CN115919286A - Disease data acquisition and analysis method and system - Google Patents
Disease data acquisition and analysis method and system Download PDFInfo
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- 238000004458 analytical method Methods 0.000 title claims abstract description 72
- 201000010099 disease Diseases 0.000 title claims abstract description 24
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 24
- 210000003928 nasal cavity Anatomy 0.000 claims abstract description 189
- 206010039083 rhinitis Diseases 0.000 claims abstract description 149
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- 230000000241 respiratory effect Effects 0.000 claims abstract description 53
- 230000028327 secretion Effects 0.000 claims description 138
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- 210000002850 nasal mucosa Anatomy 0.000 claims description 40
- 238000009423 ventilation Methods 0.000 claims description 33
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 27
- 206010039101 Rhinorrhoea Diseases 0.000 claims description 26
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- 210000001331 nose Anatomy 0.000 claims description 13
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Abstract
The invention relates to the technical field of disease data acquisition and analysis, and particularly discloses a disease data acquisition and analysis method and a disease data acquisition and analysis system. On one hand, the evaluation indexes of the internal states of the nasal cavities of the target patients corresponding to the acquisition time points are analyzed, so that the accuracy and the reliability of the evaluation results of the internal states of the nasal cavities of the target patients are guaranteed to the maximum extent, the persuasion of the analysis results of the internal states of the nasal cavities of the target patients is improved, and accurate and visual data are provided for the follow-up analysis of the severity of rhinitis of the target patients. On the other hand, the respiratory state evaluation indexes of the target patient corresponding to the acquisition time points are analyzed, so that the problem of singleness and one-sidedness of monitoring and analyzing the severity of rhinitis corresponding to the patient in the prior art is effectively solved, and the reliability and the accuracy of analyzing the severity of rhinitis of the patient are improved.
Description
Technical 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 a disease data acquisition and analysis system.
Background
With the rapid development of science and technology, the application field of data acquisition and analysis becomes wider, wherein the most remarkable is the data acquisition and data analysis of diseases, and because of the characteristics of intellectualization, high efficiency and the like, the method provides more convenient and effective diagnosis results for patients, and becomes an important diagnosis mode for keeping population health.
Due to the influence of social working environment and living environment, a plurality of patients do not pay attention to the rhinitis, so that the rhinitis of the patients is aggravated, a series of diseases are further caused, and the importance of rhinitis data acquisition and analysis is highlighted.
When gathering patient's rhinitis data at present, mainly through detecting inside the nasal cavity to the patient to carry out the diagnosis of rhinitis type to the patient based on patient's the inside data of nasal cavity, the inspection process is comparatively loaded down with trivial details, can't realize corresponding the intellectuality and the high efficiency of rhinitis type analysis to the patient, has further prolonged patient's diagnosis cycle.
At present, when the rhinitis severity of a patient is analyzed, a doctor is mainly used for diagnosing and analyzing nasal cavity data of the patient, the analysis of breathing state data of the patient is ignored, the one-sidedness and subjectivity of the rhinitis severity analysis of the patient are caused, scientific data support is lacked, and certain influence is generated on follow-up treatment of the patient to a certain extent.
Disclosure of Invention
In order to overcome the disadvantages in the background art, embodiments of the present invention provide a disease data acquisition and analysis method and an acquisition and analysis system, which can effectively solve the problems related to the background art.
The purpose of the invention can be realized by the following technical scheme: the invention provides a disease data acquisition and analysis method in a first aspect, which comprises the following steps: 1. collecting and analyzing nasal secretion information of a patient: the method comprises the steps of collecting a face state video corresponding to a set period of a target patient, obtaining a face state sub-video corresponding to each snivel behavior of the target patient, and extracting and analyzing nasal secretion information corresponding to each snivel behavior of the target patient to obtain a designated rhinitis type corresponding to the target patient.
2. Collecting and analyzing the nasal mucosa state of a patient: and acquiring the internal information of the nasal cavity of the target patient at each acquisition time point in the corresponding set period to obtain the internal information set of the nasal cavity of the target patient at each acquisition time point, and analyzing the internal state evaluation index of the nasal cavity of the target patient at each acquisition time point.
3. Collecting and analyzing the respiratory information of the patient: and collecting the respiratory information of each collection time point in the set period corresponding to the target patient to obtain a respiratory information set of each collection time point corresponding to the target patient, and analyzing the respiratory state evaluation index of each collection time point corresponding to the target patient.
4. Analysis of severity of rhinitis in patients: 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 grade corresponding to the target patient.
5. Rhinitis severity display and treatment: and displaying the severity grade of the rhinitis corresponding to the target patient, and performing corresponding treatment.
As a preferable scheme of the invention, in the first step, the nasal secretion information of the target patient corresponding to each nasal discharge behavior is extracted and analyzed, and the specific extraction and analysis steps are as follows: 101: and carrying out image segmentation on the facial state sub-images of the target patient corresponding to the running behaviors to obtain a facial state sub-image set of the target patient corresponding to the running behaviors, and carrying out focusing amplification on the nasal cavity part of the facial state sub-image set of the target patient corresponding to the running behaviors to obtain a focused and amplified nasal cavity part sub-image set of the target patient corresponding to the running behaviors.
102: extracting nasal secretion images corresponding to the running behaviors of the target patient from the focused and amplified nasal part sub-image set corresponding to the running behaviors of the target patient, extracting the nasal secretion images corresponding to the running behaviors of the target patient from the nasal secretion images corresponding to the running behaviors of the target patient, matching the nasal secretion images corresponding to the running behaviors of the target patient with the stored nasal secretion images corresponding to various secretion states to obtain the secretion state corresponding to the running behaviors of the target patient, executing 103 if the secretion state corresponding to the running behaviors of the target patient is thick, and executing 104 if the secretion state corresponding to the running behaviors of the target patient is clear.
103: and matching the thick state of the target patient corresponding to the first nasal discharge behavior with the stored specified rhinitis type of the thick state of the first nasal secretion to obtain the specified rhinitis type of the target patient corresponding to the first nasal discharge behavior, and taking the specified rhinitis type as the specified rhinitis type corresponding to the target patient.
104: comparing the nasal secretion image corresponding to the first running behavior of the target patient with the nasal secretion image corresponding to each running behavior of the target patient, executing 105 if the nasal secretion image corresponding to a certain running behavior of the target patient is inconsistent with the nasal secretion image corresponding to the first running behavior of the target patient, and executing 106 if the nasal secretion image corresponding to each running behavior of the target patient is consistent with the nasal secretion image corresponding to the first running behavior of the target patient.
105: and extracting the nasal secretion image of the snivel behavior, recording the nasal secretion image as a nasal secretion image of a subsequent snivel behavior, matching the nasal secretion image with the stored nasal secretion images corresponding to various secretion states to obtain the secretion state of the target patient corresponding to the subsequent snivel behavior, and matching the thick state of the target patient corresponding to the subsequent snivel behavior with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the thick state if the secretion state of the target patient corresponding to the subsequent snivel behavior is the thick state to obtain the specified rhinitis type of the target patient corresponding to the subsequent snivel behavior as the specified rhinitis type corresponding to the target patient.
106: recording the nasal secretion images of the target patient corresponding to the nasal discharge behaviors as consistent nasal secretion images, taking the secretion state of the target patient corresponding to the first nasal discharge behavior as the secretion state of the target patient corresponding to the subsequent nasal discharge behavior, and matching the secretion state with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the clear water state to obtain the specified rhinitis type of the target patient corresponding to the subsequent nasal discharge behavior as the specified rhinitis type corresponding to the target patient.
As a preferred embodiment of the present invention, in the second step, the nasal cavity internal information at each acquisition time point in the set period corresponding to the target patient is acquired in the following specific acquisition manner: and acquiring the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient by using an electronic nasopharyngoscope to obtain the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient.
Extracting the shape contour of the nasal mucosa, the distribution area of nasal secretion and the abnormal bulge area in the nasal cavity of each acquisition time point in the corresponding set period of the target patient from the image in the nasal cavity of each acquisition time point in the corresponding set period of the target patient, and carrying out coincidence comparison on the shape contour of the nasal mucosa of each acquisition time point in the corresponding set period of the target patient and the stored reference shape contour of the nasal mucosa to obtain the coincidence area of the nasal mucosa of each acquisition time point corresponding to the target patient.
The nasal cavity internal information set of the target patient corresponding to each acquisition time point is formed by the nasal mucosa coincidence area, the nasal cavity secretion distribution area and the abnormal bulge area in the nasal cavity of the target patient corresponding to each acquisition time point.
As a preferred embodiment of the present invention, in the second step, the evaluation index of the internal nasal cavity state of the target patient at each collection time point is analyzed in the following specific manner: matching the designated rhinitis type corresponding to the target patient with the allowable nasal secretion distribution area and the allowable abnormal bulge area in the nasal cavity corresponding to each set designated rhinitis type to obtain the allowable nasal secretion distribution area and the allowable abnormal bulge area in the nasal cavity corresponding to the target patient, and respectively recording the allowable nasal secretion distribution area and the allowable abnormal bulge area as S 1 ' and S 2 ′。
And matching the specified rhinitis type corresponding to the target patient with the set reference nasal mucosa coincidence area corresponding to each specified rhinitis type to obtain the reference nasal mucosa coincidence area corresponding to the target patient, and recording as S'.
According to the formula
Calculating the evaluation index phi of the internal state of the nasal cavity of the target patient corresponding to each acquisition time point i Index of evaluation of the internal nasal State, i, for the target patient at the ith acquisition timeExpressed as the number of the respective acquisition time point, i =1, 2.. And n, e expressed as a natural constant, which is expressed in @>
Respectively representing the coincidence area of the nasal mucosa, the distribution area of nasal secretion and the abnormal bulge area in the nasal cavity of the target patient corresponding to each acquisition time point of the ith acquisition time point, a 1 、a 2 、a 3 Respectively representing the corresponding influence factors of the preset nasal mucosa coincidence area, the nasal secretion distribution area and the abnormal bulge area in the nasal cavity.
As a preferred embodiment of the present invention, in the third step, the breathing 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 value of breathing in of the left nasal cavity, the nasal resistance value of breathing in of right nasal cavity and the nasal resistance value of breathing in of right nasal cavity that correspond to set for each collection time point in the cycle through the nasal resistance meter are gathered, obtain the nasal resistance value of breathing in of the left nasal cavity, the nasal resistance value of breathing in of right nasal cavity and the nasal resistance value of breathing in of right nasal cavity that the target patient corresponds each collection time point.
The nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity of each acquisition time point in the corresponding set period of the target patient are acquired through the nasal respiration measuring instrument, and 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 corresponding to each acquisition time point are obtained.
And the respiratory information set of the target patient corresponding to each acquisition 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 acquisition time point.
As a preferred embodiment of the present invention, in the third step, the respiratory state evaluation index of the target patient at each acquisition time point is analyzed in the following specific manner: the designated rhinitis type corresponding to the target patient is paired with each set designated rhinitis typeAnd matching the corresponding reference respiratory information sets to obtain a reference respiratory information set corresponding to the target patient, and extracting a nasal expiration resistance value, a nasal inspiration resistance value, a nasal ventilation flow rate, a nasal expiration resistance value, a nasal inspiration resistance value and a nasal ventilation flow rate of the reference left nasal cavity, the reference right nasal cavity and the target patient corresponding to the reference left nasal cavity from the reference respiratory information set, wherein the nasal expiration resistance value, the nasal inspiration resistance value and the nasal ventilation flow rate are respectively recorded as hq' Left side of 、xq′ Left side of 、tq′ Left side of 、hq′ Right side 、xq′ Right side And tq' Right side 。
According to the formula
Calculating the evaluation index of the left nasal cavity breathing state corresponding to each collection time point of the target patient, and ` 4 `>
An evaluation index, expressed as the left nasal breathing state evaluated for the target patient at the ith acquisition time point, < '> or <' >>
Respectively representing the left nasal cavity and nose expiration resistance value, the nose inspiration resistance value and the nasal cavity ventilation flow of the target patient corresponding to the ith acquisition time point, a 4 、a 5 、a 6 And the values are respectively expressed as the set corresponding influence factors of the left nasal cavity and nose expiration resistance value, the left nasal cavity and nose inspiration resistance value and the left nasal cavity ventilation flow.
Calculating right nasal cavity respiratory state evaluation indexes of the target patient corresponding to each acquisition time point according to a formula, and recording the right nasal cavity respiratory state evaluation indexes as
According to the formula
Calculating the respiratory state evaluation index, gamma, of the target patient corresponding to each acquisition time period i Respiratory state assessment finger expressed as target patient corresponding to ith acquisition time periodNumber b 1 、b 2 And the weight factors are respectively expressed as the set left nasal cavity breathing state evaluation index and the right nasal cavity breathing state evaluation index.
As a preferred embodiment of the present invention, in the fourth step, the rhinitis severity assessment coefficient corresponding to the target patient is analyzed, and the specific analysis formula is as follows:
theta is expressed as the coefficient for evaluating the severity of rhinitis for the target patient, b 3 、b 4 And the weight factors are respectively expressed as the evaluation indexes of the internal state of the nasal cavity and the corresponding weight factors of the evaluation indexes of the respiratory state.
As a preferred embodiment of the present invention, in the fourth step, the severity grade of rhinitis corresponding to the target patient is analyzed in a specific analysis manner: and matching the rhinitis severity evaluation coefficient corresponding to the target patient with the set rhinitis severity evaluation coefficient threshold corresponding to various rhinitis severity grades to obtain the rhinitis severity grade corresponding to the target patient.
The second aspect of the present invention provides a disease data collecting and analyzing system, comprising: the nasal secretion information acquisition and analysis module is used for acquiring the facial state videos of the target patient corresponding to the set period, obtaining the facial state sub-videos of the target patient corresponding to each nasal discharge behavior, and analyzing the designated rhinitis type corresponding to the target patient.
And the patient nasal mucosa state acquisition and analysis module is used for acquiring the nasal cavity internal information of each acquisition time point in the corresponding set period of the target patient and analyzing the nasal cavity internal state evaluation index of each acquisition time point corresponding to the target patient.
And the patient respiratory information acquisition and analysis module is used for acquiring respiratory information of each acquisition time point in a set period corresponding to the target patient and analyzing respiratory state evaluation indexes of the target patient corresponding to each acquisition time point.
And the patient rhinitis severity analyzing module is used for analyzing the rhinitis severity evaluation coefficient corresponding to the target patient and analyzing the rhinitis severity grade corresponding to the target patient.
And the rhinitis severity display and processing module is used for displaying the rhinitis severity grade corresponding to the target patient and carrying out corresponding processing.
The repository is used for storing nasal secretion images corresponding to various secretion states, storing the first designated rhinitis types corresponding to the thick state of the nasal secretion, storing the designated rhinitis types corresponding to the clear water state of the follow-up nasal secretion, and storing the reference nasal mucosa shape outline.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: the invention realizes the intellectualization and high efficiency of the analysis of the rhinitis type corresponding to the patient by collecting the facial state sub-video corresponding to each nasal discharge behavior of the target patient and analyzing the appointed rhinitis type corresponding to the target patient, thereby making up the defect of diagnosing the rhinitis type corresponding to the patient in the prior art.
According to the invention, the internal information of the nasal cavity of each acquisition time point in the corresponding set period of the target patient is acquired, and the internal state evaluation index of the nasal cavity of each acquisition time point corresponding to the target patient is analyzed, so that the accuracy and reliability of the internal state evaluation result of the nasal cavity corresponding to the target patient are ensured to the maximum 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 subsequent analysis of the severity of rhinitis corresponding to the target patient.
According to the invention, the respiratory information of each acquisition time point in the corresponding set period of the target patient is acquired, and the respiratory state evaluation index of each acquisition time point corresponding to the target patient is analyzed, so that the problem of singleness and sidedness of monitoring and analyzing the severity of rhinitis corresponding to the patient in the prior art is effectively solved, and the reliability and the accuracy of analyzing the severity of rhinitis of the patient are improved.
According to the invention, 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 rhinitis severity analysis of the patient is improved, and the subsequent development of targeted treatment on the patient is promoted.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
FIG. 1 is a flow chart illustrating 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 technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides a disease data collecting and analyzing method, including the following steps: 1. collecting and analyzing nasal secretion information of a patient: the method comprises the steps of collecting a face state video corresponding to a set period of a target patient, obtaining a face state sub-video corresponding to each snivel behavior of the target patient, and extracting and analyzing nasal secretion information corresponding to each snivel behavior of the target patient to obtain a designated rhinitis type corresponding to the target patient.
As a further improvement of the present invention, in the first step, the facial state sub-video of the target patient corresponding to each snivel behavior is obtained by: identifying whether the target patient has snivel behavior from the face state video of the target patient corresponding to the set period, if the target patient has snivel behavior corresponding to the set period, marking the corresponding starting snivel and ending snivel of the target patient as snivel behavior, and counting the number of times of the snivel behavior of the target patient corresponding to the set period.
And extracting the sub-video of the facial state of each snivel behavior in the set period corresponding to the target patient from the video of the facial state of the target patient in the set period corresponding to the target patient to obtain the sub-video of the facial state of each snivel behavior 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: and carrying out image segmentation on the facial state sub-video of the target patient corresponding to each snivel behavior to obtain a facial state sub-image set of the target patient corresponding to each snivel behavior, and carrying out focusing and amplification on the nasal cavity part of the facial state sub-image set of the target patient corresponding to each snivel behavior to obtain a focused and amplified nasal cavity part sub-image set of the target patient corresponding to each snivel behavior.
102: the method comprises the steps of extracting nasal secretion images of a target patient corresponding to various snivel behaviors from a focused and amplified nasal part sub-image set corresponding to the various snivel behaviors of the target patient, extracting the nasal secretion image of the target patient corresponding to the first snivel behavior from the nasal secretion image of the target patient corresponding to the various snivel behaviors, matching the nasal secretion image of the target patient corresponding to the first snivel behavior with the stored nasal secretion images corresponding to various secretion states to obtain the secretion state of the target patient corresponding to the first snivel behavior, executing 103 if the secretion state of the target patient corresponding to the first snivel behavior is thick, and executing 104 if the secretion state of the target patient corresponding to the first snivel behavior is clear.
103: and matching the thick state of the target patient corresponding to the first nasal discharge behavior with the stored specified rhinitis type of the thick state of the first nasal secretion to obtain the specified rhinitis type of the target patient corresponding to the first nasal discharge behavior, and taking the specified rhinitis type as the specified rhinitis type corresponding to the target patient.
104: comparing the nasal secretion image corresponding to the first running behavior of the target patient with the nasal secretion image corresponding to each running behavior of the target patient, executing 105 if the nasal secretion image corresponding to a certain running behavior of the target patient is inconsistent with the nasal secretion image corresponding to the first running behavior of the target patient, and executing 106 if the nasal secretion image corresponding to each running behavior of the target patient is consistent with the nasal secretion image corresponding to the first running behavior of the target patient.
105: and extracting the nasal secretion image of the snivel behavior, recording the nasal secretion image as the nasal secretion image of the subsequent snivel behavior, matching the nasal secretion image with the stored nasal secretion images corresponding to various secretion states to obtain the secretion state of the target patient corresponding to the subsequent snivel behavior, and matching the thick state of the target patient corresponding to the subsequent snivel behavior with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the thick state if the secretion state of the target patient corresponding to the subsequent snivel behavior is the thick state to obtain the specified rhinitis type of the target patient corresponding to the subsequent snivel behavior as the specified rhinitis type corresponding to the target patient.
106: recording the nasal secretion images of the target patient corresponding to the nasal discharge behaviors as consistent nasal secretion images, taking the secretion state of the target patient corresponding to the first nasal discharge behavior as the secretion state of the target patient corresponding to the subsequent nasal discharge behavior, and matching the secretion state with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the clear water state to obtain the specified rhinitis type of the target patient corresponding to the subsequent nasal discharge behavior as the specified rhinitis type corresponding to the target patient.
In a specific embodiment, the method and the device provided by the invention have the advantages that the face state sub-videos corresponding to the nasal discharge behaviors of the target patient are collected, and the designated rhinitis types corresponding to the target patient are analyzed, so that the intellectualization and the high efficiency of the analysis of the rhinitis types corresponding to the patient are realized, and the defect of diagnosing the rhinitis types corresponding to the patient in the prior art is overcome.
2. Collecting and analyzing the nasal mucosa state of a patient: and acquiring the nasal cavity internal information of each acquisition time point in the corresponding set period of the target patient to obtain the nasal cavity internal information set of the target patient corresponding to each acquisition time point, and analyzing the nasal cavity internal state evaluation index of the target patient corresponding to each acquisition time point.
As a further improvement of the present invention, in the second step, the nasal cavity internal information at each acquisition time point in the set period corresponding to the target patient is acquired, and the specific acquisition mode is as follows: and acquiring the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient through an electronic nasopharyngoscope to obtain the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient.
Extracting the shape contour of the nasal mucosa, the distribution area of nasal secretion and the abnormal bulge area in the nasal cavity of each acquisition time point in the corresponding set period of the target patient from the image in the nasal cavity of each acquisition time point in the corresponding set period of the target patient, and carrying out coincidence comparison on the shape contour of the nasal mucosa of each acquisition time point in the corresponding set period of the target patient and the stored reference shape contour of the nasal mucosa to obtain the coincidence area of the nasal mucosa of each acquisition time point corresponding to the target patient.
The nasal cavity internal information set of the target patient corresponding to each acquisition time point is formed by the nasal mucosa coincidence area, the nasal cavity secretion distribution area and the abnormal bulge area in the nasal cavity of the target patient corresponding to each acquisition time point.
As a further improvement of the present invention, in the second step, the evaluation index of the internal state of the nasal cavity of the target patient corresponding to each collection time point is analyzed in the following specific manner: matching the designated rhinitis type corresponding to the target patient with the allowed nasal secretion distribution area and the abnormal bulge area in the allowed nasal cavity corresponding to each set designated rhinitis type to obtain the allowed nasal secretion distribution area and the abnormal bulge area in the allowed nasal cavity corresponding to the target patient, and respectively recording the areas as S 1 ' and S 2 ′。
And matching the designated rhinitis type corresponding to the target patient with the set reference nasal mucosa coincidence area corresponding to each designated rhinitis type to obtain the reference nasal mucosa coincidence area corresponding to the target patient, and recording the reference nasal mucosa coincidence area as S'.
According to the formula
Calculating the evaluation index phi of the internal state of the nasal cavity of the target patient corresponding to each acquisition time point i An index of evaluation of the state of the nasal interior of the target patient at the ith acquisition time point is expressed, i is the number of each acquisition time point, i =1,2, ·>
Respectively representing the coincidence area of the nasal mucosa, the distribution area of nasal secretion and the abnormal bulge area in the nasal cavity of the target patient corresponding to each acquisition time point of the ith acquisition time point, a 1 、a 2 、a 3 Respectively expressed as the corresponding influence factors of the preset nasal mucosa coincidence area, the nasal secretion distribution area and the abnormal bulge area in the nasal cavity.
In a specific embodiment, the nasal cavity internal information of each acquisition time point in the set period corresponding to the target patient is acquired, and the nasal cavity internal state evaluation index of each acquisition time point corresponding to the target patient is analyzed, so that the accuracy and reliability of the nasal cavity internal state evaluation result corresponding to the target patient are guaranteed to the maximum extent, meanwhile, the persuasion of the nasal cavity internal state analysis result corresponding to the target patient is improved, and accurate and visual data are provided for the subsequent analysis of the rhinitis severity degree corresponding to the target patient.
3. Collecting and analyzing the respiratory information of the patient: and collecting the respiratory information of each collection time point in the set period corresponding to the target patient to obtain a respiratory information set of each collection time point corresponding to the target patient, and analyzing the respiratory state evaluation index of each collection time point corresponding to the target patient.
As a further improvement of the present invention, in the third step, the respiratory information of each acquisition time point in the corresponding set period of the target patient is acquired, and the specific acquisition mode is as follows: correspond the nasal resistance value of breathing in of the left nasal cavity of setting for each collection time point in cycle, the nasal of left nasal cavity through the nasal resistance meter and breathe in the resistance value, the nasal resistance value of breathing in of right nasal cavity and gather, obtain the nasal resistance value of breathing in of the left nasal cavity that the target patient corresponds each collection time point, the nasal of left nasal cavity breathes in the resistance value, the nasal of right nasal cavity breathes in the resistance value and the nasal of breathing in the resistance value of right nasal cavity.
The nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity of each acquisition time point in the corresponding set period of the target patient are acquired through the nasal respiration measuring instrument, and 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 corresponding to each acquisition time point are obtained.
And the respiratory information set of the target patient corresponding to each acquisition 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 acquisition time point.
As a further improvement 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 manner: matching the designated rhinitis type corresponding to the target patient with the reference breathing information set corresponding to each set designated rhinitis type to obtain the reference breathing information set corresponding to the target patient, and extracting the nasal expiration resistance value of the reference left nasal cavity, the nasal inspiration resistance value of the reference left nasal cavity, the nasal cavity ventilation flow of the reference left nasal cavity, the nasal expiration resistance value of the reference right nasal cavity, the nasal inspiration resistance value of the reference right nasal cavity and the nasal cavity ventilation flow of the reference right nasal cavity of the target patient from the reference breathing information set corresponding to each set designated rhinitis type, wherein the reference breathing information set is recorded as hq' Left side of 、xq′ Left side of 、tq′ Left side of 、hq′ Right side 、xq′ Right side And tq' Right side 。
According to the formula
Calculating the evaluation index of the left nasal cavity breathing state corresponding to each collection time point of the target patient, and ` 4 `>
Left nasal breathing expressed as the target patient corresponding to the ith acquisition time pointStatus evaluation index->
Respectively expressed as the left nasal cavity and nasal cavity exhalation resistance value, the nasal cavity inhalation resistance value and the nasal cavity ventilation flow rate of the target patient corresponding to the ith acquisition time point, a 4 、a 5 、a 6 And the values are respectively expressed as the set corresponding influence factors of the left nasal cavity and nose expiration resistance value, the left nasal cavity and nose inspiration resistance value and the left nasal cavity ventilation flow.
According to the formula
Calculating right nasal cavity respiration status evaluation index, corresponding to each collection time point, of the target patient>
An evaluation index, expressed as the right nasal breathing state evaluated for the target patient at the ith acquisition time point, < '> or <' >>
Respectively representing the right nasal cavity and nose expiration resistance value, the nose inspiration resistance value and the nasal cavity ventilation flow of the target patient corresponding to the ith acquisition time point, a 7 、a 8 、a 9 And the values are respectively expressed as the set corresponding influence factors of the exhalation resistance value of the right nasal cavity and the nasal inhalation resistance value of the right nasal cavity and the ventilation flow of the right nasal cavity.
According to the formula
Calculating the respiratory state evaluation index, gamma, of the target patient corresponding to each acquisition time period i Expressed as an index of the evaluation of the respiratory state of the target patient for the ith acquisition period, b 1 、b 2 And the weight factors are respectively expressed as the set left nasal cavity breathing state evaluation index and the right nasal cavity breathing state evaluation index.
In a specific embodiment, the respiratory information of each acquisition time point in the set period corresponding to the target patient is acquired, and the respiratory state evaluation index of each acquisition time point corresponding to the target patient is analyzed, so that the problem of singleness and one-sidedness in monitoring and analyzing the severity of rhinitis corresponding to the patient in the prior art is effectively solved, and the reliability and the accuracy of analyzing the severity of rhinitis of the patient are improved.
4. Analysis of severity of rhinitis in patients: 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 grade 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 the specific analysis formula is as follows:
theta is expressed as the coefficient for evaluating the severity of rhinitis for the target patient, b 3 、b 4 And the weight factors are respectively expressed as the evaluation indexes of the internal state of the nasal cavity and the corresponding weight factors of the evaluation indexes of the respiratory state.
As a further improvement of the present invention, in the fourth step, the severity grade of rhinitis corresponding to the target patient is analyzed in a specific analysis manner: and matching the rhinitis severity evaluation coefficient corresponding to the target patient with the set rhinitis severity evaluation coefficient threshold corresponding to various rhinitis severity grades to obtain the rhinitis severity grade corresponding to the target patient.
In a specific embodiment, 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 subsequent development of targeted treatment on the patient is promoted.
5. Rhinitis severity display and treatment: and displaying the severity grade of the rhinitis corresponding to the target patient, and carrying out corresponding treatment.
Referring to fig. 2, a second aspect of the present invention provides a disease data collecting and analyzing system, including: the nasal secretion information acquisition and analysis module for the patient, the nasal mucosa state acquisition and analysis module for the patient, the respiratory information acquisition and analysis module for the patient, the rhinitis severity display and processing module and the storage library.
The patient nasal secretion information acquisition and analysis module is respectively connected with the patient nasal mucosa state acquisition and analysis module, the patient respiratory information acquisition and analysis module and the storage library, the patient nasal mucosa state acquisition and analysis module is respectively connected with the patient rhinitis severity analysis module and the storage library, the patient respiratory information acquisition and analysis module is connected with the patient rhinitis severity analysis module, and the patient rhinitis severity analysis module and the rhinitis severity display and processing module are connected.
The nasal secretion information acquisition and analysis module is used for acquiring the facial state videos of the target patient corresponding to the set period, obtaining the facial state sub-videos of the target patient corresponding to each nasal discharge behavior, and analyzing the designated rhinitis type corresponding to the target patient.
And the patient nasal mucosa state acquisition and analysis module is used for acquiring the nasal cavity internal information of each acquisition time point in the corresponding set period of the target patient and analyzing the nasal cavity internal state evaluation index of each acquisition time point corresponding to the target patient.
And the patient respiratory information acquisition and analysis module is used for acquiring the respiratory information of each acquisition time point in the corresponding set period of the target patient and analyzing the respiratory state evaluation index of the target patient corresponding to each acquisition time point.
And the patient rhinitis severity analysis module is used for analyzing the rhinitis severity evaluation coefficient corresponding to the target patient and analyzing the rhinitis severity grade 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 carrying out corresponding processing.
The storage library is used for storing nasal secretion images corresponding to various secretion states, storing the appointed rhinitis types corresponding to the thick state of the nasal secretion for the first time, storing the appointed rhinitis types corresponding to the clear water state of the follow-up nasal secretion, and storing the reference nasal mucosa shape outline.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. A method for disease data collection and analysis, comprising:
1. collecting and analyzing nasal secretion information of a patient: acquiring a facial state video corresponding to a set period of a target patient, obtaining a facial state sub-video corresponding to each snivel behavior of the target patient, and extracting and analyzing nasal secretion information corresponding to each snivel behavior of the target patient to obtain a specified rhinitis type corresponding to the target patient;
2. collecting and analyzing the nasal mucosa state of a patient: acquiring the nasal cavity internal information of each acquisition time point in a set period corresponding to the target patient to obtain a nasal cavity internal information set of the target patient corresponding to each acquisition time point, and analyzing the nasal cavity internal state evaluation index of the target patient corresponding to each acquisition time point;
3. patient respiratory information acquisition and analysis: collecting the respiratory information of each collection time point in the corresponding set period of the target patient to obtain a respiratory information set of the target patient corresponding to each collection time point, and analyzing the respiratory state evaluation index of the target patient corresponding to each collection time point;
4. analysis of severity of rhinitis in patients: 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 grade corresponding to the target patient;
5. rhinitis severity display and treatment: and displaying the severity grade of the rhinitis corresponding to the target patient, and performing corresponding treatment.
2. The disease data collection and analysis method of claim 1, wherein: in the first step, nasal secretion information of the target patient corresponding to each nasal discharge behavior is extracted and analyzed, and the specific extraction and analysis steps are as follows:
101: performing image segmentation on the facial state sub-video of the target patient corresponding to each snivel behavior to obtain a facial state sub-image set of the target patient corresponding to each snivel behavior, and performing focusing amplification on the nasal cavity part of the facial state sub-image set of the target patient corresponding to each snivel behavior to obtain a focused and amplified nasal cavity part sub-image set of the target patient corresponding to each snivel behavior;
102: extracting nasal secretion images of the target patient corresponding to the running behaviors of each time from the sub-image set of the nasal part focused and amplified in the running behaviors corresponding to the target patient, extracting nasal secretion images of the target patient corresponding to the running behaviors of each time from the nasal secretion images of the target patient corresponding to the running behaviors of each time, matching the nasal secretion images of the target patient corresponding to the running behaviors of each time with the stored nasal secretion images corresponding to various secretion states to obtain the secretion state of the target patient corresponding to the running behaviors of each time, executing 103 if the secretion state of the target patient corresponding to the running behaviors of each time is thick, and executing 104 if the secretion state of the target patient corresponding to the running behaviors of each time is clear water;
103: matching the thick state of the target patient corresponding to the first nasal discharge behavior with the stored specified rhinitis type of the thick state of the first nasal secretion to obtain the specified rhinitis type of the target patient corresponding to the first nasal discharge behavior, and taking the specified rhinitis type as the specified rhinitis type corresponding to the target patient;
104: comparing the nasal secretion image corresponding to the first running behavior of the target patient with the nasal secretion image corresponding to each running behavior of the target patient, executing 105 if the nasal secretion image corresponding to a certain running behavior of the target patient is inconsistent with the nasal secretion image corresponding to the first running behavior of the target patient, and executing 106 if the nasal secretion image corresponding to each running behavior of the target patient is consistent with the nasal secretion image corresponding to the first running behavior of the target patient;
105: extracting the nasal secretion image of the snivel behavior, recording the nasal secretion image as a nasal secretion image of a subsequent snivel behavior, matching the nasal secretion image with stored nasal secretion images corresponding to various secretion states to obtain the secretion state of the target patient corresponding to the subsequent snivel behavior, and matching the thick state of the target patient corresponding to the subsequent snivel behavior with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the thick state if the secretion state of the target patient corresponding to the subsequent snivel behavior is thick, so as to obtain the specified rhinitis type of the target patient corresponding to the subsequent snivel behavior, which is used as the specified rhinitis type corresponding to the target patient;
106: recording the nasal secretion images of the target patient corresponding to the nasal discharge behaviors as consistent nasal secretion images, taking the secretion state of the target patient corresponding to the first nasal discharge behavior as the secretion state of the target patient corresponding to the subsequent nasal discharge behavior, and matching the secretion state with the stored specified rhinitis type of the subsequent nasal secretion corresponding to the clear water state to obtain the specified rhinitis type of the target patient corresponding to the subsequent nasal discharge behavior as the specified rhinitis type corresponding to the target patient.
3. The disease data collection and analysis method of claim 1, wherein: in the second step, the nasal cavity internal information of each acquisition time point in the corresponding set period of the target patient is acquired, and the specific acquisition mode is as follows:
acquiring the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient through an electronic nasopharyngoscope to obtain the internal images of the nasal cavity at each acquisition time point in the corresponding set period of the target patient;
extracting the shape contour of the nasal mucosa, the distribution area of nasal secretion and the abnormal bulge area in the nasal cavity of each acquisition time point in the corresponding set period of the target patient from the image in the nasal cavity of each acquisition time point in the corresponding set period of the target patient, and performing coincidence comparison on the shape contour of the nasal mucosa of each acquisition time point in the corresponding set period of the target patient and the stored reference shape contour of the nasal mucosa to obtain the coincidence area of the nasal mucosa of each acquisition time point corresponding to the target patient;
the nasal mucosa coincidence area, the nasal secretion distribution area and the abnormal bulge area in the nasal cavity 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.
4. A disease data collection and analysis method according to claim 3, wherein: in the second step, the evaluation index of the internal state of the nasal cavity of the target patient corresponding to each acquisition time point is analyzed in the following specific analysis mode:
matching the designated rhinitis type corresponding to the target patient with the allowable nasal secretion distribution area and the allowable abnormal bulge area corresponding to each set designated rhinitis type to obtain the allowable nasal secretion distribution area and the allowable abnormal bulge area corresponding to the target patient, and respectively marking as S' 1 And S' 2 ；
Matching the designated rhinitis type corresponding to the target patient with the set reference nasal mucosa coincidence area corresponding to each designated rhinitis type to obtain the reference nasal mucosa coincidence area corresponding to the target patient, and recording as S';
according to the formula
Calculating the evaluation index phi of the internal state of the nasal cavity of the target patient corresponding to each acquisition time point i An index of evaluation of the state of the nasal interior is expressed as the number of the target patient at the ith collection time point, i is expressed as the number of each collection time point, i =1,2, ·>
Respectively expressed as the nasal mucosa weight of the target patient corresponding to each acquisition time point of the ithArea of occlusion, area of nasal secretion distribution, area of abnormal bulge in nasal cavity, a 1 、a 2 、a 3 Respectively representing the corresponding influence factors of the preset nasal mucosa coincidence area, the nasal secretion distribution area and the abnormal bulge area in the nasal cavity.
5. The disease data collection and analysis method of claim 4, wherein: in the third step, the breathing information of each acquisition time point in the corresponding set period of the target patient is acquired, and the specific acquisition mode is as follows:
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 of a target patient at each collection time point in a corresponding set period through a nasal resistance meter to obtain 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;
acquiring the nasal cavity ventilation flow of the left nasal cavity and the nasal cavity ventilation flow of the right nasal cavity of a target patient at each acquisition time point in a corresponding set period through a nasal respiration measuring instrument 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;
and the respiratory information set of the target patient corresponding to each acquisition 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 acquisition time point.
6. The disease data collection and analysis method of claim 5, wherein: 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 mode:
setting the designated rhinitis type corresponding to the target patient and the reference breath corresponding to each designated rhinitis typeAnd matching the information sets to obtain a reference respiratory information set corresponding to the target patient, extracting a nasal expiration resistance value, a nasal inspiration resistance value, a nasal ventilation flow rate, a nasal expiration resistance value, a nasal inspiration resistance value and a nasal ventilation flow rate of the reference left nasal cavity, the reference right nasal cavity and the target patient corresponding to the target patient from the reference respiratory information set, and recording the values as hq' Left side of 、xq′ Left side of 、tq′ Left side of 、hq′ Right side 、xq′ Right side And tq' Right side ；
According to the formula
Calculating the evaluation index of the left nasal cavity breathing state corresponding to each collection time point of the target patient, and ` 4 `>
An evaluation index, expressed as the left nasal breathing state evaluated for the target patient at the ith acquisition time point, < '> or <' >>
Respectively representing the left nasal cavity and nose expiration resistance value, the nose inspiration resistance value and the nasal cavity ventilation flow of the target patient corresponding to the ith acquisition time point, a 4 、a 5 、a 6 Respectively representing the set left nasal cavity and nose expiration resistance value, the left nasal cavity and nose inspiration resistance value and the influence factors corresponding to the left nasal cavity and nose ventilation flow;
calculating right nasal cavity respiratory state evaluation indexes of the target patient corresponding to each acquisition time point according to a formula, and recording the right nasal cavity respiratory state evaluation indexes as
According to the formula
Calculating the respiratory state evaluation index, gamma, of the target patient corresponding to each acquisition time period i Expressed as the target patient corresponds toRespiratory state assessment index for i acquisition periods, b 1 、b 2 And the weight factors are respectively expressed as the set left nasal cavity breathing state evaluation index and the right nasal cavity breathing state evaluation index.
7. The disease data collection and analysis method of claim 6, wherein: and in the fourth step, analyzing the rhinitis severity evaluation coefficient corresponding to the target patient, wherein the concrete analysis formula is as follows:
theta is expressed as the coefficient for evaluating the severity of rhinitis for the target patient, b 3 、b 4 And the evaluation indexes are respectively expressed as weight factors corresponding to the set evaluation indexes of the internal states of the nasal cavity and the set evaluation indexes of the respiratory states.
8. The disease data collection and analysis method of claim 1, wherein: and in the fourth step, analyzing the severity grade of the rhinitis corresponding to the target patient, wherein the specific analysis mode is as follows: and matching the rhinitis severity evaluation coefficient corresponding to the target patient with the set rhinitis severity evaluation coefficient threshold corresponding to various rhinitis severity grades to obtain the rhinitis severity grade corresponding to the target patient.
9. A disease data collection and analysis system, characterized in that: the method comprises the following steps:
the nasal secretion information acquisition and analysis module is used for acquiring the facial state video of the target patient corresponding to a set period, obtaining the facial state sub-video of each nasal discharge behavior of the target patient, and analyzing the designated rhinitis type corresponding to the target patient;
the patient nasal mucosa state acquisition and analysis module is used for acquiring the nasal cavity internal information of each acquisition time point in a set period corresponding to a target patient and analyzing the nasal cavity internal state evaluation index of each acquisition time point corresponding to the target patient;
the patient respiratory information acquisition and analysis module is used for acquiring respiratory information of each acquisition time point in a set period corresponding to a target patient and analyzing a respiratory state evaluation index of the target patient corresponding to each acquisition time point;
the patient rhinitis severity analysis module is used for analyzing the rhinitis severity evaluation coefficient corresponding to the target patient and analyzing the rhinitis severity grade corresponding to the target patient;
the rhinitis severity display and processing module is used for displaying the corresponding rhinitis severity grade of the target patient and carrying out corresponding processing;
the storage library is used for storing nasal secretion images corresponding to various secretion states, storing the appointed rhinitis types corresponding to the thick state of the nasal secretion for the first time, storing the appointed rhinitis types corresponding to the clear water state of the follow-up nasal secretion, and storing the reference nasal mucosa shape outline.
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