CN115691763A

CN115691763A - Remote psychological consultation method, device, equipment and storage medium

Info

Publication number: CN115691763A
Application number: CN202211402870.2A
Authority: CN
Inventors: 胡童
Original assignee: Individual
Current assignee: Individual
Priority date: 2022-11-10
Filing date: 2022-11-10
Publication date: 2023-02-03

Abstract

The application discloses a remote psychological consultation method, a device, equipment and a storage medium, wherein the remote psychological consultation method comprises the following steps: when the terminal of the person to be checked establishes video communication with the terminal of the person to be checked selected by the person to be checked, acquiring a face image of the person to be checked; inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result; and determining the state information of the examinee based on the expression recognition result, sending the state information to an examinee terminal, and storing the expression recognition result and the state information of the examinee to a corresponding database. According to the method and the device, when the examiner and the examinee perform video communication for psychological consultation examination, the expression information and the state information of the examinee are identified, and the examiner adjusts the treatment means according to the expression information and the state information of the examinee, so that the treatment effect and experience of the patient are improved.

Description

Remote psychological consultation method, device, equipment and storage medium

Technical Field

The present application relates to the field of computer data processing, and in particular, to a method, an apparatus, a device, and a storage medium for remote psychological consultation.

Background

With the increase of social pressure, the proportion of patients suffering from psychological diseases is larger and larger, and most of psychological counseling work needs patients to go to relevant hospitals to carry out counseling work, so that the time and the labor are consumed, the efficiency is low, and the psychological conditions of the patients are difficult to detect and record quickly, so that the remote psychological counseling platform provides a convenient channel for treating the psychological diseases for the relevant patients.

In the psychological counseling platform in the prior art, a psychological counseling physician and a psychological disease patient are usually communicated for treatment through a video chat device, but problems of poor voice visualization degree, large psychological pressure of the psychological disease patient facing the psychological counseling physician remotely and the like can also occur, so that the psychological disease patient has poor treatment effect and poor user experience.

Disclosure of Invention

The application mainly aims to provide a remote psychological consultation method, a device, equipment and a storage medium, and aims to solve the technical problems that a patient suffering from a disease is poor in treatment effect and poor in user experience in the prior art.

To achieve the above objects, the present application provides a remote psychological counseling method, including:

when the terminal of the person to be checked establishes video communication with the terminal of the person to be checked selected by the person to be checked, acquiring a face image of the person to be checked;

inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result;

and determining the state information of the examinee based on the expression recognition result, sending the state information to an examinee terminal, and storing the expression recognition result and the state information of the examinee to a corresponding database.

Optionally, before the step of acquiring the face image of the examinee when the terminal of the examinee establishes video communication with the terminal of the examinee selected by the examinee, the method includes:

acquiring first data information containing inspector data and second data information containing inspected person data;

determining inspection recommendation information based on the first data information and the second data information, and sending the inspection recommendation information to an inspected person terminal;

and determining inspector selection information of the inspected person, and establishing video communication between the terminal of the corresponding inspector and the terminal of the inspected person based on the inspector selection information.

Optionally, the step of determining the check recommendation information based on the first data information and the second data information includes:

determining a first feature vector of the first data information and a second feature vector of the second data information;

calculating feature distances of the first feature vector and the second feature vector;

and determining the inspector information with the characteristic distance smaller than a preset distance threshold value as inspection recommendation information.

acquiring a face training sample and an expression label of the face training sample;

and carrying out iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model meeting precision conditions.

Optionally, the step of performing iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model meeting the precision condition includes:

inputting the face training sample into a preset model to be trained to obtain a predicted expression result;

performing difference calculation on the predicted expression result and the expression label of the face training sample to obtain an error result;

judging whether the error result meets an error standard indicated by a preset error threshold range or not based on the error result;

and if the error result does not meet the error standard indicated by the preset error threshold range, returning to the step of inputting the face training sample into a preset model to be trained to obtain a predicted expression result, and stopping training until the training error result meets the error standard indicated by the preset error threshold range to obtain an expression recognition model meeting the precision condition.

Optionally, the step of determining the state information of the examinee based on the expression recognition result includes:

acquiring a mapping relation between expression information and state information;

and determining the state information of the checked person based on the expression recognition result and the mapping relation.

Optionally, the step of obtaining the mapping relationship between the expression information and the state information includes:

acquiring a state evaluation result of expression information based on expert experience;

and matching the expression information with the state information based on the state bid evaluation result to obtain a mapping relation between the expression information and the state information.

The present application also provides a remote psychological counseling apparatus, comprising:

the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring a face image of a person to be checked when the terminal of the person to be checked establishes video communication with a terminal of the person to be checked selected by the person to be checked;

the expression recognition module is used for inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result;

and the determining module is used for determining the state information of the examinee based on the expression recognition result, sending the state information to the examinee terminal, and storing the expression recognition result and the state information of the examinee in a corresponding database.

The present application also provides a remote psychological counseling apparatus, the remote psychological counseling apparatus comprising: a memory, a processor, and a program stored on the memory for implementing the remote psychological counseling method,

the memory is used for storing a program for realizing the remote psychological counseling method;

the processor is used for executing a program for implementing the remote psychological counseling method so as to implement the steps of the remote psychological counseling method.

The present application also provides a storage medium having stored thereon a program for implementing a remote psychological counseling method, the program being executed by a processor to implement the steps of the remote psychological counseling method.

Compared with the prior art that the problems of poor voice visualization degree, large psychological pressure of a psychological disease patient on a psychological consulting doctor in a remote way and the like can occur, so that the psychological disease patient has poor treatment effect and poor user experience, in the method, when the terminal of a person to be checked and the terminal of the person to be checked selected by the person to be checked establish video communication, the face image of the person to be checked is acquired; inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result; and determining the state information of the examinee based on the expression recognition result, sending the state information to an examinee terminal, and storing the expression recognition result and the state information of the examinee to a corresponding database. In other words, in the application, when the examiner and the examinee perform video communication for psychological consultation examination, the expression information and the state information of the examinee are identified, and the examiner adjusts the treatment means according to the expression information and the state information of the examinee, so that the treatment effect and experience of the patient are improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

Fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application;

FIG. 2 is a schematic flow chart of a remote psychological counseling method according to a first embodiment of the present application;

fig. 3 is a schematic block diagram of a remote psychological consultation apparatus according to the present application.

The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

As shown in fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present application.

The terminal in the embodiment of the application may be a PC, or may be a mobile terminal device having a display function, such as a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3) player, an MP4 (Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4) player, a portable computer, or the like.

As shown in fig. 1, the terminal may include: a processor 1001, e.g. a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.

Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the mobile terminal is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer and tapping) and the like for recognizing the attitude of the mobile terminal; of course, the mobile terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.

Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating device, a network communication module, a user interface module, and a remote psychological counseling program.

In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be used to invoke a remote psychological counseling program stored in the memory 1005.

Referring to fig. 2, an embodiment of the present application provides a remote psychological counseling method, including:

step S100, when the terminal of the person to be checked establishes video communication with the terminal of the person to be checked selected by the person to be checked, the face image of the person to be checked is obtained;

step S200, inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result;

step S300, based on the expression recognition result, determining the state information of the examinee, sending the state information to the examinee terminal, and storing the expression recognition result and the state information of the examinee in a corresponding database.

In this embodiment, the specific application scenarios may be:

The method comprises the following specific steps:

in this embodiment, the remote psychological counseling method is applied to a remote psychological counseling apparatus.

In this embodiment, the examinee is usually a patient who needs psychological consultation and examination, and the examiner is usually a doctor who provides psychological consultation and examination; the terminals of the inspected person and the inspectors can be mobile terminals, such as mobile phones, tablets and the like, and can also be PC terminals; the video communication refers to communication of voice and images of a person transmitted in real time between network terminals based on the internet and a mobile internet terminal, so that an inspector and an inspected person can see a video picture of the other party through the video communication, hear the voice sent by the other party, and establish the video communication, which requires that the two parties have video acquisition equipment, such as a camera module, and voice acquisition equipment, such as a microphone module.

In this embodiment, the mode of acquiring the face image of the examinee by the apparatus is to acquire a face image sent to the apparatus by a camera of the examinee terminal, where the face image may be a video or a picture, the face image includes key point information of the face of the examinee, and the key point information of the face includes points such as eyebrows, eyes, and mouth.

In another embodiment, if the face image does not contain the face key point information, a reminder can be set to the terminal of the examiner and the terminal of the examinee, so that the face image is ensured to contain the face key point information of the examinee, and the accuracy of expression recognition of the examinee is ensured.

In the step S100, before the step of acquiring the face image of the examinee when the terminal of the examinee establishes video communication with the terminal of the examinee selected by the examinee, the method includes the following steps a100-a200:

a100, obtaining a face training sample and an expression label of the face training sample;

in this embodiment, the face training sample image is a face sample used for model training, and specifically, the face training sample image is a face image including face information. The mode of acquiring the face training sample image may be to download the face image containing the face information on the internet, or to acquire the face image containing the face information by using a camera. It should be noted that the face training sample image includes several face images. The expression label of the face training sample is a label for calibrating the expression of the image of the face training sample, for example, the face training sample a, and the facial expression in the image of the face training sample a is happy, that is, the expression label of the face training sample a is happy.

Step A200, performing iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model meeting the precision condition.

In this embodiment, the apparatus performs iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model satisfying precision conditions, specifically, a model to be trained is newly created, and the model to be trained is a model based on a corresponding relationship between the face training sample and the expression label. The model to be trained does not have a high degree of accuracy.

Specifically, the step a200 includes the following steps a210-a240:

step A210, inputting the face training sample into a preset model to be trained to obtain a predicted expression result;

in this embodiment, the device inputs the face training sample to a preset model to be trained to obtain a predicted expression result, wherein the model to be trained has a model for predicting the expression of the face training sample.

Step A220, carrying out difference calculation on the predicted expression result and the expression label of the face training sample to obtain an error result;

in this embodiment, the device performs difference calculation on the predicted expression result and the expression label of the face training sample to obtain an error result, or obtains an error result through loss function convergence.

Step A230, based on the error result, judging whether the error result meets an error standard indicated by a preset error threshold range;

in this embodiment, the preset error threshold includes a preset mean square error threshold, and as known to those skilled in the art, the smaller the mean square error threshold is, the more accurate the representative model is, and the determining whether the training error result satisfies the error criterion indicated by the preset error threshold includes: and judging whether the mean square error result is smaller than a preset mean square error threshold value or not.

Step A240, if the error result does not meet the error standard indicated by the preset error threshold range, returning to the step of inputting the face training sample into a preset model to be trained to obtain a predicted expression result, and stopping training until the training error result meets the error standard indicated by the preset error threshold range to obtain an expression recognition model meeting the precision condition.

In this embodiment, if the error result does not satisfy the error standard indicated by the preset error threshold range, the device returns to the step of inputting the face training sample to a preset model to be trained to obtain a predicted expression result, and stops training until the training error result satisfies the error standard indicated by the preset error threshold range to obtain an expression recognition model satisfying the precision condition.

In another embodiment, the device can also segment the face training sample to obtain a plurality of key point images on the face image, respectively identify the key point images, judge the identification result in the key point images, and judge the final expression identification result according to a plurality of identification results, so as to improve the accuracy of the face image judgment.

in this embodiment, the device inputs the face image into a preset expression recognition model, and performs expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result, specifically, based on the expression recognition model satisfying the precision condition, the device has a function of accurately recognizing the face image to obtain the expression recognition result.

In this embodiment, the device determines the state information of the examinee, that is, determines the current state of the examinee by the expression of the examinee based on the expression recognition result, for example, if the expression recognition result of the examinee is confused, the device determines that the state of the examinee is uneasy, and transmits the uneasy state of the examinee to the examinee terminal, and the examinee can perform adjustment of the corresponding examination mode according to the state of the examinee, thereby improving the treatment effect and experience of the patient.

In this embodiment, the device stores the expression recognition result and the state information of the examinee into the corresponding database, so that the examinee can check the whole consultation examination and treatment state of the examinee after examination, and a scheme for next psychological examination is formulated according to the state, and the treatment effect and experience of the patient are improved.

Specifically, the step S300 includes the following steps S310 to S320:

step S310, acquiring a mapping relation between the expression information and the state information;

in this embodiment, the apparatus obtains a mapping relationship between the expression information and the status information, that is, a preset mapping between the expression information and the status information, for example, a mapping between confused expression information and insecure status information, that is, when the expression information is confused, the status information is correspondingly in an insecure status.

Specifically, the step S310 includes the following steps S311 to S312:

step S311, obtaining the state evaluation result of the expert experience on the expression information;

in this embodiment, the device obtains the state evaluation result of the expert experience on the expression information, that is, evaluates the state information corresponding to the expression information according to the expert experience.

And step S312, matching the expression information with the state information based on the state bid evaluation result to obtain the mapping relation between the expression information and the state information.

In this embodiment, the device matches the expression information with the state information based on the state bid evaluation result to obtain a mapping relationship between the expression information and the state information.

Step S320, determining the status information of the examinee based on the expression recognition result and the mapping relationship.

In this embodiment, the apparatus determines the status information of the examinee based on the expression recognition result and the mapping relationship.

Compared with the problems that the speech visualization degree is poor, the psychological stress of a psychological disease patient facing a psychological consulting doctor is large in a remote mode, the treatment effect of the psychological disease patient is poor, and the user experience is poor in the prior art, in the remote psychological consulting method, when the terminal of a person to be checked and the terminal of the person to be checked selected by the person to be checked establish video communication, the face image of the person to be checked is obtained; inputting the face image into a preset expression recognition model, and carrying out expression recognition processing on the face image based on the expression recognition model to obtain an expression recognition result; and determining the state information of the examinee based on the expression recognition result, sending the state information to an examinee terminal, and storing the expression recognition result and the state information of the examinee to a corresponding database. In other words, in the application, when the examiner and the examinee perform video communication for psychological consultation examination, the expression information and the state information of the examinee are identified, and the examiner adjusts the treatment means according to the expression information and the state information of the examinee, so that the treatment effect and experience of the patient are improved.

Based on the first embodiment described above, the present application further provides another embodiment, in the step S100, before the step of acquiring the face image of the examinee when the terminal of the examinee establishes video communication with the terminal of the examinee selected by the examinee, the method includes the following steps B100 to B300:

step B100, acquiring first data information containing inspector data and second data information containing inspected person data;

in this embodiment, the first data information is the data information of the examiner, including the work history, work proof, direction of excellence, occupation, name, etc. of the examiner as the service person providing psychological consultation and treatment; the second data information is the data information of the examinee, and comprises information such as pathological condition information, occupation and name of psychological diseases of the examinee.

Step B200, determining the inspection recommendation information based on the first data information and the second data information, and sending the inspection recommendation information to the terminal of the inspected person;

in this embodiment, the device determines the examination recommendation information based on the first data information and the second data information, and sends the examination recommendation information to the examinee terminal, that is, according to the information of the examinee and the examinee, the examinee is provided with the information of the examinee and recommends the examinee correspondingly suitable for treating the relevant pathology, and the examinee can select the preferred examinee by himself, so as to improve the treatment effect and experience of the patient.

Specifically, the step B200 includes the following steps B210 to B230:

step B210, determining a first feature vector of the first data information and a second feature vector of the second data information;

in this embodiment, a device determines a first feature vector of the first data information and a second feature vector of the second data information, where the first data information and the second data information are text information, and a text feature extraction method is used to determine the first feature vector of the first data information and the second feature vector of the second data information.

Step B220, calculating a feature distance between the first feature vector and the second feature vector;

in this embodiment, the apparatus calculates the feature distances between the first feature vector and the second feature vector, and calculates the feature distances between each of the first feature vector and each of the second feature vector in a recursive manner, for example, the first feature vector includes A1 and A2, and the second feature vector includes B1, B2 and B3, and then calculates the feature distances between A1 and B1, B2 and B3, and the feature distances between A2 and B1, B2 and B3, respectively, to obtain 6 feature distance results.

And step B230, determining the inspector information with the characteristic distance smaller than a preset distance threshold as the inspection recommendation information.

In this embodiment, the device determines the inspector information with the characteristic distance smaller than a preset distance threshold as the corresponding inspection recommendation information, where the distance threshold is a self-set threshold range, and the characteristic distance smaller than the preset distance threshold indicates that the inspector information conforms to the information of the current inspector and is determined as the inspection recommendation information.

Step B300, determining the inspector selection information of the inspector, and establishing video communication between the terminal of the corresponding inspector and the terminal of the inspector based on the inspector selection information.

In this embodiment, the apparatus establishes video communication between the terminal of the corresponding examiner and the terminal of the examinee based on the examiner selection information.

Based on the first embodiment and the second embodiment, the present application further provides another embodiment, where after the step S300 of determining the state information of the examinee based on the expression recognition result, sending the state information to the examinee terminal, and saving the expression recognition result and the state information of the examinee in the corresponding database, the method includes the following steps C100-C300:

step C100, acquiring voice information and character information input by the examinee;

in this embodiment, the voice information may be voice information generated when the examinee communicates with the examinee, and is collected by a microphone at the examinee end; the text information is the information input by the examinee, and can be the text information generated by typing or the text information identified by voice information.

Step C200, inputting the voice information and the text information into a preset information recognition model, and performing state recognition processing on the voice information and the text information based on the information recognition model to obtain a state recognition result;

in this embodiment, the information recognition model is based on a speech training sample, a text training sample, a state label of the speech training sample, and a state label of the text training sample, and the model to be trained is iteratively trained to obtain an information recognition model satisfying a precision condition. Specifically, the iterative training process of the information recognition model refers to the training process of the expression recognition model in the first embodiment.

And step C300, sending the state identification result to an inspector terminal, and storing the state identification result of the inspected person to a corresponding database.

In the embodiment, the expression recognition result, the voice recognition result and the character recognition result of the person to be examined are comprehensively considered, so that the obtained emotion recognition result of the person to be examined is more accurate, and the treatment effect and experience of the patient are improved.

The present application also provides a remote psychological counseling apparatus, referring to fig. 3, the remote psychological counseling apparatus comprising:

an obtaining module 10, configured to obtain a face image of an examinee when video communication is established between a terminal of the examinee and a terminal of the examinee selected by the examinee;

the expression recognition module 20 is configured to input the facial image into a preset expression recognition model, and perform expression recognition processing on the facial image based on the expression recognition model to obtain an expression recognition result;

and the determining module 30 is configured to determine the state information of the examinee based on the expression recognition result, send the state information to the examinee terminal, and store the expression recognition result and the state information of the examinee in a corresponding database.

Optionally, the remote psychological counseling apparatus further comprises:

the information acquisition module is used for acquiring first data information containing inspector data and second data information containing inspected person data;

the recommendation information determining module is used for determining the checking recommendation information based on the first data information and the second data information and sending the checking recommendation information to the checked person terminal;

and the communication module is used for determining the inspector selection information of the inspected person and establishing video communication between the terminal of the corresponding inspector and the terminal of the inspected person based on the inspector selection information.

Optionally, the recommendation information determining module includes:

a vector determination module, configured to determine a first feature vector of the first data information and a second feature vector of the second data information;

a feature distance calculation module for calculating feature distances of the first feature vector and the second feature vector;

and the checking recommendation information determining module is used for determining the checker information with the characteristic distance smaller than a preset distance threshold as the checking recommendation information.

Optionally, the remote psychological counseling apparatus further comprises:

the system comprises a sample acquisition module, a face training module and a face recognition module, wherein the sample acquisition module is used for acquiring a face training sample and an expression label of the face training sample;

and the training module is used for carrying out iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model meeting the precision condition.

Optionally, the training module comprises:

the prediction module is used for inputting the face training sample into a preset model to be trained to obtain a predicted expression result;

the difference calculation module is used for performing difference calculation on the predicted expression result and the expression label of the face training sample to obtain an error result;

the judging module is used for judging whether the error result meets the error standard indicated by a preset error threshold range or not based on the error result;

and the iterative training module is used for returning to the step of inputting the face training sample into a preset model to be trained to obtain a predicted expression result if the error result does not meet the error standard indicated by the preset error threshold range, and stopping training until the training error result meets the error standard indicated by the preset error threshold range to obtain an expression recognition model meeting the precision condition.

Optionally, the determining module 30 includes:

the mapping acquisition module is used for acquiring the mapping relation between the expression information and the state information;

and the state information determining module is used for determining the state information of the checked person based on the expression recognition result and the mapping relation.

Optionally, the mapping obtaining module includes:

the state bid evaluation result acquisition module is used for acquiring the state bid evaluation result of the expert experience on the expression information;

and the matching module is used for matching the expression information with the state information based on the state bid evaluation result to obtain the mapping relation between the expression information and the state information.

The specific implementation manner of the remote psychological consultation device of the present application is substantially the same as that of each embodiment of the remote psychological consultation method, and is not described herein again.

Referring to fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present application.

As shown in fig. 1, the terminal may include: a processor 1001, e.g. a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory such as a disk memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.

Optionally, the remote psychological counseling apparatus may further include a rectangular user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).

It will be understood by those skilled in the art that the remote psychological counseling apparatus configuration shown in fig. 1 is not intended to be limiting, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.

As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a network communication module, and a remote psychological counseling program. The operating system is a program for managing and controlling hardware and software resources of the remote psychological counseling apparatus, and supports the operation of the remote psychological counseling program and other software and/or programs. The network communication module is used to enable communication between the components within the memory 1005 and with other hardware and software in the remote psychological counseling system.

In the remote psychological counseling apparatus shown in fig. 1, the processor 1001 is configured to execute a remote psychological counseling program stored in the memory 1005 to implement the steps of any one of the remote psychological counseling methods described above.

The specific implementation manner of the remote psychological consultation device of the present application is substantially the same as that of each embodiment of the remote psychological consultation method, and thus, details are not repeated herein.

The present application also provides a storage medium having stored thereon a program for implementing a remote psychological counseling method, the program being executed by a processor to implement the remote psychological counseling method as follows:

when video communication is established between a terminal of a person to be checked and a terminal of the person to be checked selected by the person to be checked, a face image of the person to be checked is obtained;

and determining the inspector selection information of the inspected person, and establishing video communication between the terminal of the corresponding inspector and the terminal of the inspected person based on the inspector selection information.

The specific implementation of the storage medium of the present application is substantially the same as that of each embodiment of the above remote psychological consulting method, and is not described herein again.

The present application also provides a computer program product, comprising a computer program which, when executed by a processor, performs the steps of the above-described method of remote psychological counseling.

The specific implementation of the computer program product of the present application is substantially the same as the embodiments of the remote psychological counseling method described above, and will not be described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method described in the embodiments of the present application.

The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.

Claims

1. A remote psychological counseling method, wherein the remote psychological counseling method comprises:

2. A remote psychological consultation method according to claim 1, characterized in that before the step of acquiring the image of the face of the examinee when the examinee's terminal establishes video communication with the examinee's terminal selected by the examinee, the method comprises:

determining inspection recommendation information based on the first data information and the second data information, and sending the inspection recommendation information to a terminal of an inspected person;

3. The remote psychological counseling method of claim 2, wherein the step of determining the examination recommendation information based on the first data information and the second data information comprises:

4. A remote psychological counseling method according to claim 1, wherein the method comprises, before the step of acquiring the face image of the examinee when the examinee's terminal establishes video communication with the examinee's terminal selected by the examinee, the steps of:

and performing iterative training on a preset model to be trained based on the face training sample and the expression label of the face training sample to obtain an expression recognition model meeting the precision condition.

5. The remote psychological consultation method according to claim 4, wherein the step of iteratively training a preset model to be trained based on the facial training samples and the facial expression labels of the facial training samples to obtain an expression recognition model satisfying a precision condition includes:

6. The remote psychological counseling method of claim 1, wherein the step of determining the state information of the examinee based on the expression recognition result comprises:

7. The remote psychological counseling method of claim 6, wherein the step of obtaining the mapping relationship between the expression information and the state information comprises:

and matching the expression information with the state information based on the state bid evaluation result to obtain the mapping relation between the expression information and the state information.

8. A remote psychological counseling apparatus, wherein the remote psychological counseling apparatus comprises:

the acquisition module is used for acquiring the face image of the examinee when the terminal of the examinee establishes video communication with the terminal of the examinee selected by the examinee;

and the determining module is used for determining the state information of the checked person based on the expression recognition result, sending the state information to a terminal of the checked person, and storing the expression recognition result and the state information of the checked person to a corresponding database.

9. A remote psychological counseling apparatus, wherein the remote psychological counseling apparatus comprises: a memory, a processor, and a program stored on the memory for implementing the remote psychological counseling method,

the processor is configured to execute a program for implementing the remote psychological counseling method, so as to implement the steps of the remote psychological counseling method according to any one of claims 1 to 7.

10. A storage medium having stored thereon a program for implementing a remote psychological counseling method, the program being executed by a processor to implement the steps of the remote psychological counseling method according to any one of claims 1 to 7.