CN107799165A - A kind of psychological assessment method based on virtual reality technology - Google Patents
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Abstract
Psychological assessment method of the invention based on virtual reality technology, by mental scale virtual scene；Collection subject question and answer, behavior and physiological data in real time；Question and answer option based on subject, complete the intelligent skip of mental scale problem；Comprehensive intelligent analysis is carried out to gauge content, by three class data by carrying out Fusion Features after convolutional neural networks, Recognition with Recurrent Neural Network training, softmax layers is input to, draws psychological assessment model；Subject's psychological assessment result is compared with doctor's label using psychological assessment model, by counting loss function and gradient reverse conduction, intelligent correction is carried out to subject's question and answer option；Physiology, behavior and calibrated question and answer data are calculated by psychological assessment model again, obtain final assessment result.The technologies such as VR, intelligent sensing, big data analysis, artificial intelligence are combined by the present invention with traditional psychological assessment method, are improved the accuracy of psychological assessment, are effectively saved medical resource.
Description
Technical field
The present invention relates to mental health domains, intelligent sensing field, virtual reality technology, big data analysis field and artificial
A kind of smart field etc., and in particular to psychological assessment method based on virtual reality technology.
Background technology
As the fast development of social economy and competitive pressure continue to increase, all kinds of Psychological Health Problems emerge in an endless stream.
But the corresponding medical resource wretched insufficiency in China, China's clinical diagnosis psychological problems typically first pass through equipment at present
Check to exclude organic disease, then assess using scale and doctor assess by the way of being combined whether to make a definite diagnosis with psychology
Disease, the aspectant diagnosis of doctors and patients excessively rely on the professional knowledge of doctor and subjective opinion.In view of patient generally has sick shame sense,
With that may have been concealed in the aspectant communication process of doctor, this causes doctor patient communication very big difficulty to be present.
Virtual reality (Virtual Reality, VR) technology is widelyd popularize and developed in recent years, in medical field
Existing certain application, and also attempted in terms of mental disease treatment.VR technologies can be built and real world heights
Similar virtual world, user can carry out, close to really interacting, producing experience on the spot in person with virtual world.
VR technologies, intelligent sensing technology, big data analytical technology, artificial intelligence technology and traditional mental scale are assessed into phase
With reference to improving the limitation that traditional psychological assessment method is brought, the sick shame sense of deficiency, sufferer including medical resource, comment
Estimate the subjectivity of process.By the effective psychological assessment scene of VR technique constructions, self-service psychological assessment side is provided for user
Method, Waiting time can be saved, save medical resource, increase the comfort level of user, reduce the sick shame sense of user, raising makes
The fitness of user and the validity of psychological assessment；Gather user's physiological data and behavioral data in real time in evaluation process,
User's real-time status is analyzed using intelligent information processing technology, intelligent correction is carried out to subject's question and answer option, psychology is improved and comments
Estimate the accuracy and objectivity of result；By standardizing interrogation process, can solve the present situation of quantification difficult in traditional interrogation.Simultaneously
With reference to big data technology, the excavation of user individual psychological characteristics and regularity summarization are carried out, lifts the accuracy of psychological assessment.
Therefore, by VR technologies, intelligent sensing technology, virtual reality technology, big data analytical technology, artificial intelligence technology with
Traditional psychological assessment method is combined, and can make up many deficiencies of conventional method, and provide one to assess psychological condition
Kind new method and thinking.
The content of the invention
To solve the problems of prior art, the present invention provides a kind of psychological assessment side based on virtual reality technology
Method, this method is by VR technologies, intelligent sensing technology, big data analytical technology, artificial intelligence technology and traditional psychological assessment method
It is combined, improves the accuracy of psychological assessment, while is also effectively saved medical resource.
The technical solution adopted in the present invention is as follows：A kind of psychological assessment method based on virtual reality technology, including with
Lower step：
S1：Selected mental scale；
S2：By selected mental scale virtual scene, the assessment content based on the design of specific mental scale is presented；
S3：Collection subject's question and answer data, behavioral data and physiological data in real time；
S4：Question and answer option based on subject, complete the intelligent skip of mental scale problem；
S5：Comprehensive intelligent analysis is carried out to gauge content, behavioral data is passed through convolutional neural networks by comprehensive intelligent analysis
Training, the output after question and answer data are trained by Recognition with Recurrent Neural Network, physiological data is trained by convolutional neural networks are through feature
A softmax layer is input to after fusion, draws psychological assessment model；
S6：Compared using the psychological assessment result that psychological assessment model obtains to subject's primary learning and doctor's label
It is right, by counting loss function and gradient reverse conduction, intelligent correction is carried out to the question and answer option of subject；
S7：Physiological data, behavioral data and calibrated question and answer option are calculated by psychological assessment model again, so as to obtain
Final comprehensive assessment result.
Preferably, the intelligent skip of mental scale problem described in step S4, simultaneously root is judged by designing a variety of Correlation Criterias
Jump strategy is selected according to real-time condition；The jump strategy include redirected according to relevant issues in doctor's clinical experience scale, according to
The user's state for redirecting according to current answer situation and being analyzed in real time according to system is redirected.
Preferably, step S5 comprises the following steps to the training process of behavioral data progress convolutional neural networks：
(1) shape information and Optic flow information are extracted respectively to the behavioral data of video acquisition；
(2) shape information and Optic flow information of extraction are pre-processed, obtains the input picture of convolutional neural networks；
(3) parameter of convolutional neural networks is set, shape information and Optic flow information are subjected to pretreated input picture
Two convolutional neural networks are inputted respectively to be trained；
(4) shape information after two convolutional neural networks are handled and the feature of Optic flow information are merged；
(5) output after step (4) Fusion Features is sequentially inputted to follow-up convolutional layer, pond layer and full articulamentum.
Preferably, step S5 to question and answer data Recognition with Recurrent Neural Network is handled the step of it is as follows：
(1) natural language processing is carried out to voice response data, speech data is converted into text data；
(2) text data is encoded；
(3) by first time question and answer data input to Recognition with Recurrent Neural Network；
(4) this question and answer data and previous step output result are input to Recognition with Recurrent Neural Network；
(5) circulation step (4), until question and answer terminate.
Preferably, step S5 comprises the following steps to the training process of physiological data progress convolutional neural networks:
(21) Short Time Fourier Transform is carried out to physiological data, obtains multichannel spectrogram；
(22) multichannel spectrogram is trained using convolutional neural networks.
As can be known from the above technical solutions, the present invention be based on virtual reality technology, merge evaluated object mental scale determine,
Behavioral data and the physiological data monitored in real time, by based on the data marked with doctor via convolutional neural networks and circulation
Neutral net even depth learning algorithm obtains psychological assessment model, and the model has clinical experience, can autonomous intelligence assess do not have
The data of doctor's mark.Meanwhile the psychological assessment result of subject is compared the present invention with doctor's label, damaged by calculating
Lose function and gradient reverse conduction and intelligent correction is carried out to question and answer option, the question and answer data after correction can preferably reflect subject
True psychological condition, then calculated via psychological assessment model, so as to obtain final comprehensive assessment result.Compared with prior art,
The present invention at least has the advantages that：
Mental scale evaluation process is embodied by the present invention, is transformed into scale problem using virtual reality technology and is easy to
The virtual scene that subject understands, while doctor is observed into Data Digital, and subject physiologic's data are gathered, by question and answer number
Comprehensive analysis is carried out according to, physiological data and behavioral data, obtains subject's psychological assessment result, while assessment result is marked with doctor
The intelligence correction for realizing subject's question and answer option is compared in label., can using traditional doctors experience and objective physiological parameter
To lift the accuracy of psychological assessment, help user to be known from body psychological condition in time, help user management mental health, prevention
The generation of mental disease.Working doctor amount, save medical resources can be reduced simultaneously.And this method provides for medical research
New research ideas and methods, be advantageous to find related emotional, psychological judgement symbol thing and mechanism.This method collects largely
User data can be used for realizing cloud computing, excavate user individual psychological characteristics with the method for machine learning, enter one
Step provides targetedly psychological consultation.
Brief description of the drawings
Fig. 1 is psychological assessment flow chart of the present invention；
Fig. 2 is comprehensive intelligent analysis principle figure；
Fig. 3 is intelligent correction schematic diagram；
Fig. 4 is behavioral data processing procedure figure；
Fig. 5 is the network structure of question and answer data processing；
Fig. 6 is physiology data handling procedure figure.
Embodiment
The present invention proposes a kind of psychological assessment method based on virtual reality technology, by mental scale evaluation process tool as
Change, scale problem is transformed into the virtual scene for being easy to subject to understand using virtual reality technology；Doctor is observed simultaneously
Data Digital, subject physiologic's data are gathered, handle subject's scale question and answer data, triplicity is subjected to comprehensive analysis,
Intelligent correction of answering invalid to subject simultaneously.Subject is avoided because the difference that external interference and doctor observe causes to assess
As a result difference, and avoid answer privacy concern because of sick shame sense is the diversity of this immersive VR content and true
Reality is that doctor assesses and brought great convenience, while based on big data technology, to excavate subject more under particular context
Information.
Psychological assessment method of the present invention includes virtual reality presentation, speech recognition and the natural language processing skill of mental scale
Art, the intelligent skip logic of evaluation problem, the intelligent correcting algorithm of subject's question and answer option, comprehensive intelligent parser, such as scheme
1, specifically comprise the following steps：
Step S1：Selected mental scale；
Step S2：Selected mental scale virtual scene is presented in the assessment based on the design of specific mental scale
Hold；
The virtual reality of the mental scale is presented, and using virtual reality technology, mental scale is converted into Virtual Space
The enquirement form of middle fititious doctor.Mental scale virtual scene, i.e., by being decomposed to sentimental space, make with specific
The virtual reality scenario that mood induces, mental scale problem is embodied.
By mental scale continuous mode virtual reality scenario, the standard understood for improving subject mental scale problem
True property, the validity of subject's answer is improved, so as to which psychological assessment result is more scientific and effective；Aid in objective physiological number simultaneously
According to behavioral data, assess and provide effectively and easily means for psychological condition.Wherein virtual reality scenario includes but is not limited to
Fititious doctor image design, cyberspace design, fititious doctor inquiry form.
Step S3：Gather subject real-time question and answer data, real-time behavioral data and non-real time physiological data；
Subject's non-real time physiological data of the collection, including but not limited to brain electricity, brain blood flow, pulse, electrocardio, myoelectricity,
Body temperature, skin electricity, blood oxygen concentration.For analyzing the psychological condition in subject's question answering process, the input as psychological assessment model
And the condition judgment for intelligent skip logic.
Step S4：Question and answer option based on subject, complete the intelligent skip of mental scale problem；
The intelligent skip of the mental scale problem, by designing a variety of Correlation Criterias judgements and being selected according to real-time condition
Jump strategy, include but are not limited to be redirected according to relevant issues in doctor's clinical experience scale, jumped according to current answer situation
Turn, redirected according to user's state that system is analyzed in real time.
Step S5：Comprehensive intelligent analysis is carried out to gauge content；
Comprehensive intelligent analysis method, for analyzing gathered user data, a large number of users number based on long-time accumulation
According to progress personality mentality feature mining and regularity summarization.Based on the data that doctor marks via convolutional neural networks and following
Ring neutral net even depth learning algorithm obtains psychological assessment model.Meanwhile the heart that this method obtains to subject's primary learning
Reason assessment result is compared with doctor's label, by counting loss function and gradient reverse conduction, so as to realize that subject measures
The intelligence correction that table is answered.Calibrated scale is answered and inputs psychological assessment model again with behavior and physiological data, is drawn
Final psychological assessment report.
Specifically, comprehensive analysis carries out convolutional Neural net respectively to behavioral data, physiological data, question and answer data first
The training of network, Recognition with Recurrent Neural Network, convolutional neural networks, the output after three class data are trained carry out Fusion Features, are input to
Softmax layers.
Real-time behavioral data is handled, as shown in figure 4, input video material (behavioural information of subject), extraction
Wherein shape information and Optic flow information, both are separately input in a convolutional neural networks, two convolutional neural networks structures
It is identical, including the first convolutional layer, the first pond layer, the second convolutional layer, the second pond layer, the 3rd convolutional layer 1, the 3rd convolutional layer 2,
3rd pond layer, after two convolutional neural networks carry out Fusion Features, it is input to Volume Four lamination, the 4th pond layer, the 5th complete
Articulamentum, the 6th full articulamentum.First convolutional layer, the first pond layer, the second convolutional layer, the second pond layer, the 3rd convolution
Layer the 1, the 3rd convolutional layer 2, the 3rd pond layer are sequentially connected, the convolutional neural networks, Volume Four lamination, the 4th pond layer, the
Five full articulamentums, the 6th full articulamentum are sequentially connected.
The training process that convolutional neural networks are carried out to real-time behavioral data comprises the following steps：
(1) shape information and Optic flow information are extracted respectively to the behavioral data of video acquisition；
(2) shape information and Optic flow information of extraction are pre-processed, obtains the input picture of convolutional neural networks；
(3) parameter of convolutional neural networks is set, pretreated input picture input convolutional neural networks will be carried out and entered
Row training.Training of the convolutional neural networks to input picture, is comprised the following steps that：
(31) input picture inputs the first convolutional layer, and it is 3*3 that size is carried out to it, and step-length 1, the filling distance is 1 volume
Product operation, altogether using 3 convolution kernels；
(32) picture exported through the first convolutional layer is input to the first pond layer, carries out maximum pond operation, pond block it is big
Small is 2*2, step-length 2；
(33) picture through the first pond layer output is input to the second convolutional layer, and it is 3*3 that size is carried out to it, step-length 1,
The filling distance is 1 convolution operation, altogether using 3 convolution kernels；
(34) picture exported through the second convolutional layer is input to the second pond layer, carries out maximum pond operation, pond block it is big
Small is 2*2, step-length 2；
(35) picture through the second pond layer output is input to the 3rd convolutional layer 1, and it is 3*3 that size is carried out to it, and step-length is
1, the filling distance is 1 convolution operation, altogether using 3 convolution kernels；
(36) picture exported through the 3rd convolutional layer 1 is input to the 3rd convolutional layer 2, and it is 3*3 that size is carried out to it, and step-length is
1, the filling distance is 1 convolution operation, altogether using 3 convolution kernels；
(37) picture exported through the 3rd convolutional layer 2 is input to the 3rd pond layer, carries out maximum pond operation, pond block it is big
Small is 2*2, step-length 2.
(4) shape information after two convolutional neural networks are handled and the feature of Optic flow information are merged；
(5) output after step (4) Fusion Features is input to Volume Four lamination, and it is 3*3 that size is carried out to it, and step-length is
1, the filling distance is 1 convolution operation, altogether using 3 convolution kernels；
(6) picture exported through Volume Four lamination is input to the 4th pond layer, carries out maximum pond operation, the size of pond block
For 2*2, step-length 2；
(7) picture through the 4th pond layer output is input to the 5th full articulamentum；
(8) picture through the 5th full articulamentum output is input to the 6th full articulamentum.
The network structure handled question and answer data is as shown in figure 5, be a shot and long term memory Recognition with Recurrent Neural Network.Institute
State question and answer data shot and long term memory Recognition with Recurrent Neural Network processing the step of it is as follows：
(1) natural language processing is carried out to voice response data, speech data is converted into text data；
Based on intelligent sound identification with natural language processing algorithm, the voice signal that subject is answered a question is converted into text
This, integrative medicine dictionary obtains real-time answer result through row natural language processing, including but be not limited only to segmentation methods, close
Keyword extraction, text Emotion identification algorithm.
(2) text data is encoded；
(3) first time question and answer data (i.e. question and answer data 1) are input to shot and long term memory Recognition with Recurrent Neural Network；
(4) this question and answer data and previous step output result are input to shot and long term memory Recognition with Recurrent Neural Network；
(5) circulation step (4), until question and answer terminate.
The process handled using convolutional neural networks physiological data is as shown in fig. 6, the physiology that input monitors in real time
Data, by Short Time Fourier Transform, the multichannel spectrogram of physiological data is obtained, is input to a convolutional neural networks, should
Convolutional neural networks include the first convolutional layer, the second convolutional layer, the 3rd pond layer and the 4th full articulamentum.The physiological data volume
The training process of product neutral net comprises the following steps:
(1) Short Time Fourier Transform is carried out to physiological data, obtains multichannel spectrogram；
(2) parameter of the convolutional neural networks is set, and multichannel spectrogram is inputted into the convolutional neural networks is carried out
Training.Physiological data is as follows in the training step of convolutional neural networks：
(21) Short Time Fourier Transform is carried out to physiological data, obtains multichannel spectrogram；
(22) spectrogram is inputted into the first convolutional layer, it is 15*3 that size is carried out to it, and step-length 1, the filling distance is 1 volume
Product operation, altogether using 2 convolution kernels；
(23) figure exported through the first convolutional layer is input to the second convolutional layer, it is 1*1 that size is carried out to it, step-length 1,
The filling distance is 1 convolution operation, altogether using 1 convolution kernel；
(24) figure exported through the second convolutional layer is input to the 3rd pond layer, carries out maximum pond operation, pond block it is big
Small is 2*2, step-length 2；
(25) picture through the 3rd pond layer output is input to the 4th full articulamentum.
The convolutional neural networks of behavioral data, the Recognition with Recurrent Neural Network of question and answer data, the convolutional neural networks of physiological data
Output a softmax layer is input to after Fusion Features, draw psychological assessment model.The Fusion Features are by behavioral data
Convolutional neural networks, the Recognition with Recurrent Neural Network of question and answer data, the output result of convolutional neural networks of physiological data connect entirely.
Step S6：Intelligence corrects wrong question and answer option；
This step carries out intelligent correction to the wrong question and answer option of subject, by by subject's question and answer data, behavior number
It is trained according to physiological data, output psychological assessment result is compared with doctor's label, and counting loss function and gradient are anti-
To conduction to question and answer option, the false answer of subject is corrected, as shown in Figure 3.
Such as Fig. 2,3, the present invention carries out comprehensive intelligent analysis and step S6 intelligently correction mistake to gauge content in step S5
By mistake during question and answer option, Fusion Features processing is carried out to subject's behavioral data, simulation doctor clinical evaluation observation is tested
Person's state, the real-time behavioral data of subject is recorded, include but are not limited to that expression, sound, eye be dynamic, limb action.Utilize expression
The technology such as identification, sound and its Emotion identification, action recognition, for the input of comprehensive intelligent parser and for intelligent jump
Turn the condition judgment of logic.Speech recognition and natural language processing are carried out to the real-time behavioral data of subject, collection in real time by
The voice signal of examination person is simultaneously converted into text, and natural language processing analysis semanteme and mood are carried out to text.
Step S7：Obtain final subject's psychological assessment report.
The present invention is analyzed by comprehensive intelligent, will be neural via convolutional neural networks and circulation with the data that doctor demarcates
Network even depth learning algorithm is learnt, and obtains psychological assessment model.Meanwhile this psychological assessment models is tentatively learned subject
Practise the psychological assessment result obtained to be compared with doctor's label, by counting loss function and gradient reverse conduction, to question and answer
Option carries out intelligent correction.Physiological data, behavioral data and calibrated question and answer option are calculated by psychological assessment model again, from
And obtain final comprehensive assessment result.
The present invention simulates real psychological assessment process, by mental scale question and answer intelligent logical, realizes virtual reality scenario
In fititious doctor and subject's intelligent human-machine interaction, Real Time Observation and record subject behavioral data, physiological data, question and answer number
According to etc.；Based on obtaining the heart via convolutional neural networks and Recognition with Recurrent Neural Network even depth learning algorithm with the data that doctor marks
Manage assessment models, the model has clinical experience, can autonomous intelligence assess the data of no doctor's mark.
As described above, the present invention can be better realized.
Claims (8)
- A kind of 1. psychological assessment method based on virtual reality technology, it is characterised in that comprise the following steps：S1：Selected mental scale；S2：By selected mental scale virtual scene, the assessment content based on the design of specific mental scale is presented；S3：Collection subject's question and answer data, behavioral data and physiological data in real time；S4：Question and answer option based on subject, complete the intelligent skip of mental scale problem；S5：To gauge content carry out comprehensive intelligent analysis, comprehensive intelligent analysis behavioral data is trained by convolutional neural networks, Output after question and answer data are trained by Recognition with Recurrent Neural Network, physiological data is trained by convolutional neural networks is after Fusion Features A softmax layer is input to, draws psychological assessment model；S6：The psychological assessment result that subject's primary learning obtains is compared with doctor's label using psychological assessment model, By counting loss function and gradient reverse conduction, intelligent correction is carried out to the question and answer option of subject；S7：Physiological data, behavioral data and calibrated question and answer option are calculated by psychological assessment model again, it is final so as to obtain Comprehensive assessment result.
- 2. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that described in step S4 The intelligent skip of mental scale problem, judged and according to real-time condition selection jump strategy by designing a variety of Correlation Criterias；Institute Stating jump strategy includes being redirected according to relevant issues in doctor's clinical experience scale, being redirected and according to system according to current answer situation The user's state analyzed in real time of uniting is redirected.
- 3. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that step S5 is to row The training process that convolutional neural networks are carried out for data comprises the following steps：(1) shape information and Optic flow information are extracted respectively to the behavioral data of video acquisition；(2) shape information and Optic flow information of extraction are pre-processed, obtains the input picture of convolutional neural networks；(3) parameter of convolutional neural networks is set, shape information and Optic flow information are subjected to pretreated input picture difference Two convolutional neural networks of input are trained；(4) shape information after two convolutional neural networks are handled and the feature of Optic flow information are merged；(5) output after step (4) Fusion Features is sequentially inputted to follow-up convolutional layer, pond layer and full articulamentum.
- 4. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that step S5 is to asking Answer is according to as follows Recognition with Recurrent Neural Network is handled the step of：(1) natural language processing is carried out to voice response data, speech data is converted into text data；(2) text data is encoded；(3) by first time question and answer data input to Recognition with Recurrent Neural Network；(4) this question and answer data and previous step output result are input to Recognition with Recurrent Neural Network；(5) circulation step (4), until question and answer terminate.
- 5. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that step S5 is to life The training process that reason data carry out convolutional neural networks comprises the following steps：(21) Short Time Fourier Transform is carried out to physiological data, obtains multichannel spectrogram；(22) multichannel spectrogram is trained using convolutional neural networks.
- 6. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that the behavior number According to including expression, sound, eye be dynamic and limb action.
- 7. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that the physiology number According to, including brain electricity, brain blood flow, pulse, electrocardio, myoelectricity, body temperature, skin electricity and blood oxygen concentration.
- 8. the psychological assessment method according to claim 1 based on virtual reality technology, it is characterised in that described in step S2 Virtual scene includes fititious doctor image design, cyberspace design and fititious doctor inquiry form.
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