucosa shape outlines.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.