CN114743680A - Method, device and storage medium for evaluating non-fault - Google Patents
Method, device and storage medium for evaluating non-fault Download PDFInfo
- Publication number
- CN114743680A CN114743680A CN202210645746.2A CN202210645746A CN114743680A CN 114743680 A CN114743680 A CN 114743680A CN 202210645746 A CN202210645746 A CN 202210645746A CN 114743680 A CN114743680 A CN 114743680A
- Authority
- CN
- China
- Prior art keywords
- test
- state
- user
- client
- text
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Public Health (AREA)
- General Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Medical Informatics (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Library & Information Science (AREA)
- Primary Health Care (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biomedical Technology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Pathology (AREA)
- Artificial Intelligence (AREA)
- Multimedia (AREA)
- Computational Linguistics (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a method, equipment and a storage medium for evaluating an illness, and relates to the field of medical treatment. The method comprises the steps of sending a state test instruction to a first client after obtaining authorization information, wherein the state test instruction comprises a test video segment and a test text, and the test video segment and the test text sent by the same first client are dynamically changed. User status information determined in response to the status test instruction is then received and stored. And then inquiring a plurality of pieces of user state information stored in the first client within a preset time period, matching the state evaluation rule and determining the state evaluation value of the user within the preset time period. And finally, judging whether the state of the user meets the disease-free condition according to the state evaluation value, determining a judgment result and determining whether to send disease-free early warning information to the second client side in real time. Therefore, if the user receives the early warning information of the disease, the early warning information can be timely adjusted or intervention treatment can be carried out in advance, and the early warning information plays a role in preventing the disease from occurring in advance.
Description
Technical Field
The invention relates to the technical field of medical treatment, in particular to a method, equipment and a storage medium for evaluating an ill condition.
Background
According to the current medical theory, the health status of the population can be divided into three types: firstly, the health is not sick; secondly, the disease is not sick; and thirdly, the diseased state is not transmitted, wherein the non-diseased evaluation means that aiming at the second state, when people do not show specific diseased states, active treatment can be carried out so as to eradicate the focus, and the effect of preventing the disease from being gradual is achieved.
However, in the prior art, only specific physiological indexes such as the heart rate, the body fat rate, the physical signs and the blood fat of the user are generally considered in the process of performing the non-illness evaluation, but the evaluation on the mental state of the user is ignored, for example, the user is easily suffered from a psychological disease when being in an anxiety state or a grief state for a long time, and the probability of suffering from the psychological disease is greatly improved under the factors of the psychological disease, so that the accuracy of the non-illness evaluation is low.
Disclosure of Invention
In view of the above, the present invention has been developed to provide an uneventful method, apparatus, and storage medium that overcome or at least partially address the above-discussed problems.
According to a first aspect of the present invention, there is provided an undetected value evaluation method applied to a server, the method including:
randomly sending an evaluation authorization instruction to a first client;
under the condition that the authorization information of the first client responding to the evaluation authorization instruction is obtained, sending a state test instruction to the first client, wherein the state test instruction comprises a test video clip and a test text, and the test video clip and the test text sent by the same first client are dynamically changed;
receiving and storing user state information of the first client, wherein the user state information is determined in response to the state test instruction, the user state information comprises a plurality of facial images and a test text result, and the plurality of facial images are images of the user's face shot when the user watches a plurality of target nodes in the test video clip;
inquiring a plurality of pieces of user state information stored in a preset time period by the first client;
matching the state information of each user with a state evaluation rule according to a time sequence, and determining a state evaluation value of the user in the preset time period;
judging whether the state evaluation value meets an illness-free condition or not, and determining a judgment result;
and determining whether to send an early warning instruction of no illness to the second client side in real time according to the judgment result.
According to a second aspect of the present invention, there is also provided an electronic apparatus, comprising:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform any of the above-described unmistakable methods.
According to a third aspect of the present invention, there is also provided a computer readable storage medium storing a computer program for use in conjunction with an electronic device, the computer program being executable by a processor to perform any of the above-described methods of non-complaint assessment.
In the scheme of the invention, under the condition of obtaining the authorization information of the first client, a state test instruction is sent to the first client, wherein the state test instruction comprises a test video segment and a test text, and the test video segment and the test text sent by the same first client are dynamically changed. And then receiving and storing user state information of the first client, wherein the user state information is determined in response to the state test instruction, inquiring a plurality of pieces of user state information stored in the first client in a preset time period, matching the state evaluation rule, and determining the state evaluation value of the user in the preset time period. And finally, judging whether the state of the user meets the disease-free condition according to the state evaluation value, determining a judgment result and determining whether to send disease-free early warning information to the second client side in real time. Therefore, if the user receives the early warning information of the disease, the early warning information can be timely adjusted or the intervention treatment can be carried out in advance, and the effect of preventing the disease before the disease is prevented is achieved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings.
In the drawings:
FIG. 1 is a flow chart illustrating the steps of a method for disease detection provided by an embodiment of the present invention;
FIG. 2 is a flow chart of steps in another method for non-morbidity assessment in accordance with an embodiment of the present invention;
fig. 3 is a block diagram of an undetected measurement apparatus according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Referring to fig. 1, a flowchart illustrating steps of an unclaimed evaluation method provided by an embodiment of the present invention is shown, and applied to a server, the method may include:
s101, sending a state test instruction to a first client under the condition of obtaining authorization information of the first client, wherein the state test instruction comprises a test video clip and a test text, and the test video clip and the test text sent by the same first client are dynamically changed.
In the embodiment of the invention, the first client runs on the terminal equipment of the user. The terminal device may include a tablet, a mobile phone, a notebook computer, and the like, or may be other intelligent terminal devices integrated with functions of audio-video interaction, multimedia application, and the like. Before the user state information is collected, an evaluation authorization instruction can be randomly sent to the first client side, and the evaluation authorization instruction is used for requesting authorization information of a user. And sending a state test instruction to the first client under the condition of obtaining authorization information of the first client responding to the evaluation authorization instruction. The state test instruction comprises a test video segment and test text, wherein the test video segment refers to a video segment which can be used for evaluating the mental state of the user, and the test text refers to text which can be used for evaluating the mental state of the user. In order to improve the evaluation accuracy, when the server sends a state test instruction to the same client, the corresponding test video segment and the corresponding test text are in dynamic change.
S102, receiving and storing user state information of the first client, wherein the user state information is determined in response to the state test instruction, the user state information comprises a plurality of facial images and test text results, and the facial images are images of the user faces shot when the user watches a plurality of target nodes in the test video clip.
In the embodiment of the invention, the user state information determined by the first client in response to the state test instruction is received and stored in the server. Correspondingly, when the user watches the test video segment, the image of the face of the user can be shot according to a plurality of target nodes in the video segment. And the target node is a preset playing node in the test video clip, and when the test video clip is played to the corresponding target node, an image of the face of the user is shot. Thus, after the user views the test video segment, a plurality of facial images are obtained. Thus, the user status information includes several facial images and test text results.
S103, inquiring a plurality of pieces of user state information stored in the first client within a preset time period.
And S104, matching the state information of each user with a state evaluation rule according to a time sequence, and determining the state evaluation value of the user in the preset time period.
In the embodiment of the invention, a plurality of pieces of user state information are acquired from the time dimension for comprehensive evaluation, so that the precision of non-ill evaluation is improved. The first client may be queried for a number of pieces of user status information stored within a preset time period, where the preset time period may be a time interval from a history date to a date of currently receiving the user status information. The state evaluation rule is used for converting each user state information distributed according to time sequence into a quantization index (namely, a state evaluation value) reflecting the user psychological state. And matching the state information of each user with the state evaluation rule according to the time sequence, so as to determine the state evaluation value of the user in the preset time period. The state evaluation value is used for representing the health condition of the current psychological state of the user. For example, a lower status assessment value indicates a healthier status.
And S105, judging whether the state evaluation value meets the disease-free condition or not, and determining a judgment result.
And S106, determining whether to send the early warning information of the disease failure to the first client side in real time according to the judgment result.
In the embodiment of the invention, whether the state of the user meets the disease-free condition or not is judged according to the obtained state evaluation value. The non-diseased condition may be predetermined based on a state evaluation rule, for example, the non-diseased condition may be that the state evaluation value is greater than or equal to a state threshold value on the premise that the lower the state evaluation value, the healthier the state is.
And when the state evaluation value is judged to meet the non-disease condition, the server side sends non-disease early warning information to the first client side in real time, wherein the non-disease early warning information comprises the state evaluation value and analysis information aiming at the state information of a plurality of users. Therefore, the user receives the early warning information of the disease, and then can timely perform mental state adjustment or perform intervention treatment in advance based on the first client, so that the effect of preventing the disease before the disease is prevented is achieved.
Referring to fig. 2, a flowchart illustrating steps of another non-disease evaluation method provided by an embodiment of the present invention is shown, and applied to a server, the method may include:
s201, randomly determining a test video clip from a test database under the condition of obtaining the authorization information of the first client.
S202, randomly determining a test text from the test database.
S203, combining the test video clip and the test text to obtain a state test instruction, and sending the state test instruction to the first client.
In the embodiment of the invention, before the user state information is collected, an evaluation authorization instruction can be randomly sent to the first client, and the evaluation authorization instruction is used for requesting the authorization information of the user. And sending a state test instruction to the first client under the condition of obtaining authorization information of the first client responding to the evaluation authorization instruction. The state test instruction comprises a test video segment and test text, wherein the test video segment refers to a video segment which can be used for evaluating the mental state of the user, and the test text refers to text which can be used for evaluating the mental state of the user. In order to improve the evaluation accuracy, when the server sends a state test instruction to the same client, the corresponding test video segment and the corresponding test text are in dynamic change. Specifically, when the server generates the state test instruction, the test video clip may be determined from the test database in a random extraction manner, and the test text may also be determined from the test database in a random extraction manner. And combining the test video clip and the test text to complete information packaging so as to generate a state test instruction, and sending the state test instruction to the first client.
In order to further improve the accuracy of the non-ill evaluation in the spatial dimension, the situation that a user already watches a test video segment or answers a test text before and generates a subtler influence when an evaluation test is carried out is avoided. After the test video clip and the test text are determined, content verification is respectively carried out.
In an optional embodiment of the invention, the authorization information may include a user identifier, where the user identifier is associated with the first client, and may be a user ID or the like. After the test video segment is randomly determined from the test database, a plurality of historical state test instructions sent to the first client corresponding to the user identifier may be queried, and the test video segment may be matched with a historical test video segment in the plurality of historical state test instructions. If the video segment with the same content as the test video segment is matched, a new test video segment is randomly determined from the test database, the steps of inquiring the historical state test instruction, matching the video segment, determining whether the segment content is the same and the like are repeated until the test video segment is determined not to generate the state test instruction sent to the first client side, and therefore the situation that a subsequent state evaluation value cannot objectively reflect the psychological state of the user due to the fact that the user watches the state test instruction can be avoided. Making the assessment of disease more accurate.
In an alternative embodiment of the invention, the test text may be formed by combining a plurality of test questions. The test questions may be choice questions for the sake of unifying the test text results fed back by the user and for the sake of easier follow-up evaluation. And randomly extracting a plurality of test questions from the test database and combining the test questions into a test text. The number of test questions per test text may be determined according to actual conditions, for example, in order to balance the user experience and the evaluation accuracy, the test questions per test text may be 25, 30, and 35, etc. And matching the test text with the historical test texts in the plurality of historical state test instructions to determine the similarity of the plurality of test questions. The similarity of each test question can be determined according to the proportion of the same number of the test questions in each two test texts to the total number of the test questions in each test text.
In order to further improve the accuracy of the undetected evaluation in the spatial dimension, the condition that most test texts are already answered by a user before and the condition that the evaluation test is performed generates subtlety influence is avoided. Setting a similar updating condition in advance, where the similar updating condition may be that the similarity of any test question is greater than a similar threshold, for example, the similar threshold is set to 0.08. And if the similarity of any test question meets the similarity updating condition, determining that part of the test questions in the current test text have been answered by the user before and do not have objectivity. Thus, new test texts can be randomly determined from the test database. And repeating the steps of matching the test texts, determining the similarity of the test questions and the like until the similarity of a plurality of test questions corresponding to the new test texts does not accord with the similarity updating condition, and generating a state test instruction for the test video clips and the test texts. Thus, the test video segment and the test text sent for the same first client are dynamically changing.
In an alternative embodiment of the invention, the method may further include:
and acquiring a data updating request sent by a second client, wherein the data updating request comprises the test video segment and the test text, and updating the test database according to the test video segment and the test text. And the user corresponding to the second client is a psychological counseling doctor. In order to ensure the data objectivity of the test video segments and the test texts, the psychological counselor can update the test database periodically, for example, add some test video segments and test texts for expanding the data amount in the test database.
S204, receiving and storing user state information of the first client, wherein the user state information is determined in response to the state test instruction, the user state information comprises a plurality of facial images and test text results, and the facial images are images of the user faces shot when the user watches a plurality of target nodes in the test video clip.
In the embodiment of the invention, the user state information determined by the first client in response to the state test instruction is received and stored in the server. Correspondingly, when the user watches the test video segment, the image of the face of the user can be shot according to a plurality of target nodes in the video segment. And the target node is a preset playing node in the test video clip, and when the test video clip is played to the corresponding target node, an image of the face of the user is shot. Thus, after the user views the test video segment, a plurality of facial images are obtained. Thus, the user status information includes several facial images and test text results.
S205, inquiring a plurality of pieces of user state information stored in the first client in a preset time period.
In the embodiment of the invention, a plurality of pieces of user state information are acquired from the time dimension for comprehensive evaluation, so that the precision of non-ill evaluation is improved. The first client may be queried for a number of pieces of user status information stored within a preset time period, where the preset time period may be a time interval from a history date to a date of currently receiving the user status information. For example, the preset time period may be set according to a time interval between two times of collecting the user status information. If the time interval between every two times of collecting the user state information is 4 days, and if 8 pieces of user state information need to be obtained in the time dimension for comprehensive evaluation, the preset time period is within 28 days before the date of obtaining the current user state information. If the date of the current user state information is 5 months and 29 days, the corresponding preset time period is 5 months and 1 day.
The state evaluation rule is used for converting each user state information distributed according to time sequence into a quantization index (namely, a state evaluation value) reflecting the user psychological state. The state evaluation rule defines a processing step for a plurality of user state information, and the state evaluation value of the user in the preset time period can be determined by matching each user state information with the state evaluation rule according to the time sequence. In one example, facial images and text test results in user status information may be processed separately.
And S206, combining and inputting a plurality of facial images in each user state information into an image recognition model for image matching, and determining an expression evaluation value.
In the embodiment of the invention, a series of facial expressions of a user when watching a target video are determined through the facial images. For example, expressions may include excitement, happiness, suffering, anger, and disgust, among others. When the first classification model is trained, parameter adjustment of the model can be performed based on sample data of eyes, eyebrows, mouths, noses and facial muscles corresponding to each expression. For example, the pupil may dilate when happy and contract when aversive. As another example, the brow may be down-stooped to indicate anger, elevated mouth angle at ease, painful down-tipped mouth angle, etc. The image recognition model may employ neural networks, which are common in the art. And, the image recognition model may include a plurality of image transmission channels, wherein each image transmission channel is used to transmit several facial images in one piece of user status information. Therefore, a middle evaluation value can be obtained in advance according to the plurality of facial images in each piece of user state information, and weighting is carried out according to the plurality of middle evaluation values arranged in time sequence, so that the expression evaluation value is determined. Correspondingly, the more frequently negative, sad and angry emotions are presented, the higher the corresponding expression evaluation value is.
In one example, the first intermediate evaluation value is referenced when determining the first intermediate evaluation value. If the latter intermediate evaluation value is higher than the first intermediate evaluation value, multiplying the first intermediate evaluation value by a first weight, wherein the first weight is greater than 1; if the latter intermediate evaluation value is equal to the first intermediate evaluation value, multiplying the first intermediate evaluation value by a second weight, wherein the second weight is equal to 1; if the latter intermediate evaluation value is smaller than the first intermediate evaluation value, the first intermediate evaluation value is multiplied by a third weight, wherein the third weight is smaller than 1.
And S207, matching the test text results in the user state information in sequence in a preset text evaluation mapping table to determine a text evaluation value.
In the embodiment of the invention, when the test text in the test database is updated, a text evaluation mapping table can also be synchronously set, for example, corresponding test questions and score weights corresponding to test question options are preset in the text evaluation mapping table. Therefore, after the test text results are matched, a plurality of target evaluation values arranged according to the time sequence can be obtained, and the plurality of target evaluation values are weighted, so that the text evaluation values are determined. When weighting the target evaluation value, the weighting may be performed according to the weighting rule of the first weight, the second weight, and the third weight.
And S208, determining the state evaluation value of the user in the preset time period according to the expression evaluation value and the text evaluation value.
In the embodiment of the present invention, the expression evaluation value and the text evaluation value may be accumulated to obtain a state evaluation value, and the state evaluation value is used for representing the health condition of the current psychological state of the user. For example, a lower status assessment value indicates a healthier status.
S209, judging whether the state evaluation value is larger than or equal to a preset state threshold value.
If yes, step S210 is executed, and if not, step S201 is waited to be executed.
And S210, sending early warning information of the diseases to the first client in real time.
And S211, sending the non-disease early warning information to a second client in real time.
S212, an unhealthy precaution strategy determined by the second client in response to the unhealthy early warning information is received and forwarded to the first client.
In the embodiment of the invention, the preset state threshold is a judgment condition for determining whether the disease-free early warning is required. If the state evaluation value is greater than or equal to a preset state threshold value, determining that a problem occurs in the current state of the user, and prompting the user, so as to send disease-free early warning information to the first client in real time, wherein the disease-free early warning information comprises the state evaluation value and analysis information aiming at a plurality of pieces of user state information. Therefore, the user receives the early warning information of the disease-free state based on the first client, and then can timely perform mental state adjustment or perform intervention treatment in advance, so that the effect of preventing the disease-free state in advance is achieved.
In another example, the early warning information of the disease can be sent to the second client at the same time, and in order to further improve the evaluation accuracy and help the user to perform timely intervention and treatment, the psychological counseling doctor can check the early warning information of the disease based on the second client. If the psychological state of the user is determined to have a problem, the psychological counseling doctor can generate an unhealthy precaution strategy through the second client side and forward the strategy to the first client side through the client side. Wherein the disease prevention strategy comprises information such as a pressure release mode, diet recommendation and the like.
In an alternative embodiment of the invention, a status alarm threshold may be set. If the state evaluation value is greater than or equal to the state alarm threshold value, if the state evaluation value is in percentage, the state alarm threshold value is 95 minutes, and when the state evaluation value is greater than or equal to 95 minutes, the server side needs to send the non-sick alarm information to the second client side, so that a psychological counseling doctor can be reminded, and follow-up treatment can be performed on related users in time. For example, a voice connection between the first client and the second client may be established so that the psycho-coaching physician can psychologically persuade the user in a timely manner. Thereby being capable of ensuring the mental health and the safety of the user.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.
Referring to fig. 3, which illustrates an undetected evaluation apparatus provided by an embodiment of the present invention, applied to a server, the apparatus may include:
the test instruction sending module 301 is configured to send a state test instruction to a first client under the condition that authorization information of the first client is obtained, where the state test instruction includes a test video segment and a test text, and the test video segment and the test text sent by the same first client dynamically change.
A status information obtaining module 302, configured to receive and store user status information of the first client, where the user status information is determined in response to the status test instruction, the user status information includes a plurality of facial images and a test text result, and the plurality of facial images are images of a user's face captured when the user views a plurality of target nodes in the test video segment.
A status information query module 303, configured to query a plurality of pieces of user status information stored in a preset time period by the first client.
And an evaluation value determining module 304, configured to match the state information of each user with a state evaluation rule according to a time sequence, and determine a state evaluation value of the user in the preset time period.
A state determination module 305, configured to determine whether the state evaluation value satisfies an unhealthy condition, and determine a determination result.
And an early warning information sending module 306, configured to determine whether to send the non-disease early warning information to the first client in real time according to the determination result.
In an optional embodiment of the invention, the test instruction sending module 301 may include:
and the first random submodule is used for randomly determining the test video clip from the test database.
And the second random submodule is used for randomly determining a test text from the test database.
And the instruction combination submodule is used for combining the test video clip and the test text to obtain a state test instruction and sending the state test instruction to the first client.
In an optional embodiment of the invention, the authorization information includes a user identifier; the first random sub-module may include:
a first random unit for randomly determining a test video segment from the test database.
And the instruction query unit is used for querying a plurality of historical state test instructions sent to the first client corresponding to the user identification.
And the video matching unit is used for matching the test video clip with historical test video clips in a plurality of historical state test instructions.
And the video updating unit is used for randomly determining a new test video segment from the test database if the video segment with the same content as the test video segment is matched.
In an alternative embodiment of the invention, the second random sub-module may include:
and the text combination unit is used for randomly extracting a plurality of test questions from the test database and combining the test questions into a test text.
And the similarity determining unit is used for matching the test text with the historical test texts in the plurality of historical state test instructions to determine the similarity of the plurality of test questions.
And the text updating unit is used for randomly determining a new test text from the test database if the similarity of any test question meets the similarity updating condition.
In an optional embodiment of the invention, the apparatus may further include:
and the update request acquisition module is used for acquiring a data update request sent by a second client, wherein the data update request comprises the test video clip and the test text.
And the database updating module is used for updating the test database according to the test video clip and the test text.
In an alternative embodiment of the invention, the evaluation value determining module 304 may include:
and the expression evaluation submodule is used for combining and inputting a plurality of facial images in each user state information into the image recognition model for image matching to determine an expression evaluation value.
And the text evaluation sub-module is used for matching the test text results in the user state information in sequence in a preset text evaluation mapping table to determine a text evaluation value.
And the state evaluation sub-module is used for determining the state evaluation value of the user in the preset time period according to the expression evaluation value and the text evaluation value.
In an optional embodiment of the invention, the state determining module 305 may further be configured to:
and if the state evaluation value is greater than or equal to a preset state threshold value, judging that the state evaluation value meets the non-disease condition.
In an optional embodiment of the invention, the apparatus may further include:
and the report sending module is used for sending the non-disease early warning information to a second client in real time under the condition that the state evaluation value is judged to meet the non-disease condition.
And the strategy receiving module is used for receiving the disease prevention strategy determined by the second client in response to the disease prevention early warning information and forwarding the disease prevention strategy to the first client.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As is readily imaginable to the person skilled in the art: any combination of the above embodiments is possible, and thus any combination between the above embodiments is an embodiment of the present invention, but the present disclosure is not necessarily detailed herein for reasons of space.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adapted and arranged in one or more devices other than the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
An electronic device, comprising:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the methods of the embodiments described above.
A computer-readable storage medium storing a computer program for use in conjunction with an electronic device, the computer program being executable by a processor to perform the method of the above-described embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The above detailed description is provided for the non-disease evaluation method and the non-disease evaluation device, and the specific examples are applied herein to explain the principle and the implementation of the present invention, and the description of the above embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. An uncomfortableness evaluating method is applied to a server side, and comprises the following steps:
under the condition of obtaining authorization information of a first client, sending a state test instruction to the first client, wherein the state test instruction comprises a test video segment and a test text, and the test video segment and the test text sent by the same first client are dynamically changed;
receiving and storing user state information of the first client, wherein the user state information is determined in response to the state test instruction, the user state information comprises a plurality of facial images and a test text result, and the plurality of facial images are images of the user's face shot when the user watches a plurality of target nodes in the test video clip;
inquiring a plurality of pieces of user state information stored in the first client within a preset time period;
matching the state information of each user with a state evaluation rule according to a time sequence, and determining a state evaluation value of the user in the preset time period;
judging whether the state evaluation value meets an illness-free condition or not, and determining a judgment result;
and determining whether to send the non-sick early warning information to the first client in real time according to the judgment result.
2. The method of claim 1, wherein sending the state test instruction to the first client comprises:
randomly determining a test video clip from a test database;
randomly determining a test text from the test database;
and combining the test video clip and the test text to obtain a state test instruction, and sending the state test instruction to the first client.
3. The method of claim 2, wherein the authorization information includes a user identifier;
the randomly determining a test video clip from a test database includes:
randomly determining a test video clip from a test database;
inquiring a plurality of historical state test instructions sent to a first client corresponding to the user identification;
matching the test video clip with historical test video clips in a plurality of historical state test instructions;
and if the video clip with the same content as the test video clip is matched, randomly determining a new test video clip from the test database.
4. The method of claim 3, wherein said randomly determining test text from said test database comprises:
randomly extracting a plurality of test questions from the test database and combining the test questions into a test text;
matching the test text with historical test texts in a plurality of historical state test instructions to determine the similarity of a plurality of test questions;
and if the similarity of any test question meets the similarity updating condition, randomly determining a new test text from the test database.
5. The method of claim 2, further comprising:
acquiring a data updating request sent by a second client, wherein the data updating request comprises the test video clip and the test text;
and updating the test database according to the test video clip and the test text.
6. The method according to claim 1, wherein the determining the state evaluation value of the user in the preset time period by matching the state information of each user with the state evaluation rule according to the time sequence comprises:
combining and inputting a plurality of facial images in each user state information into an image recognition model for image matching, and determining an expression evaluation value;
in a preset text evaluation mapping table, matching test text results in the user state information in sequence to determine a text evaluation value;
and determining the state evaluation value of the user in the preset time period according to the expression evaluation value and the text evaluation value.
7. The method according to claim 1, wherein the determining whether the user's status satisfies the non-diseased condition according to the status evaluation value, and determining the determination result comprises:
and if the state evaluation value is greater than or equal to a preset state threshold value, judging that the state evaluation value meets the non-disease condition.
8. The method of claim 7, further comprising:
under the condition that the state evaluation value is judged to meet the non-disease condition, transmitting the non-disease early warning information to a second client in real time;
and receiving an unhealthy precaution strategy determined by the second client in response to the unhealthy early warning information, and forwarding the strategy to the first client.
9. An electronic device, comprising:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-8.
10. A computer-readable storage medium storing a computer program for use in conjunction with an electronic device, the computer program being executable by a processor to perform the method of any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210645746.2A CN114743680B (en) | 2022-06-09 | 2022-06-09 | Method, device and storage medium for evaluating non-fault |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210645746.2A CN114743680B (en) | 2022-06-09 | 2022-06-09 | Method, device and storage medium for evaluating non-fault |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114743680A true CN114743680A (en) | 2022-07-12 |
| CN114743680B CN114743680B (en) | 2022-09-06 |
Family
ID=82287279
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210645746.2A Active CN114743680B (en) | 2022-06-09 | 2022-06-09 | Method, device and storage medium for evaluating non-fault |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114743680B (en) |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102012959A (en) * | 2009-09-08 | 2011-04-13 | 刘金硕 | Mathematical modeling method for automatically constructing graph intelligence topic generation cognitive system |
| US20140315168A1 (en) * | 2013-02-12 | 2014-10-23 | Emotient | Facial expression measurement for assessment, monitoring, and treatment evaluation of affective and neurological disorders |
| CN105559802A (en) * | 2015-07-29 | 2016-05-11 | 北京工业大学 | Tristimania diagnosis system and method based on attention and emotion information fusion |
| CN105868560A (en) * | 2016-03-28 | 2016-08-17 | 赤峰学院 | Social psychology survey system |
| CN106236115A (en) * | 2016-08-12 | 2016-12-21 | 渤海大学 | A kind of psychological test system |
| CN106326879A (en) * | 2016-09-08 | 2017-01-11 | 哈尔滨理工大学 | Abnormal micro expression recognition device |
| CN208243563U (en) * | 2017-12-07 | 2018-12-18 | 江苏大学 | Based on the interactive contactless psychology detection therapeutic device of Internet of Things and its system |
| CN109498039A (en) * | 2018-12-25 | 2019-03-22 | 北京心法科技有限公司 | Personality assessment's method and device |
| CN110706786A (en) * | 2019-09-23 | 2020-01-17 | 湖南检信智能科技有限公司 | Non-contact intelligent analysis and evaluation system for psychological parameters |
| US20200066405A1 (en) * | 2010-10-13 | 2020-02-27 | Gholam A. Peyman | Telemedicine System With Dynamic Imaging |
| CN111265226A (en) * | 2020-03-03 | 2020-06-12 | 淮安信息职业技术学院 | System and method for detecting psychological stress management ability |
| CN111427909A (en) * | 2020-01-17 | 2020-07-17 | 吾达软件（武汉）股份有限公司 | Behavior big data and mental health test system based on artificial intelligence |
| CN111477328A (en) * | 2020-03-31 | 2020-07-31 | 北京智能工场科技有限公司 | Non-contact psychological state prediction method |
| CN111933275A (en) * | 2020-07-17 | 2020-11-13 | 兰州大学 | Depression evaluation system based on eye movement and facial expression |
| CN111950381A (en) * | 2020-07-20 | 2020-11-17 | 湖北美和易思教育科技有限公司 | Mental health on-line monitoring system |
| CN111967363A (en) * | 2020-08-10 | 2020-11-20 | 河海大学 | Emotion prediction method based on micro-expression recognition and eye movement tracking |
| US20210045696A1 (en) * | 2019-08-14 | 2021-02-18 | Christian D. Poulin | Assistance in response to predictions in changes of psychological state |
| CN113782200A (en) * | 2021-08-19 | 2021-12-10 | 刘欣 | Psychological risk screening and determining method and device, computer equipment and storage medium |
| CN114155964A (en) * | 2021-12-09 | 2022-03-08 | 孙茜 | Depression patient symptom improvement degree recording and analyzing device |
| CN114171198A (en) * | 2021-11-26 | 2022-03-11 | 智恩陪心(北京)科技有限公司 | Multi-mode mental health analysis method based on sand table images, texts and videos |
| CN216053888U (en) * | 2021-07-07 | 2022-03-15 | 郑州大学 | Hypertension patient anxiety and depression screening and managing system combining internet technology |
-
2022
- 2022-06-09 CN CN202210645746.2A patent/CN114743680B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102012959A (en) * | 2009-09-08 | 2011-04-13 | 刘金硕 | Mathematical modeling method for automatically constructing graph intelligence topic generation cognitive system |
| US20200066405A1 (en) * | 2010-10-13 | 2020-02-27 | Gholam A. Peyman | Telemedicine System With Dynamic Imaging |
| US20140315168A1 (en) * | 2013-02-12 | 2014-10-23 | Emotient | Facial expression measurement for assessment, monitoring, and treatment evaluation of affective and neurological disorders |
| CN105559802A (en) * | 2015-07-29 | 2016-05-11 | 北京工业大学 | Tristimania diagnosis system and method based on attention and emotion information fusion |
| CN105868560A (en) * | 2016-03-28 | 2016-08-17 | 赤峰学院 | Social psychology survey system |
| CN106236115A (en) * | 2016-08-12 | 2016-12-21 | 渤海大学 | A kind of psychological test system |
| CN106326879A (en) * | 2016-09-08 | 2017-01-11 | 哈尔滨理工大学 | Abnormal micro expression recognition device |
| CN208243563U (en) * | 2017-12-07 | 2018-12-18 | 江苏大学 | Based on the interactive contactless psychology detection therapeutic device of Internet of Things and its system |
| CN109498039A (en) * | 2018-12-25 | 2019-03-22 | 北京心法科技有限公司 | Personality assessment's method and device |
| US20210045696A1 (en) * | 2019-08-14 | 2021-02-18 | Christian D. Poulin | Assistance in response to predictions in changes of psychological state |
| CN110706786A (en) * | 2019-09-23 | 2020-01-17 | 湖南检信智能科技有限公司 | Non-contact intelligent analysis and evaluation system for psychological parameters |
| CN111427909A (en) * | 2020-01-17 | 2020-07-17 | 吾达软件（武汉）股份有限公司 | Behavior big data and mental health test system based on artificial intelligence |
| CN111265226A (en) * | 2020-03-03 | 2020-06-12 | 淮安信息职业技术学院 | System and method for detecting psychological stress management ability |
| CN111477328A (en) * | 2020-03-31 | 2020-07-31 | 北京智能工场科技有限公司 | Non-contact psychological state prediction method |
| CN111933275A (en) * | 2020-07-17 | 2020-11-13 | 兰州大学 | Depression evaluation system based on eye movement and facial expression |
| CN111950381A (en) * | 2020-07-20 | 2020-11-17 | 湖北美和易思教育科技有限公司 | Mental health on-line monitoring system |
| CN111967363A (en) * | 2020-08-10 | 2020-11-20 | 河海大学 | Emotion prediction method based on micro-expression recognition and eye movement tracking |
| CN216053888U (en) * | 2021-07-07 | 2022-03-15 | 郑州大学 | Hypertension patient anxiety and depression screening and managing system combining internet technology |
| CN113782200A (en) * | 2021-08-19 | 2021-12-10 | 刘欣 | Psychological risk screening and determining method and device, computer equipment and storage medium |
| CN114171198A (en) * | 2021-11-26 | 2022-03-11 | 智恩陪心(北京)科技有限公司 | Multi-mode mental health analysis method based on sand table images, texts and videos |
| CN114155964A (en) * | 2021-12-09 | 2022-03-08 | 孙茜 | Depression patient symptom improvement degree recording and analyzing device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114743680B (en) | 2022-09-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110516161B (en) | Recommendation method and device | |
| US20200365275A1 (en) | System and method for assessing physiological state | |
| US20220392625A1 (en) | Method and system for an interface to provide activity recommendations | |
| KR20170061222A (en) | The method for prediction health data value through generation of health data pattern and the apparatus thereof | |
| US20190027142A1 (en) | Communication system and communication control method | |
| CN103561652A (en) | Method and system for assisting patients | |
| CN102149319A (en) | Alzheimer's cognitive enabler | |
| WO2019242155A1 (en) | Voice recognition-based health management method and apparatus, and computer device | |
| US20170344713A1 (en) | Device, system and method for assessing information needs of a person | |
| CN109659009B (en) | Emotion management method and device and electronic equipment | |
| US20080154894A1 (en) | System for cross-acquisition of physiological and psychological information | |
| CN112908481A (en) | Automatic personal health assessment and management method and system | |
| CN111063429A (en) | Medical consultation method, device, equipment and computer-readable storage medium | |
| CN113035232A (en) | Psychological state prediction system, method and device based on voice recognition | |
| KR102670492B1 (en) | Method and apparatus for psychological counselingusing artificial intelligence | |
| CN115862868A (en) | Psychological assessment system, psychological assessment platform, electronic device and storage medium | |
| Nie et al. | Conversational ai therapist for daily function screening in home environments | |
| CN116741360B (en) | Doctor inquiry and service quality evaluation system based on intelligent terminal | |
| CN114743680B (en) | Method, device and storage medium for evaluating non-fault | |
| WO2023163236A1 (en) | Database integrating treatment/therapeutic systems, and method for implementing same | |
| RU2415645C1 (en) | Method of diagnosing falsity of reported information by dianamics of parametres of person's nonverbal behaviour | |
| CN114971658A (en) | Anti-fraud propaganda method, system, electronic equipment and storage medium | |
| CN110767282B (en) | Health record generation method and device and computer readable storage medium | |
| Metu et al. | Evaluating fluency in aphasia: Fluency scales, trichotomous judgements, or machine learning | |
| CN112185516A (en) | Human-computer interaction based mental construction method and device for heavy smart personnel and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |