CN116759075A - Psychological disorder inquiry method, device, equipment and medium - Google Patents
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Abstract
The invention relates to the technical field of artificial intelligence and intelligent medical treatment, and discloses a psychological disorder inquiry method, device, equipment and medium, which comprise the following steps: receiving personal information and disorder information input by a patient in response to a patient-triggered inquiry operation; performing cause identification on the disorder information to obtain a cause corresponding to the disorder information; collecting facial images of the patient, and identifying micro expressions corresponding to the facial images; and outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression, so that a doctor can diagnose the patient according to the auxiliary inquiry information. The method can improve the accuracy of on-line inquiry.
Description
Technical Field
The invention relates to the technical field of artificial intelligence and intelligent medical treatment, in particular to a psychological disorder inquiry method, device, equipment and medium.
Background
With the rapid development of economic technology, great improvement is brought to the life of substances of people. However, the development of the economic technology brings about the acceleration of the social progress rhythm, brings greater pressure to the mind and body life of people, and is easy to produce psychological health problems, so that the psychological health problems are a common problem in the current society, and the value and life style of people are rapidly changed under the diversified social and economic system. Different age groups can be expected to lack safety in future life more or less, and can not be changed adaptively to rapid changes of environment, so that psychological diseases tend to cause anxiety, depression, interpersonal sensitivity and even suicide, and therefore, in order to solve the psychological problems, it is very important to know the psychological states of people in time, and to reasonably predict and receive psychological dispersion of psychological doctors.
For patients, psychological diseases are not controlled by pain of physiological diseases, psychological problem diagnosis and treatment are difficult to actively take place, meanwhile, due to subjective rejection consciousness of the patients, problems can be intentionally avoided and facts are hidden, the final evaluation result and judgment accuracy are affected, in the intelligent medical field, the patients are subjected to on-line inquiry, however, the current on-line inquiry mode is usually adopted to conduct letter communication, and is different from face-to-face communication, on-line inquiry is improved in flexibility, but the current on-line inquiry is mostly conducted by the patients and doctors, and some patients cannot select video inquiry due to privacy and other reasons, information which can be expressed by letter communication is limited, so that the patients cannot accurately and comprehensively express own disease conditions and causes, and the on-line inquiry accuracy is poor.
Disclosure of Invention
The invention provides an artificial intelligence psychological barrier inquiry method, an artificial intelligence psychological barrier inquiry device, computer equipment and a medium, which aim to solve the technical problem of poor accuracy of on-line inquiry.
In a first aspect, there is provided a psychological disorder inquiry method comprising:
receiving personal information and disorder information input by a patient in response to a patient-triggered inquiry operation;
Performing cause identification on the disorder information to obtain a cause corresponding to the disorder information;
collecting facial images of the patient, and identifying micro expressions corresponding to the facial images;
and outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro expression.
In a second aspect, there is provided a psychological disorder inquiry apparatus comprising:
the receiving module is used for responding to the inquiry operation triggered by the patient and receiving personal information and disorder information input by the patient;
the identification module is used for identifying the etiology of the disease information to obtain the etiology corresponding to the disease information;
the acquisition module is used for acquiring the facial image of the patient and identifying the micro expression corresponding to the facial image;
and the output module is used for outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro expression.
In a third aspect, a computer device is provided comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the psychological barrier inquiry method described above when the computer program is executed by the processor.
In a fourth aspect, a computer readable storage medium is provided, the computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the psychological barrier inquiry method described above.
In the scheme realized by the psychological disorder inquiry method, the psychological disorder inquiry device, the computer equipment and the storage medium, the personal information and the disease information input by the patient can be received in response to the inquiry operation triggered by the patient; performing cause identification on the disorder information to obtain a cause corresponding to the disorder information; the facial image of the patient is acquired, the micro-expression corresponding to the facial image is identified, and the auxiliary inquiry information corresponding to the patient is output according to the personal information, the etiology and the micro-expression, so that a doctor diagnoses the patient according to the auxiliary inquiry information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic view of an application environment of a central disorder inquiry method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for central disorder inquiry according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a central disorder inquiry system according to one embodiment of the present invention;
FIG. 4 is a schematic diagram of a device for diagnosing disorders in a center according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of another embodiment of a computer device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The psychological barrier inquiry method provided by the embodiment of the invention can be applied to an application environment as shown in fig. 1, wherein a client communicates with a server through a network. The method comprises the steps that a client can respond to inquiry operation triggered by a patient, personal information and disorder information input by the patient are received, then cause identification is conducted on the disorder information to obtain cause corresponding to the disorder information, then face images of the patient are collected, micro-expressions corresponding to the face images are identified, finally auxiliary inquiry information corresponding to the patient is output according to the personal information, the cause and the micro-expressions, so that a doctor can diagnose the patient according to the auxiliary inquiry information.
Referring to fig. 2, fig. 2 is a flowchart of a psychological disorder inquiry method according to an embodiment of the present invention, including the following steps:
s10: personal information and condition information entered by the patient is received in response to a patient-triggered interrogation operation.
The patient can trigger the inquiry operation on the terminal, such as clicking an inquiry button, or by browsing a webpage and selecting a corresponding psychological doctor on the webpage to trigger the inquiry operation, after the patient triggers the inquiry operation, an information filling interface and a description interface can be sequentially displayed, and the patient can input personal information such as gender, age, work and the like in the information filling interface. The patient may describe the interface entering information about what they identify as symptoms, such as headache, loss of appetite, or nothing to do.
It should be noted that, the information filling interface may also be displayed before the patient triggers the inquiry operation, the patient is displayed before the inquiry operation is triggered, corresponding personal information is input in the information filling interface, and after the inquiry operation is triggered, the personal information of the patient can be directly obtained.
S20: and carrying out etiology identification on the disease information to obtain the etiology corresponding to the disease information.
In the present invention, the disorder information is composed of text entered by the patient, which includes relevant text describing the disorder and irrelevant text other than the disorder, for example, the disorder information entered by the user is "doctor, i feel nothing about himself or herself, feel meaning nothing about life, i seem depressed", for which the text relating to the disorder is: "do nothing to interest", "feel life meaningless", and "depression", when the etiology recognition is performed, taking the case of recognizing the etiology of depression, recognizing that the condition information has a text capable of representing "depression", defining "depression" as a target semantic meaning, that is, when the condition information has "depression" word, or has related "depression" semantic meaning, recognizing the related text but not the unrelated text, thereby not only improving the accuracy of the etiology recognition, but also reducing the computational overhead, optionally, in some embodiments, the step of "performing the etiology recognition on the condition information to obtain the etiology corresponding to the condition information" may specifically include:
s21: extracting descriptive text for the disorder from the disorder information;
S22: and carrying out etiology recognition on the description text to obtain the etiology corresponding to the disorder information.
It should be noted that, since the condition information is input by the patient, the input text mainly describes the condition content of the patient, but in the process of actually performing online consultation, the patient may not be familiar with the client or the web page of online consultation, so that the input text contains a large number of spaces, or the patient touches a certain key by mistake, so that the input text is not only irrelevant to the condition, but also nonsensical text such as text like "i me" or "11111111", and therefore, in order to improve the efficiency of subsequent consultation, when the validity detection needs to be performed on the condition information, the description text for the condition is extracted when the validity detection passes; when the validity detection fails, a corresponding prompt message is output to inform the patient so that the patient reenters the disease information, that is, optionally, in some embodiments, the step of extracting descriptive text for the disease from the disease information may specifically include:
s211: detecting the validity of the disease information;
s212: when the validity detection of the disease information passes, extracting an information text of the disease information;
S213: performing disorder semantic detection on the information text to obtain a semantic detection result;
s214: based on the semantic detection result, descriptive text for the disorder is extracted from the disorder information.
The validity detection of the invention is to detect whether the Chinese content of the disease information is valid or not and whether the word number of the words is larger than the set word number, the set word number can be set according to practical situations, for example, 25 words are set, for example, for the disease information 'headache', the word number of the text describing the disease is smaller than the set word number although the word content is valid, so that the subsequent diagnosis of doctors is inconvenient, and therefore, for the disease information 'headache', the invention judges that the disease information 'headache' does not pass the validity detection; for another example, the condition information is "doctor, i feel that nothing is done by himself or herself, feel that life is meaningless, i look like depression", the text content is valid, and the word number of the words is larger than the set word number, then the text can be determined, "doctor, i feel that nothing is done by herself, feel that life is meaningless, i feel that he or she is depressed," through validity detection, then the information text of the condition information is extracted, and condition semantic detection is performed on the information text, so as to obtain a semantic detection result, wherein the condition semantic detection of the information text can be realized by, for example, specifically, word segmentation processing can be performed on the information text, the information text is converted into words and phrases, and the parts of speech thereof such as labeled verbs, nouns or prepositions and the like are labeled, then the grammatical relation and hierarchical structure between the words and the phrases are determined, then the actual meanings of the words and the semantic phrases are determined according to the context, and the corresponding information is extracted, finally the condition of the information text is identified through a machine learning algorithm, and finally the condition text is extracted for the condition is described according to the detection result.
S30: and collecting facial images of the patient, and identifying micro-expressions corresponding to the facial images.
For example, image acquisition may be performed on a face of a patient through a camera installed on a terminal, specifically, in consideration of a user privacy problem, before acquisition, prompt information may be issued to a terminal where the patient is located, when the patient triggers a confirmation operation based on the prompt information, the patient is determined to agree to the acquisition, at this time, a face image of the patient is acquired, face key points are extracted from the acquired face image, and micro-expression recognition is performed on the face image based on a preset micro-expression recognition model, that is, optionally, in some embodiments, the step of "acquiring the face image of the patient and recognizing a micro-expression corresponding to the face image" may specifically include:
s31: issuing prompt information of image acquisition to a terminal where a patient is located;
s32: when a confirmation operation of a patient aiming at prompt information is received, collecting a plurality of continuous facial images of the patient in preset time;
s33: extracting face key points of each face image;
s34: based on a preset micro-expression recognition model and the key points of the human face, recognizing the micro-expression of each facial image.
It should be noted that, if only a single facial image is acquired, noise, illumination or the cause of the device itself may occur, so that the quality of the acquired facial image is not very high, or some patients may subconsciously adjust their own expression after learning that image acquisition is required; the above situation may lead to lack of reliability of the facial image, thereby affecting subsequent micro-expression recognition. Therefore, in the invention, a plurality of continuous facial images of a patient in a preset time are collected, then, the face key points of each facial image are extracted, and finally, based on a preset micro-expression recognition model and the face key points, the micro-expression of each facial image is recognized.
Specifically, the geometrical characteristics of the face can be utilized to extract the face characteristic points with invariance of size, rotation and displacement, for example, the positions of key points of the face such as eyes, nose, lips and the like can be extracted. For example, 9 feature points of a face are selected, and the distribution of the key points of the face has angular invariance, namely, 2 eyeball center points, 4 eye corner points, the middle point of two nostrils and 2 mouth corner points.
When face feature extraction is performed, the conventional edge detection operator cannot reliably extract the features of the face, such as the eyes or the area of the lips, because local edge information cannot be effectively organized, so that an algorithm of a minimum absorption homovalue kernel region (Small univalue segment assimilating nucleus, susan) operator can be adopted to extract the features of the face. The principle of Susan operator is: taking a circular area with pixels as radius, namely an area coverage pixel position as a mask, and observing the pixel value of all points of each point in the face image within the area range and the consistency degree of the pixel value of the current point.
It should be noted that, since the shape of lips may be greatly changed due to different facial expressions, and the lip areas are relatively easily disturbed by beard factors, the accuracy of extracting feature points in the lip areas may be greatly affected. Because the position of the mouth corner point is relatively less affected by the expression and the like and is more accurate, the important feature points of the lip region are adopted as the positioning mode of the two mouth corner points.
It can be understood that the judgment of the human micro-expression is mainly focused on the eyes, mouth, eyebrows, cheeks and other parts, while other parts of the human face, such as the forehead, chin and the like, have no great reference value, so that the whole facial image of the patient only needs to pick out the identification area to be identified, and the other areas do not need to be identified, thereby achieving the technical effect of shortening the identification time. Therefore, optionally, in some embodiments, the area to be recognized may be determined in the face image based on the position of the face key point in the face image and the face object corresponding to each face key point, and then the area to be recognized is recognized by the micro-expression recognition model, so as to obtain the micro-expression of the face image, that is, the step of "recognizing the micro-expression of each face image based on the preset micro-expression recognition model and the face key point" may specifically include:
S341: determining a region to be identified in the face image based on the positions of the face key points in the face image and the face objects corresponding to each face key point;
s342: and carrying out microexpressive recognition on the region to be recognized based on a preset microexpressive recognition model to obtain the microexpressive of each facial image.
For convenience of description, taking a face image as an example, after extracting a face key point, determining a position of each face key point and a face object corresponding to the face key point, where the face object may be eyes, eyebrows, a mouth or a nose, then determining the eyes, the eyebrows and the mouth as target face key points, constructing a region to be identified based on the target face key point, and finally only identifying a pose corresponding to the face object in the region to be identified to obtain a micro-expression of the face image, that is, optionally, in some embodiments, the step of performing micro-expression identification on the region to be identified based on a preset micro-expression identification model to obtain a micro-expression of each face image may specifically include:
s3421: determining target face key points in the extracted face key points based on the face objects corresponding to each face key point;
S3422: and acquiring an area of a preset range of the key points of the target face in the face image, and fusing the acquired area to obtain an area to be identified.
For example, specifically, after determining the positions of the eyes, the mouth and the eyebrows in the facial image, taking the length corresponding to the eyes as a radius, taking the eyes as dots, and acquiring a region S1 of the eyes in a preset range in the facial image; likewise, taking the length corresponding to the mouth as a radius, taking the mouth as a dot, and acquiring an area S2 of the mouth in a preset range in the face image; and taking the length corresponding to the eyebrows as a radius, taking the eyebrows as dots, and acquiring an area S3 of the eyebrows in a preset range in the face image. It should be noted that, the length corresponding to the key points of the face refers to: the distance between two pixel points which are farthest from the image corresponding to the characteristic object. After the region S1, the region S2 and the region S3 are obtained, the region S1, the region S2 and the region S3 are communicated, so that a region to be recognized is obtained, and finally, the micro expression corresponding to the facial image is determined according to the gesture corresponding to the facial object in the region to be recognized. For example, if the upper eyelid is lifted to expose more upper edges of the iris and the mouth is large, the micro expression of the patient is surprise; the eyebrows are wrinkled and raised, the inner sides of the eyebrows are twisted, the upper eyelids are lifted, and the irises are exposed, so that the micro expression of the patient is fear; lifting the upper lip, and forming nose-lip grooves on two sides of the nose wing, so that the micro expression of the patient is averse; when the eyebrow is raised, the whole eyebrow keeps pressing downwards, and the micro expression of the patient is sad; when the upper eyelid is lifted and the lower eyelid is tightened, the micro expression of the patient is anger; the eyes are squinted, fish tail lines are formed, the lower eyelid is tightened, lifted, raised, the mouth corners are tilted, nose and lip furrows are formed by stretching, cheeks are raised, and the micro expression of the patient is pleasant and the like.
S40: and outputting corresponding auxiliary inquiry information of the patient according to the personal information, the etiology and the micro expression.
It will be appreciated that the doctor diagnoses the patient based on the auxiliary inquiry information.
After personal information, etiology and micro-expression of the patient are obtained, the estimated symptoms of the patient can be estimated according to the micro-expression, if the eyebrow of the patient is identified to be raised, the whole eyebrow is kept pressed down, namely, the micro-expression of the patient is sad, the estimated symptoms of the patient can be estimated to be depression, then, the occupational and sex information of the patient and the like are extracted from the personal information, and the estimated etiology and the estimated symptoms are combined to output auxiliary inquiry information corresponding to the patient, wherein the auxiliary inquiry information can be: preliminary predictions may be made that the patient may suffer from depression, and in combination with his work and sex, his actual etiology may be that the work pressure is high.
It should be noted that, for a plurality of facial images, the corresponding micro-expressions may include a plurality of pre-estimated symptoms, so in this case, the micro-expressions need to be screened to facilitate the subsequent output of auxiliary inquiry information, that is, optionally, in some embodiments, the step of outputting the corresponding auxiliary inquiry information of the patient according to personal information, etiology and micro-expressions, so that the doctor diagnoses the patient according to the auxiliary inquiry information may specifically include:
S41: filtering the identified micro-expressions based on a preset strategy to obtain filtered micro-expressions;
s42: estimating at least one estimated condition corresponding to the patient according to the filtered microexpressions;
s43: based on the personal information, the etiology and the estimated symptoms, auxiliary inquiry information corresponding to the patient is output, so that a doctor can diagnose the patient according to the auxiliary inquiry information.
Optionally, in some embodiments, the preset strategy may be to reject the micro-expressions having the occurrence frequency less than the preset value, for example, the plurality of micro-expressions include micro-expression a, micro-expression b, micro-expression c, micro-expression d and micro-expression e, where micro-expression a corresponds to pleasure, micro-expression b corresponds to sadness, micro-expression c corresponds to sadness, micro-expression d corresponds to aversion, micro-expression e corresponds to aversion, the preset value is 2, that is, reject micro-expression a, then predict the predicted symptoms corresponding to micro-expression b, micro-expression c, micro-expression d and micro-expression e, respectively, then fuse the same predicted symptoms, determine auxiliary inquiry information in the fused etiology based on personal information and etiology, and finally output auxiliary inquiry information corresponding to the patient according to the auxiliary inquiry information, personal information and etiology, so that the doctor can diagnose the patient according to the auxiliary inquiry information.
For example, specifically, after outputting the auxiliary inquiry information, the doctor may perform an inquiry with a higher tendency according to the auxiliary inquiry information, for example, the auxiliary inquiry information is: the method has the advantages that the female patient is estimated to suffer from depression initially, the working intensity is high, most of men are considered in the working environment, the estimated cause is possibly high working pressure, after the doctor knows the auxiliary inquiry information, the doctor can inquire the female patient from the working angle and provide specific psychological treatment for the female patient, and the problem that the doctor cannot conduct exact inquiry and misdiagnosis is caused only by text communication is avoided, so that the accuracy of online inquiry can be improved.
The invention provides a psychological disorder inquiry method, which is characterized in that in response to inquiry operation triggered by a patient, after personal information and disorder information input by the patient are received, the disorder information is subjected to cause recognition to obtain the cause corresponding to the disorder information, then, a facial image of the patient is acquired, micro-expressions corresponding to the facial image are recognized, finally, auxiliary inquiry information corresponding to the patient is output according to the personal information, the cause and the micro-expressions, so that a doctor can diagnose the patient according to the auxiliary inquiry information.
For further understanding of the psychological disorder inquiry scheme of the present invention, a medical scenario is taken as an example for further explanation, referring to fig. 3, the present invention provides an on-line psychological disorder inquiry system (hereinafter referred to as a system) comprising a doctor end and a patient end, wherein an inquiry flow of the system is as follows:
the patient inputs personal basic information such as age, sex, work property, etc. The portion of the content is entered not only as a reference to the doctor, but also as part of the etiology recognition module within the intelligent recognition module. Because of the basic information of the patient, such as sex, work content, etc., which is greatly different, there may be a difference in the cause of the psychological diseases. For example, when a woman after delivery makes a consultation, the cause of the disease comes from the family and other factors. The etiology recognition module may assign different weights to the basic information of the patient that has significant differences.
The patient describes the major disorder. The part is input by the patient into own main symptoms such as recent sleep abnormality, emotion abnormality and the like. The background of the system can recognize semantic understanding of the part of input of the patient, and if the characters input by the patient are recognized as invalid information, such as all blank spaces, or only one character, such as commas, periods or semicolons, or too few characters, the patient can be required to further input main symptoms, for example, the patient can be prompted to input specific symptoms through a prompt popup window, or the patient is prompted to input characters with the number greater than 25. The main function of the identification function is to ensure that a doctor can acquire the main symptoms of a patient during the first consultation, save the time for the doctor to take the consultation, avoid the doctor to repeatedly inquire the most basic main symptoms of the patient, and the like, quicken the time for the consultation and improve the efficiency for the on-line doctor to take the consultation.
The physician looks at the patient's primary condition and asks the patient for other conditions based on the patient's description.
The patient answers according to the physician's query. After receiving the inquiry of the doctor, the text contents of the patient reply are directly displayed to the doctor on one hand, and the doctor performs subjective etiology and diagnosis according to self-practice experience. On the other hand, the characters replied by the patient can be transmitted into the intelligent recognition module, and the etiology recognition module and the micro expression recognition module in the intelligent recognition module extract information.
a) The etiology recognition module first performs a text process on the text entered by the patient, such as modifying mispronounced words, sensitive word filtering, and the like. The module then identifies the etiology of the patient for his description. For example, the patient types text content to feel that nothing is interesting to do and feel that life is meaningless. The user can feel normal building jumping, and negative emotion is spread throughout life. "at this time, most doctors will primarily judge that the patient suffers from depression based on the text of the patient. But more advanced problems should be identified, at this time, the etiology recognition module will perform semantic understanding and topic classification according to the text of the patient, give the patient the etiology such as "lack of living target positioning" or "confusion of self-value recognition", and prompt the result to the doctor, and assist the doctor in understanding the symptoms of the patient.
b) The micro-expression recognition module will first ask if the patient would like to collect his face picture. If the patient agrees, a face picture of the patient is taken, and a micro-expression recognition model is called. The microexpressive recognition model recognizes which microexpressions the face of the patient has and gives a corresponding disease prediction, such as recognizing that the patient has characteristics of eye cavities, facial dullness, etc., and the model predicts that the patient may suffer from depression. If a patient is identified as having facial muscle tightness, eye distraction, and/or mouth tightness, the model predicts that the patient is likely to suffer from anxiety. The facial features and predictions of the disease are then fed back to the physician, who makes a reference and gives a corresponding reply or diagnosis.
The doctor makes multiple queries to the patient and finally gives prescriptions or regulatory advice.
It can be understood that when a doctor makes multiple queries on a patient, the doctor can acquire the disease information input by the patient for multiple times and acquire the image of the patient for multiple times, and when new information is acquired, the information acquired before is deleted, so that the calculation cost can be reduced, and the privacy of the user can be protected.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
In one embodiment, a psychological disorder inquiry device is provided, and the psychological disorder inquiry device corresponds to the central disorder inquiry method in one-to-one correspondence. As shown in fig. 4, the psychological disorder inquiry apparatus includes a receiving module 101, an identifying module 102, an acquisition module 103, and an output module 104. The functional modules are described in detail as follows:
the receiving module 101 is configured to receive personal information and disorder information input by a patient in response to a patient-triggered inquiry operation.
The identification module 102 is configured to identify the etiology of the disorder information, and obtain the etiology corresponding to the disorder information.
And the acquisition module 103 is used for acquiring the facial image of the patient and identifying the micro expression corresponding to the facial image.
The output module 104 is configured to output auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression.
Optionally, in some embodiments, the identification module 102 may be specifically configured to:
Extracting descriptive text for the disorder from the disorder information;
and carrying out etiology recognition on the description text to obtain the etiology corresponding to the disorder information.
Optionally, in some embodiments, the identification module 102 may be specifically configured to:
detecting the validity of the disease information;
when the validity detection of the disease information passes, extracting an information text of the disease information;
performing disorder semantic detection on the information text to obtain a semantic detection result;
based on the semantic detection result, descriptive text for the disorder is extracted from the disorder information.
Optionally, in some embodiments, the acquisition module 103 may be specifically configured to:
issuing prompt information of image acquisition to a terminal where a patient is located;
when a confirmation operation of a patient aiming at prompt information is received, collecting a plurality of continuous facial images of the patient in preset time;
extracting face key points of each face image;
based on a preset micro-expression recognition model and the key points of the human face, recognizing the micro-expression of each facial image.
Optionally, in some embodiments, the acquisition module 103 may be specifically configured to:
determining a region to be identified in the face image based on the positions of the face key points in the face image and the face objects corresponding to each face key point;
And carrying out microexpressive recognition on the region to be recognized based on a preset microexpressive recognition model to obtain the microexpressive of each facial image.
Optionally, in some embodiments, the determining module 103 may specifically be configured to:
determining target face key points in the extracted face key points based on the face objects corresponding to each face key point;
and acquiring an area of a preset range of the key points of the target face in the face image, and fusing the acquired area to obtain an area to be identified.
Optionally, in some embodiments, the output module 104 may be specifically configured to:
filtering the identified micro-expressions based on a preset strategy to obtain filtered micro-expressions;
estimating at least one estimated symptom corresponding to the patient according to the filtered microexpressions;
based on the personal information, the etiology and the estimated symptoms, auxiliary inquiry information corresponding to the patient is output, so that a doctor can diagnose the patient according to the auxiliary inquiry information.
The invention provides a psychological disorder inquiry device.A receiving module 101 responds to inquiry operation triggered by a patient, and after receiving personal information and disease information input by the patient, a recognition module 102 performs cause recognition on the disease information to obtain disease information corresponding to the disease information The collecting module 103 collects the facial image of the patient and recognizes the micro-expression corresponding to the facial image, and finally, the output module 104 outputs the auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression, so that the doctor can diagnose the patient according to the auxiliary inquiry information, in the psychological disorder inquiry scheme provided by the invention, a first part Aspects of the invention On the other hand, the facial image of the patient is identified, so that the micro-expression corresponding to the facial image is identified, and finally, the auxiliary inquiry information of the patient is output by combining the personal information, the etiology and the micro-expression, so that a doctor can diagnose the patient based on the auxiliary inquiry information conveniently, and the technical problem that the information is missing due to online text communication, so that the accuracy of online inquiry is poor can be solved, namely, the accuracy of online inquiry can be improved.
For specific limitations of the psychological disorder inquiry apparatus, reference may be made to the above limitation of the intelligent question answering method, and no further description is given here. The above-mentioned individual modules in the psychological disorder inquiry apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Alternatively, in some embodiments, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes non-volatile and/or volatile storage media and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external client via a network connection. The computer program, when executed by the processor, performs the functions or steps of a server side of a psychological disorder inquiry method.
Alternatively, in some embodiments, a computer device is provided, which may be a client, and the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external server via a network connection. The computer program is executed by a processor to perform the functions or steps of a method for assessing psychological disorders on the client side.
Optionally, in some embodiments, a computer device is provided, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
receiving personal information and disorder information input by a patient in response to a patient-triggered inquiry operation;
carrying out etiology identification on the disease information to obtain etiology corresponding to the disease information;
collecting face images of a patient, and identifying micro expressions corresponding to the face images;
and outputting corresponding auxiliary inquiry information of the patient according to the personal information, the etiology and the micro expression.
After the OCT image of a patient is acquired, the large blood vessel mask and the small blood vessel mask are segmented in the OCT image by utilizing the preset blood vessel segmentation model, and then the thickness of the large choroid blood vessel in the OCT image and the thickness of the small choroid blood vessel in the OCT image are calculated based on the central concave point, the large blood vessel mask and the small blood vessel mask, so that the problem of poor precision caused by manual measurement can be avoided, and meanwhile, the measurement efficiency is improved, and the accuracy of psychological disorder inquiry is further improved.
Optionally, in some embodiments, a computer readable storage medium is provided, having stored thereon a computer program which when executed by a processor performs the steps of:
receiving personal information and disorder information input by a patient in response to a patient-triggered inquiry operation;
carrying out etiology identification on the disease information to obtain etiology corresponding to the disease information;
collecting face images of a patient, and identifying micro expressions corresponding to the face images;
and outputting corresponding auxiliary inquiry information of the patient according to the personal information, the etiology and the micro expression.
In the psychological disorder inquiry scheme provided by the invention, on one hand, personal information and disorder information input by a patient are received, on the other hand, facial images of the patient are identified, so that micro expressions corresponding to the facial images are identified, and finally, the personal information, the etiology and the micro expressions are combined, auxiliary inquiry information of the patient is output, so that a doctor can conveniently diagnose the patient based on the auxiliary inquiry information, and therefore, the technical problem that information is lost due to online text communication, and the accuracy of online inquiry is poor can be solved, namely, the accuracy of online inquiry can be improved.
It should be noted that, the functions or steps implemented by the computer readable storage medium or the computer device may correspond to the relevant descriptions of the server side and the client side in the foregoing method embodiments, and are not described herein for avoiding repetition.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. A method of assessing psychological disorders comprising:
receiving personal information and disorder information input by a patient in response to a patient-triggered inquiry operation;
Performing cause identification on the disorder information to obtain a cause corresponding to the disorder information;
collecting facial images of the patient, and identifying micro expressions corresponding to the facial images;
and outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro expression.
2. The method of claim 1, wherein the capturing facial images of the patient and identifying the micro-expressions corresponding to the facial images comprises:
issuing prompt information of image acquisition to a terminal where the patient is located;
when the confirmation operation of the patient for the prompt information is received, collecting a plurality of continuous facial images of the patient in preset time;
extracting face key points of each face image;
based on a preset micro-expression recognition model and the face key points, recognizing micro-expressions of each face image;
outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression so that a doctor can diagnose the patient according to the auxiliary inquiry information, wherein the method comprises the following steps: and outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression of each facial image.
3. The psychological disorder inquiry method according to claim 2, wherein the identifying the micro-expression of each facial image based on the preset micro-expression identification model and the face key points comprises:
determining a region to be recognized in the face image based on the positions of the face key points in the face image and the face objects corresponding to each face key point;
and carrying out microexpressive recognition on the region to be recognized based on a preset microexpressive recognition model to obtain the microexpressive of each facial image.
4. The psychological disorder inquiry method according to claim 3, wherein the determining the region to be identified in the face image based on the positions of the face key points in the face image and the face object corresponding to each face key point comprises:
determining target face key points in the extracted face key points based on the face objects corresponding to each face key point;
and acquiring an area of the preset range of the target face key point in the face image, and fusing the acquired area to obtain an area to be identified.
5. The psychological disorder inquiry method according to claim 2, wherein the outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro-expression of each facial image for the doctor to diagnose the patient according to the auxiliary inquiry information comprises:
Filtering the identified micro-expressions based on a preset strategy to obtain filtered micro-expressions;
estimating at least one estimated condition corresponding to the patient according to the filtered microexpressions;
based on the personal information, the etiology and the estimated symptoms, auxiliary inquiry information corresponding to the patient is output.
6. The method according to any one of claims 1 to 5, wherein the identifying the etiology of the disorder information to obtain the etiology of the disorder information comprises:
extracting descriptive text for a disorder from the disorder information;
and carrying out etiology recognition on the descriptive text to obtain the etiology corresponding to the disorder information.
7. The method of claim 6, wherein extracting descriptive text for a disorder from the disorder information comprises:
detecting the validity of the disease information;
when the validity detection of the disease information is passed, extracting an information text of the disease information;
performing disorder semantic detection on the information text to obtain a semantic detection result;
and extracting descriptive text for the symptoms from the symptom information based on the semantic detection result.
8. A psychological disorder inquiry apparatus, comprising:
the receiving module is used for responding to the inquiry operation triggered by the patient and receiving personal information and disorder information input by the patient;
the identification module is used for identifying the etiology of the disease information to obtain the etiology corresponding to the disease information;
the acquisition module is used for acquiring the facial image of the patient and identifying the micro expression corresponding to the facial image;
and the output module is used for outputting auxiliary inquiry information corresponding to the patient according to the personal information, the etiology and the micro expression.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the psychological barrier interrogation method of any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the psychological disorder inquiry method according to any one of claims 1 to 7.
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| CN117649933B (en) * | 2023-11-28 | 2024-05-28 | 广州方舟信息科技有限公司 | Online consultation assistance method and device, electronic equipment and storage medium |
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