CN115862868A - Psychological assessment system, psychological assessment platform, electronic device and storage medium - Google Patents
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Abstract
The system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring response data of a tested person aiming at a pre-configured questionnaire, modal data acquired by the tested person during the response of the questionnaire and modal data characteristics of the modal data, and the modal data comprises non-physiological data and/or physiological data; and the analysis module is used for determining a psychological evaluation result of the tested person according to at least one of the answering data, the modal data and the modal data characteristics, and the psychological evaluation result represents the psychology of the tested person. According to the embodiment of the disclosure, accurate and comprehensive psychological evaluation results can be provided, so that the determined psychological evaluation results are closer to the real psychological condition of the tested person.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a psychological assessment system, a psychological assessment platform, an electronic device, and a storage medium.
Background
In the fields of enterprise recruitment, student psychological problem screening, commercial product research and the like, the psychology of a user is usually evaluated by using a questionnaire. Early researchers all used paper questionnaires, and the collected questionnaires were electronized, and data answered by the tested persons were recorded in a computer and analyzed to obtain evaluation results. At present, a plurality of electronic evaluation platforms appear in the internet, and researchers can directly create an electronic questionnaire on the evaluation platforms to collect and analyze response data of the tested personnel to obtain an evaluation result of the tested personnel.
However, these evaluation platforms actually use the collection mode of the traditional questionnaire to perform evaluation, and the person to be evaluated may be hidden and misrepresented during the answering process, so that the evaluation result obtained according to the answering data of the questionnaire has errors with the actual situation, and the evaluation result is inaccurate.
Disclosure of Invention
In view of this, the present disclosure provides a psychological assessment system, a psychological assessment platform, an electronic device, and a storage medium, which can provide an accurate and comprehensive psychological assessment result, so that the determined psychological assessment result is closer to the real psychological situation of the person to be assessed.
According to an aspect of the present disclosure, there is provided a psychological assessment system including: the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring response data of a tested person aiming at a preconfigured questionnaire, modal data acquired by the tested person during response of the questionnaire and modal data characteristics of the modal data, and the modal data comprises non-physiological data and/or physiological data; and the analysis module is used for determining a psychological evaluation result of the tested person according to at least one of the response data, the modal data and the modal data characteristics, and the psychological evaluation result represents the psychology of the tested person.
In a possible implementation manner, the determining a psychological evaluation result of the tested person according to at least one of the answer data, the modal data and the modal data characteristics includes: inputting at least one of the response data, the modal data and the modal data characteristics into a psychological analysis model to obtain a psychological evaluation result of the tested person, wherein the psychological analysis model comprises at least one of the following: a statistical analysis model, a confidence and validity test model and a neural network model.
In a possible implementation manner, the determining a psychological evaluation result of the person to be tested according to at least one of the answer data, the modal data and the modal data characteristics includes: determining answer scores corresponding to the questionnaires according to the answer data; determining an emotional state score and/or a concentration degree score of the person under test according to the at least one of the modal data and the modal data characteristics; according to the emotional state score and/or the concentration degree score and the answer score, determining a psychological score corresponding to the tested person; and determining the psychological evaluation result according to the psychological score.
In one possible implementation, the system further includes: a configuration module to determine a type of the configured questionnaire and the configured modal data in response to a configuration operation for the questionnaire and the modal data; and/or the generating module is used for generating a shortcut for entering a user evaluation system based on the configured questionnaire and the type of the configured modal data, the shortcut is used for sending the shortcut to the tested person so as to enable the tested person to enter the user evaluation system to answer the questionnaire, and the user evaluation system is used for collecting answer data of the tested person for the questionnaire and modal data of the tested person during answering the questionnaire.
In a possible implementation manner, the obtaining module includes: the acquisition unit is used for acquiring response data of a tested person to the questionnaire and modal data of the tested person during response of the questionnaire based on a pre-configured questionnaire and the type of the modal data; and/or the receiving unit is used for receiving response data and modal data sent by the user evaluation system, wherein the user evaluation system is used for displaying a pre-configured questionnaire, collecting the response data of the tested person aiming at the questionnaire and collecting the modal data of the tested person during the response of the questionnaire; and/or the importing unit is used for responding to the importing operation aiming at the offline collected response data and modal data and acquiring the imported response data and modal data; the feature extraction unit is configured to perform feature extraction on at least one of the modal data acquired by the acquisition unit, the modal data received by the first receiving unit, and the modal data imported by the first importing unit to obtain a modal data feature.
In a possible implementation manner, the receiving unit is further configured to receive modal data features sent by the user evaluation system, and the user evaluation system is further configured to perform feature extraction on the acquired modal data to obtain modal data features; and/or the importing unit is further used for responding to the importing operation of the offline extracted modal data features and acquiring the imported modal data features.
In one possible implementation, the system further includes: the checking module is used for responding to the checking request aiming at the evaluation condition of the tested personnel participating in the evaluation and displaying the personnel number of the tested personnel participating in the evaluation and the psychological evaluation result of each tested personnel; and/or the model creating module is used for creating a psychological analysis model in response to the creating operation aiming at the psychological analysis model, and the created psychological analysis model is used for determining the psychological evaluation result of the tested person according to at least one of the response data, the modal data and the modal data characteristics.
In one possible implementation, the questionnaire comprises a text questionnaire in a text form, or a voice questionnaire in a dialogue form; the answering data comprises answering results and answering duration of each question in the questionnaire; the non-physiological data includes at least one of: video data, audio data, text data; the physiological data includes at least one of: electroencephalogram signals, heartbeat signals, blood pressure information, body temperature signals and respiration signals; the modal data characteristics include at least one of: the method comprises the following steps that facial features of a detected person in video data, audio features of audio data, text features of text data, electroencephalogram features of electroencephalogram signals, heartbeat features of heartbeat signals, blood pressure features of blood pressure signals, body temperature features of body temperature signals and breathing features of breathing signals are detected; the facial features of the person under test in the video data include at least one of: facial muscle variation characteristics, facial expression characteristics, face orientation characteristics and eye movement characteristics; the audio characteristics of the audio data include at least one of: emotional tendency of the audio, stop words, and tone of the audio; the text features of the text data include at least one of: the occurrence frequency of different words in the text, keywords appearing in the text, emotional tendency of the text, text topics and text center ideas.
According to another aspect of the present disclosure, there is provided a psychological assessment platform, including: the system comprises a user evaluation system, a data processing system and a data processing system, wherein the user evaluation system is used for displaying a preconfigured questionnaire, acquiring response data of a tested person aiming at the questionnaire and acquiring modal data of the tested person during the response of the questionnaire, and the modal data comprises physiological data and/or non-physiological data; and, the above described psychological assessment system.
According to another aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement a system-on-a-chip when executing the instructions stored by the memory.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the above-described system.
According to another aspect of the present disclosure, there is provided a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, the processor in the electronic device performs the above-described system.
According to the embodiment of the disclosure, the answer data of the tested person to the questionnaire and the modal data characteristics of the modal data collected by the tested person during the answer of the questionnaire can be combined, and the psychological evaluation result of the tested person can be comprehensively and accurately given, so that the determined psychological evaluation result is closer to the real psychological condition of the tested person.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.
Fig. 1 illustrates a block diagram of a psychological assessment system provided according to an embodiment of the present disclosure.
Fig. 2 illustrates a schematic diagram of a psychological assessment system provided according to an embodiment of the present disclosure.
Fig. 3 shows a schematic diagram of a psychological assessment platform provided according to an embodiment of the present disclosure.
Fig. 4 illustrates a block diagram of an electronic device 1900 provided in accordance with an embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
As described above, many electronic evaluation platforms appear in the internet, and researchers can directly create an electronic questionnaire on the evaluation platform to collect and analyze answer data of a person to be tested, so as to obtain an evaluation result of the person to be tested. The existing evaluation platform acquires relatively single data through a text questionnaire, can extract limited effective information, needs a large number of questions to be answered by a tested person to obtain relatively accurate results in order to ensure test effectiveness and accuracy, can easily sense the evaluation purpose of the tested person with an evaluation basis, enables the tested person to be in an unnatural state, and can make the evaluation result inaccurate by misrepresenting or hiding the answer result, namely, errors exist between the evaluation result obtained according to the answer data of the questionnaire and the actual situation.
In view of this, the embodiment of the present disclosure provides a psychological assessment system, which can combine the response data of a tested person to an questionnaire, the modal data collected by the tested person during the response to the questionnaire, and the modal data characteristics of the modal data to comprehensively determine the psychological assessment result of the tested person, so that the psychological assessment result can be explored from different dimensions by combining multidimensional data, and deep features of the tested person that are difficult to hide are mined, so that the psychological assessment result is closer to the real psychological condition, and the number of questions to be answered by the tested person can be greatly reduced, and the experience of the user can be improved.
In the embodiment of the present disclosure, besides using the text questionnaire for psychological assessment, the voice questionnaire of the natural conversation type can be used for psychological assessment, that is, the person to be assessed can complete the questionnaire answering in the conversation mode of normal communication, so that the assessment result is closer to the real result of the natural state.
Fig. 1 illustrates a block diagram of a psychological assessment system provided according to an embodiment of the present disclosure. The psychological assessment system may be executed by an electronic device such as a terminal device or a server, and the terminal device may be a medical instrument, a User Equipment (UE), a mobile device, a User terminal, a Personal Digital Assistant (PDA), a handheld device, a wearable device, or the like. As shown in fig. 1, the psychological evaluation system includes:
the acquisition module 101 is configured to acquire response data of a person to be tested on a preconfigured questionnaire, modal data acquired by the person to be tested during the response of the questionnaire, and modal data characteristics of the modal data, where the modal data includes non-physiological data and/or physiological data;
and the analysis module 102 is configured to determine a psychological evaluation result of the tested person according to at least one of the response data, the modal data, and the modal data characteristics, where the psychological evaluation result represents the psychology of the tested person.
The questionnaire comprises a text questionnaire or a dialogue voice questionnaire, and the answering data comprises answering results and answering duration of each question in the questionnaire; it should be understood that the questionnaire can be presented to the person to be tested in the form of a web page, an application program, an applet, or the like, for example, and the person to be tested can answer based on the presented questionnaire to obtain an answer result; the voice questionnaire can be played to the tested person through an audio playing device (such as a sound), the tested person can answer through voice, and during the answering period of the tested person through voice, the answering voice of the tested person can be collected through an audio collecting device (such as a recorder), and the answering voice is subjected to voice recognition to obtain an answering result; and recording the response time of the tested person to each question simultaneously during the response of the tested person to the questionnaire.
Wherein the non-physiological data comprises at least one of: video data, audio data, text data; the physiological data includes at least one of: electroencephalogram signals, heartbeat signals, blood pressure information, body temperature signals and respiratory signals. It should be understood that, according to the type of the preset modal data, the relevant data acquisition device may be used to acquire the modal data, for example, a video acquisition device (such as a camera) is used to acquire video data of the person to be measured during answering a questionnaire, an audio acquisition device is used to acquire audio data of the person to be measured during answering the questionnaire, the text data may be, for example, a text directly input by the person to be measured, or a text obtained by performing voice recognition on the audio data, etc.; an electroencephalogram signal sensor, a pulse signal sensor, a blood pressure signal sensor, a skin temperature sensor, a respiratory signal sensor and the like can be adopted to acquire physiological data such as electroencephalogram signals, heartbeat signals, blood pressure information, body temperature signals, respiratory signals and the like.
Wherein the modal data characteristics include at least one of: the method comprises the following steps that facial features of a detected person in video data, audio features of audio data, text features of text data, electroencephalogram features of electroencephalogram signals, heartbeat features of heartbeat signals, blood pressure features of blood pressure signals, body temperature features of body temperature signals and breathing features of breathing signals are detected; the facial features of the person under test in the video data include at least one of: facial muscle variation characteristics, facial expression characteristics, face orientation characteristics and eye movement characteristics; the audio characteristics of the audio data include at least one of: emotional tendency of audio, stop words, audio intonation; the text features of the text data include at least one of: the occurrence frequency of different words in the text, keywords appearing in the text, emotional tendency of the text, text subject, and text center thought.
The system can acquire corresponding modal data according to the type of the modal data preset by a tested person, and after acquiring the corresponding modal data, perform feature extraction on the modal data according to the feature type of the preset modal data feature to obtain the required modal data feature.
For example, for the facial features of a person to be detected in video data, an image sequence in the video data may be extracted and preprocessed, then a deep learning model is used to perform face detection, face key point extraction, facial expression feature extraction and other processing on the preprocessed image sequence, and then facial muscle change features, face orientation features, eye movement features and the like are determined based on the face key points extracted from the image sequence.
For example, the audio data may be pre-processed for its audio characteristics, including: filtering, resampling, fixed-length cutting, frequency spectrum analysis, time-frequency transformation and the like, extracting frequency distribution of segmented audio and normalized intensity of different frequency bands to obtain characteristics such as stop words and audio intonations, and analyzing the preprocessed audio data by using a deep learning network to obtain emotional tendency and degree in the audio data.
For example, for text features of text data, word segmentation, stop word removal and other processing can be performed on the text data by using a word segmentation method to obtain a word segmentation sequence, and then, the occurrence frequency of different words in the word segmentation sequence is counted; keyword extraction can be performed on the word sequences by using a keyword extraction algorithm (such as a Textrank algorithm) processed by natural language to obtain keywords appearing in the text; topic extraction can be carried out on the word sequences by using a topic extraction algorithm (such as an LDA algorithm) processed by natural language to obtain a text topic; the emotional tendency of the words in the text data can be extracted according to a preset emotional word bank, and the emotional tendency and the degree of the text can be obtained by weighting and averaging the emotional tendency of each word; the text key sentence can be obtained by adopting a text word clustering algorithm or other clustering algorithms processed by natural language to obtain the text center thought.
It should be understood that the researchers can configure the topics in the questionnaire according to the actual needs, and configure the types of the modality data required to be collected, and the embodiment of the present disclosure is not limited thereto. In a possible implementation manner, the obtaining module 101 may include: the acquisition unit is used for acquiring answer data of the tested person aiming at the questionnaire and modal data of the tested person during the answering of the questionnaire based on the type of the preset questionnaire and the modal data; the psychological evaluation system can extract the characteristics of the acquired modal data to obtain the modal data characteristics. The mode can be understood that the tested person answers the questionnaire in the psychological assessment system, the acquisition unit acquires answering data during the answering period of the tested person, meanwhile, various modal data are acquired by using data acquisition devices such as a camera, a recorder and various sensors, and further, the modal data features of the modal data can be extracted by using an artificial intelligence algorithm.
In consideration of the fact that the tested person may not answer the questionnaire conveniently by using the psychological system, a simple user evaluation system can be provided for the tested person, and is used for displaying the preconfigured questionnaire, collecting answer data of the tested person aiming at the questionnaire, collecting modal data of the tested person in the questionnaire answering period, and sending the collected answer data and modal data to the psychological evaluation system. In this way, the user evaluation system can be understood as a foreground system facing the tested person, the psychological evaluation system can be understood as a background system facing the researcher, and data communication is performed between the foreground system and the background system.
Based on this, in a possible implementation manner, the obtaining module 101 may further include: and the receiving unit is used for receiving the response data and the modal data sent by the user evaluation system. The mode can be understood that a tested person answers an questionnaire in the user evaluation system, the user evaluation system can acquire answering data during answering of the tested person, meanwhile, various modal data during answering are acquired by using data acquisition devices such as a camera, a recorder and various sensors, and the psychological evaluation system can perform feature extraction on the modal data sent by the user evaluation system to obtain modal data features, so that answering of the questionnaire is more convenient.
In a possible implementation manner, the receiving unit may be further configured to receive modal data features sent by the user evaluation system, and the user evaluation system is further configured to perform feature extraction on the acquired modal data to obtain the modal data features.
In view of the possible needs of researchers to collect response data and modal data characteristics on line, in one possible implementation, the obtaining module 101 may further include: and the importing unit is used for responding to the importing operation aiming at the offline collected response data and modal data and acquiring the imported response data and modal data. The mode can be understood as that researchers upload response data and modal data by themselves, and feature extraction is carried out on the modal data features through a psychological evaluation system to obtain the modal data features; and evaluating the psychology of the tested person based on the answering data and the modal data.
In one possible implementation manner, the importing unit is further configured to obtain an imported modal data feature in response to an importing operation for the offline extracted modal data feature. The mode can be understood that a researcher can perform feature extraction on the modal data acquired offline to obtain modal data features, and directly upload the modal data features extracted offline to the psychological assessment system, wherein offline can be understood that the embodiment of the present disclosure does not limit the feature extraction mode of the modal data acquired offline. The modal data collected offline is not the modal data collected by the psychological assessment system and the user assessment system, and the modal data features extracted offline is not the modal data features extracted by the psychological assessment system and the user assessment system.
In practical applications, researchers may pre-configure different psychological analysis models for different psychological assessment needs, such as depression symptom assessment, psychological health assessment, character assessment, and the like, to assess different types of psychology, wherein the psychological analysis models include at least one of the following: statistical analysis models, confidence test models, neural network models, which may include, for example, multivariate regression models, analysis of variance models, and other statistical data models. The system can provide a preset psychological analysis model for researchers to select a required psychological analysis model, and the researchers can also create the psychological analysis model in the system in a self-defined mode, for example, a new model can be introduced into the system, multiple models can be combined, or the models can be modified.
Based on this, in one possible implementation, the system may further include: and the model creating module is used for responding to creating operation aiming at the psychological analysis model and creating the psychological analysis model. The creating operation may include, for example, model importing, combining, modifying, and the like to obtain a desired psychoanalysis model, and it should be understood that a person skilled in the art may customize, in a psychology evaluation system, the desired psychoanalysis model according to actual needs, and configure data input by a psychology analysis modality, which is not limited in this disclosure. Through the mode, the researchers can use the psychological analysis model of the demands conveniently to perform accurate and comprehensive psychological assessment on the tested personnel.
Based on the above mental analysis model, in a possible implementation manner, the analysis module 102 determines a mental evaluation result of the tested person according to the response data and the modal data characteristics, including: and inputting at least one of the response data, the modal data and the modal data characteristics into a psychological analysis model to obtain a psychological evaluation result of the tested person, wherein the psychological evaluation result can represent the psychology of the tested person. For example, psychological assessment results may include, for a need for a depression symptom assessment: the psychology is normal, the psychology is mild depression symptom, moderate depression symptom or severe depression symptom; the psychological assessment results may include an outward-type character or an inward-type character with respect to the requirement of the character assessment. It should be understood that response data, modal data, and modal data characteristics can be input data for the psychology analysis model, and the input data required for different psychology analysis models can be different, depending on the model structure and type of psychology analysis model configured by the researcher.
It should be noted that the psychological evaluation result obtained by the psychological evaluation system according to the embodiment of the present disclosure represents an objective evaluation result, and is not used for diagnosis and treatment of the psychology of the person to be tested.
In a possible implementation manner, the analysis module 102 determines the psychological evaluation result of the tested person according to at least one of the response data, the modal data and the modal data characteristics, and may further include: determining answer scores corresponding to the questionnaires according to the answer data; determining an emotional state score and/or a concentration degree score of the tested person according to at least one of the modal data and the modal data characteristics; determining a psychological score corresponding to the tested person according to the emotional state score and/or the concentration degree score and the answering score; and determining a psychological evaluation result according to the psychological evaluation. By the mode, the answer scores of the questionnaire are corrected equivalently to the emotional state scores and/or the concentration degree scores, and the accurate psychological assessment results more fit to the actual situation are obtained.
The method comprises the steps of obtaining answer scores of all questions, and summing the answer scores of all the questions to obtain answer scores corresponding to questionnaires. The researchers can also preset mapping relations among various modal data, the emotion state scores and the concentration degree scores according to actual requirements, and preset mapping relations among various modal data characteristics, the emotion state scores and/or the concentration degree scores corresponding to the tested personnel on the basis of the mapping relations after the modal data and/or the modal data characteristics corresponding to the tested personnel are obtained, for example, the emotion state scores can be determined according to the emotions expressed by the text data, and the concentration degree scores can be determined according to the facial characteristics of the tested personnel in the video data; wherein, the emotional state score can represent whether the emotional state of the tested person is positive emotion or negative emotion, and the concentration degree score can represent the concentration degree of the tested person when the tested person answers the questionnaire.
The modal data can be modal data collected by a tested person when answering each topic, and the modal data features extracted from the modal data can be modal data features of the tested person when answering each topic, so that the mood state score and the concentration degree score of the tested person when answering each topic can be determined, and then the mood state score and the concentration degree score corresponding to all the topics are summed respectively to obtain the mood state score and the concentration degree score corresponding to the tested person.
Wherein, according to the emotional state score and/or the concentration degree score and the answering score, determining the corresponding psychological score of the tested person, for example, may include: weighting and summing the emotional state score and the answering score to obtain a psychological score; or, carrying out weighted summation on the concentration degree score and the answering score to obtain a psychological score; or, carrying out weighted summation on the emotional state score, the concentration degree score and the answer score to obtain a psychological score.
The researchers can preset different scoring levels and psychology corresponding to the different scoring levels according to actual needs, so that after obtaining the psychological score of the tested person, the psychological scoring result of the tested person can be determined based on the scoring level to which the psychological score belongs, for example, the psychological score can be distributed between 1 and 100, the higher the scoring is, the worse the psychology is, the psychology is divided into normal, mild depression symptom, moderate depression symptom and severe depression symptom, for example, 1-20 can be preset to represent normal, 21-40 to represent mild depression symptom, 41-80 to represent moderate depression symptom, and 81-100 to represent severe depression symptom.
It should be understood that the above determination method of the psychological score and the psychological evaluation result is an implementation manner provided by the embodiment of the present disclosure, and in fact, a person skilled in the art can set various specific values of the psychological score and determine a specific implementation manner of the psychological evaluation result in a customized manner according to actual needs, and the embodiment of the present disclosure is not limited thereto.
As described above, the researchers can customize and configure the topics in the questionnaire according to the actual needs, and configure the types of the modality data that needs to be collected, in one possible implementation, the system further includes: a configuration module to determine a configured questionnaire and a type of configured modality data in response to a configuration operation for the questionnaire and the modality data. In this manner, a researcher may utilize the system on-line configuration questionnaire and the type of modality data required. The embodiments of the present disclosure do not limit the implementation manner of the above configuration operation.
As described above, a simple user evaluation system may be provided for a person under test to answer a questionnaire and collect modal data, and in one possible implementation, the system further includes: and the generating module is used for generating a shortcut for entering the user evaluation system based on the configured questionnaire and the type of the configured modal data, and the shortcut is used for sending the tested person so that the tested person enters the user evaluation system to answer the questionnaire.
The shortcut can be, for example, a URL (Uniform Resource Locator) link and/or a two-dimensional code, the researcher can send the shortcut to the tested person, the tested person can directly enter the user evaluation system by clicking the URL link or scanning the two-dimensional code to answer the questionnaire, and the user evaluation system can collect answer data and modal data during the answering of the questionnaire.
The user evaluation system may be in the form of software such as a web page, an applet, an application program, and the like, for example, and the embodiment of the disclosure is not limited thereto. The user evaluation system can display a pre-configured questionnaire, collect answer results input by a tested person, count answer duration, simultaneously adopt data acquisition devices such as an audio acquisition device and a video acquisition device to acquire modal data, and then send the acquired answer data and modal data to the psychological evaluation system.
In order to facilitate the researchers to check the evaluation condition of the tested person participating in the evaluation, in a possible implementation manner, the system further comprises: and the checking module is used for responding to the checking request aiming at the evaluation condition of the tested personnel participating in the evaluation and displaying the personnel number of the tested personnel participating in the evaluation and the psychological evaluation result of each tested personnel. It should be understood that the psychological evaluation system may display the number of persons participating in evaluation and the psychological evaluation result of each person to be evaluated in any visual manner, and the embodiment of the present disclosure is not limited thereto. By the mode, the method is convenient for researchers to check the evaluation condition in real time.
In one possible implementation, the system may further include: and the personal information management module is used for realizing operations of modifying personal basic information, modifying passwords, binding login accounts and the like.
According to the psychological assessment system disclosed by the embodiment of the disclosure, the psychological assessment result of the tested person can be comprehensively and accurately given by combining the answering data of the tested person to the questionnaire and the modal data characteristics of the modal data collected by the tested person in the questionnaire answering period, so that the determined psychology is closer to the real situation of the tested person.
Fig. 2 is a schematic diagram illustrating a psychological assessment system according to an embodiment of the present disclosure, as shown in fig. 2, the psychological assessment system including: the device comprises a user module, a data acquisition module and a data analysis module.
The user module comprises a personal information management module, an evaluation project management module and a project data analysis module. The personal information management module is used for realizing operations of modifying personal basic information, modifying passwords, binding login accounts and the like.
The evaluation item management module comprises a configuration module and a viewing module; the configuration module can configure a text questionnaire item in a text mode and a voice questionnaire item in a free conversation mode: wherein, the text questionnaire project is configured by researchers (i.e. testers) for questioning questions, and the testees answer according to the set question sequence; the voice questionnaire project is characterized in that a research staff sets question range and question strategy, the system can automatically select proper questions to inquire according to the answering conditions of the tested staff, and the tested staff can answer according to the questions to inquire. After the evaluation project is established, the researchers can check the evaluation conditions of the tested persons participating in the evaluation through the checking module, wherein the evaluation conditions comprise the number of the tested persons participating in the evaluation and psychological evaluation results.
The project data analysis module is used for setting a required psychological analysis model and performing modeling analysis on the acquired project data (including at least one of response data, modal data and modal data characteristics), and specifically, the selected psychological analysis model can be used for analyzing at least one of the acquired response data, the modal data and the modal data characteristics to obtain a psychological analysis result output by the psychological analysis model.
The system can collect answering data and modal data simultaneously according to the set type of the modal data during the period that a tested person answers an questionnaire, and carries out feature extraction on the modal data according to the set feature type to obtain the modal data features.
The data analysis module can be used for analyzing project data, and various psychological analysis models can be arranged in the data analysis module and comprise a multiple regression model, a variance analysis model, a confidence and validity degree test model, a neural network model and the like. The tested person can create a needed neural state analysis model and associated project data in the data analysis module, and the associated project data can comprise at least one of response data, collected modal data and extracted modal data characteristics collected by the data collection module, and can also comprise response data, modal data and modal data characteristics uploaded by the tested person. The system analyzes the project data according to a psychological analysis model created by the researcher to obtain a psychological evaluation result, and displays the psychological evaluation result to the researcher by using a visual display form.
In the embodiment of the disclosure, a researcher can configure a questionnaire on a user module, and set modal data to be collected, a tested person can answer the questionnaire through a data collection module to collect answering data, the data collection module also collects different modal data by using data collection devices such as a camera and a recorder, the modal data characteristics of the different modal data are extracted through an artificial intelligence algorithm, the modal data characteristics are associated with questionnaire questions in a time dimension, and the data collected by the data collection module is subjected to modeling analysis through a data analysis module to give a psychological assessment result.
In practical application, the answer data and the modal data can be acquired through a user evaluation system, the user evaluation system can be a software system with questionnaire data acquisition and multi-modal data acquisition, and the expression form can be a webpage, an applet or an application program. The method has the main functions of displaying questionnaires to provide answers for tested personnel, collecting answer data of the tested personnel in the answering process, and collecting modal data, such as audio data and video data, of the tested personnel in the answering process; and after the tested person completes answering, transmitting the collected answering data and modal data to a psychological evaluation system.
Fig. 3 is a schematic diagram illustrating a psychological assessment platform provided according to an embodiment of the present disclosure, as shown in fig. 3, the platform including:
the user evaluation system is used for displaying the preconfigured questionnaire, acquiring response data of the tested person aiming at the preconfigured questionnaire and acquiring modal data of the tested person in the response questionnaire period;
and, the psychological assessment system in the above-mentioned embodiment of the present disclosure.
It should be understood that the user evaluation system in the platform is in communication connection with the psychological evaluation system, and the user evaluation system can send the collected response data and modal data to the psychological evaluation system.
Based on the psychological assessment platform, assuming that a researcher desires to use a questionnaire to assess depression symptoms of a tested person according to the emotional state and concentration degree of the tested person in video data, the operation process of the researcher on the psychological assessment platform may include:
researchers create an evaluation item in a psychological evaluation system, configure a questionnaire, enter the questionnaire into the evaluation item, set multimodal data features to be extracted in the evaluation item, for example, modal data features for determining a mood state score and a concentration degree score can be set for video data, and the system automatically generates a URL link and a two-dimensional code. The researcher can send the URL link and the two-dimensional code to the tested person.
And the tested person enters an evaluation interface of the user evaluation system by inputting a URL link in a browser or scanning the two-dimensional code by using a two-dimensional code scanning tool. The tested person answers the questionnaire on the evaluation interface, and the user evaluation system can record the answering result, the answering time and the video data in the answering process of the tested person at the same time. After the tested person finishes answering, the user evaluation system transmits the answering data and the video data to the psychological evaluation system.
And the psychological evaluation system performs characteristic extraction on the modal data sent by the user evaluation system according to the characteristic type of the modal data characteristic of the modal data which is set by researchers and needs to be extracted, so as to obtain the modal data characteristic for determining the emotional state score and/or the concentration degree score. The psychological evaluation system determines a psychological evaluation result of the tested person according to at least one of the answer data, the modal data and the modal data characteristics. The researchers can check the evaluation conditions of the tested persons participating in the evaluation in the psychological evaluation system, including the number of the tested persons participating in the evaluation and the psychological evaluation results of the tested persons.
Illustratively, the psychological assessment system determines the psychological assessment result of the tested person according to at least one of the response data, the modal data and the modal data characteristics, and may include:
suppose that the answer option of the tested person on the ith question is X i ，i∈[1,N]N is the total questions in the questionnaire, and the time length for answering the questions is t i Then, the item X in the ith topic i Corresponding score S i Expressed as formula (1):
wherein f is i Representing the mapping function, the answer score of the questionnaire is expressed as formula (2):
obtaining the emotional state score and the concentration degree score of the tested person when answering each question according to the mapping relation between at least one of the modal data and the modal data characteristics and the emotional state score and the concentration degree score, and assuming that the emotional state score of the tested person when answering the ith question is Y i1 (Y i1 >0 represents a positive mood, Y i1 <0 represents a negative emotion and the degree of concentration in response to the ith question was scored as Y i2 (wherein 0. Ltoreq. Y i2 ≤100，Y i2 Larger representing higher concentration), the psychological score S of the tested person can be determined total Expressed as formula (3):
wherein λ is 1 Is a weight coefficient, λ, of the emotional state score 2 Weight coefficient, σ, representing concentration degree score α Representing a function
α is a predetermined value, for example 0.
Wherein S can be total The correspondence is set to percentiles and according to S total The specific numerical value of (A) judges whether the psychology of the tested person belongs to normal, mild depression symptom, moderate depression symptom or severe depression symptom.
It should be noted that, although the operation process of the researcher at the psychological evaluation platform is described above by taking the evaluation of depression symptoms as an example, those skilled in the art can understand that the present disclosure should not be limited thereto. In fact, the user can flexibly set the user psychology to be evaluated according to personal preference and/or practical application scenes.
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-described system. The computer readable storage medium may be a volatile or non-volatile computer readable storage medium.
An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the system described above when executing the instructions stored by the memory.
Embodiments of the present disclosure also provide a computer program product including computer readable code or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, the processor in the electronic device executes the above system.
Fig. 4 illustrates a block diagram of an electronic device 1900 provided in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server or terminal device. Referring to fig. 4, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the apparatus 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output interface 1958 (I/O interface). The device 1900 may operate based on an operating system, such as Windows Server, stored in memory 1932 TM ，Mac OS X TM ，Unix TM ,Linux TM ，FreeBSD TM Or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions that are executable by the processing component 1922 of the electronic device 1900 to implement the above-described system.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as a punch card or an in-groove protruding structure with instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the market, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (11)
1. A psychological assessment system, comprising:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring response data of a tested person aiming at a preconfigured questionnaire, modal data acquired by the tested person during response of the questionnaire and modal data characteristics of the modal data, and the modal data comprises non-physiological data and/or physiological data;
and the analysis module is used for determining a psychological evaluation result of the tested person according to at least one of the answer data, the modal data and the modal data characteristics, and the psychological evaluation result represents the psychology of the tested person.
2. The system according to claim 1, wherein said determining a psychological assessment of the person under test based on at least one of the response data, the modal data, and the modal data characteristics comprises:
inputting at least one of the response data, the modal data and the modal data characteristics into a psychological analysis model to obtain a psychological evaluation result of the tested person, wherein the psychological analysis model comprises at least one of the following: a statistical analysis model, a confidence and validity test model and a neural network model.
3. The system according to claim 1, wherein said determining a psychological assessment of said subject based on at least one of said response data, said modal data, and said modal data characteristics comprises:
determining answer scores corresponding to the questionnaires according to the answer data;
determining an emotional state score and/or a concentration degree score of the person under test according to the at least one of the modal data and the modal data characteristics;
determining a psychological score corresponding to the tested person according to the emotional state score and/or the concentration degree score and the answering score;
and determining the psychological evaluation result according to the psychological score.
4. The system of claim 1, further comprising:
a configuration module to determine a type of the configured questionnaire and the configured modal data in response to a configuration operation for the questionnaire and the modal data; and/or the presence of a gas in the gas,
the system comprises a generating module, a shortcut module and a user evaluation system, wherein the generating module is used for generating the shortcut module for entering the user evaluation system based on the configured questionnaire and the type of the configured modal data, the shortcut module is used for sending the shortcut module to the tested person so as to enable the tested person to enter the user evaluation system to answer the questionnaire, and the user evaluation system is used for collecting the answer data of the tested person to the questionnaire and the modal data of the tested person during the answer of the questionnaire.
5. The system of claim 1, wherein the acquisition module comprises:
the device comprises a collecting unit, a processing unit and a processing unit, wherein the collecting unit is used for collecting response data of a tested person to a questionnaire and modal data of the tested person during response of the questionnaire based on a preconfigured questionnaire and the type of modal data; and/or the presence of a gas in the gas,
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving response data and modal data sent by a user evaluation system, the user evaluation system is used for displaying a pre-configured questionnaire, collecting the response data of a tested person aiming at the questionnaire, and collecting the modal data of the tested person during the process of answering the questionnaire; and/or the presence of a gas in the gas,
the importing unit is used for responding to importing operation aiming at offline collected answering data and modal data and acquiring the imported answering data and the modal data;
the feature extraction unit is configured to perform feature extraction on at least one of the modal data acquired by the acquisition unit, the modal data received by the receiving unit, and the modal data imported by the importing unit to obtain a modal data feature.
6. The system of claim 5,
the receiving unit is further used for receiving the modal data characteristics sent by the user evaluation system, and the user evaluation system is further used for carrying out characteristic extraction on the acquired modal data to obtain modal data characteristics; and/or the presence of a gas in the gas,
the importing unit is further used for responding to the importing operation of the offline extracted modal data features and acquiring the imported modal data features.
7. The system of claim 1, further comprising:
the checking module is used for responding to the checking request aiming at the evaluation condition of the tested personnel participating in the evaluation and displaying the personnel number of the tested personnel participating in the evaluation and the psychological evaluation result of each tested personnel; and/or the presence of a gas in the gas,
and the model creating module is used for creating a psychological analysis model in response to creating operation aiming at the psychological analysis model, and the created psychological analysis model is used for determining a psychological evaluation result of the tested person according to at least one of the response data, the modal data and the modal data characteristics.
8. The system according to any one of claims 1 to 7,
the questionnaire comprises a text questionnaire in a text mode or a voice questionnaire in a conversation mode;
the answering data comprises answering results and answering duration of each question in the questionnaire;
the non-physiological data includes at least one of: video data, audio data, text data;
the physiological data includes at least one of: electroencephalogram signals, heartbeat signals, blood pressure information, body temperature signals and respiration signals;
the modal data characteristics include at least one of: the method comprises the following steps that facial features of a detected person in video data, audio features of audio data, text features of text data, electroencephalogram features of electroencephalogram signals, heartbeat features of heartbeat signals, blood pressure features of blood pressure signals, body temperature features of body temperature signals and breathing features of breathing signals are detected;
the facial features of the person under test in the video data include at least one of: facial muscle variation characteristics, facial expression characteristics, face orientation characteristics and eye movement characteristics;
the audio characteristics of the audio data include at least one of: emotional tendency of audio, stop words, audio intonation;
the text features of the text data include at least one of: the occurrence frequency of different words in the text, keywords appearing in the text, emotional tendency of the text, text subject, and text center thought.
9. A psychological assessment platform, comprising:
the system comprises a user evaluation system, a data processing system and a data processing system, wherein the user evaluation system is used for displaying a preconfigured questionnaire, acquiring response data of a tested person aiming at the questionnaire and acquiring modal data of the tested person during the response of the questionnaire, and the modal data comprises physiological data and/or non-physiological data;
and, a psychological assessment system according to any one of claims 1 to 8.
10. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to implement the psychological assessment system of any one of claims 1 to 8 when executing the memory-stored instructions.
11. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the psychological assessment system of any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117133413A (en) * | 2023-10-26 | 2023-11-28 | 厚德明心(北京)科技有限公司 | NLP-based user psychological state assessment method and system |
| CN117289804A (en) * | 2023-11-23 | 2023-12-26 | 北京健康有益科技有限公司 | Virtual digital human facial expression management method, device, electronic equipment and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108197305A (en) * | 2018-01-30 | 2018-06-22 | 深圳壹账通智能科技有限公司 | Questionnaire test and appraisal processing method, device, computer equipment and storage medium |
| CN113903469A (en) * | 2021-11-15 | 2022-01-07 | 平安普惠企业管理有限公司 | Psychological assessment method, device, electronic device and medium based on artificial intelligence |
| CN115064246A (en) * | 2022-08-18 | 2022-09-16 | 山东第一医科大学附属省立医院(山东省立医院) | Depression evaluation system and equipment based on multi-mode information fusion |
-
2022
- 2022-12-15 CN CN202211613492.2A patent/CN115862868A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108197305A (en) * | 2018-01-30 | 2018-06-22 | 深圳壹账通智能科技有限公司 | Questionnaire test and appraisal processing method, device, computer equipment and storage medium |
| CN113903469A (en) * | 2021-11-15 | 2022-01-07 | 平安普惠企业管理有限公司 | Psychological assessment method, device, electronic device and medium based on artificial intelligence |
| CN115064246A (en) * | 2022-08-18 | 2022-09-16 | 山东第一医科大学附属省立医院(山东省立医院) | Depression evaluation system and equipment based on multi-mode information fusion |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117133413A (en) * | 2023-10-26 | 2023-11-28 | 厚德明心(北京)科技有限公司 | NLP-based user psychological state assessment method and system |
| CN117133413B (en) * | 2023-10-26 | 2024-01-30 | 厚德明心(北京)科技有限公司 | NLP-based user psychological state assessment method and system |
| CN117289804A (en) * | 2023-11-23 | 2023-12-26 | 北京健康有益科技有限公司 | Virtual digital human facial expression management method, device, electronic equipment and medium |
| CN117289804B (en) * | 2023-11-23 | 2024-02-13 | 北京健康有益科技有限公司 | Virtual digital human facial expression management method, device, electronic equipment and medium |
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