CN113628724B - Assessment and intervention method for violent fear psychology based on virtual reality technology - Google Patents
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Abstract
The invention discloses an assessment and intervention method for the mental of violent fear based on a virtual reality technology, which comprises the steps of carrying out symptom assessment and grade assessment on a trainer according to machine learning, giving a training plan by an operator, simulating a scene through the virtual reality technology, carrying out repeated reading training for multiple times, so that the trainer increases the psychological quality of the trainer, and learning how to self-protect and self-save; the training person is guided to build the correct psychology by simulating the punishment suffered by the riot; compared with the prior art, the invention can intuitively improve the psychological condition of a trainer, changes from self and overcomes the fear of violence.
Description
Technical Field
The invention relates to the field of virtual reality application, in particular to an evaluation and intervention method for the fear psychology of violence based on a virtual reality technology.
Background
The violent fear is commonly existed in the current society, and the phenomena of the overlong in schools, the riot in families and the like cause the fear psychology of a part of people on the violence, the people can only usually yield under the violence and can not save oneself, serious psychological diseases are caused, the long-time violent behaviors are caused, the bad psychological problems are easy to generate, the families are not only influenced, but also the social stability is influenced; the existing intervention on the mental fear of violent fear is generally the relief of changing environment, family accompanies and psychologists, but the intervention is difficult for the riot to fundamentally solve the psychological problem.
Disclosure of Invention
In order to solve the defects of the prior art, the invention aims to provide an evaluation and intervention method for the psychology of the violent fear based on the virtual reality technology, which aims to help a training object to overcome the psychology of the violent fear, and simultaneously train a trainer how to cope with the violence and self-help.
In order to achieve the above object, the present invention adopts the following technical scheme:
the method for evaluating and intervening the fear psychology based on the virtual reality technology is characterized by comprising the following steps:
s1, acquiring videos of a trainer when symptoms appear in daily life;
s2, inputting the video into a model, and evaluating and grading the symptoms of the trainer according to the video by the model;
s3, an operator makes a corresponding intervention training plan for a trainer according to the evaluation and symptom level given by the model;
s4, when the trainer performs intervention training, recording the state of the trainer during training through a camera and biofeedback equipment, and transmitting the state to the model;
s5, the model evaluates according to the received real-time video and gives a report and a training adjustment plan;
s6, an operator performs psychological dispersion, pacifying and encouragement on the trained trainer; after the physiological state of the trainer is restored to a normal state, the operator and the trainer analyze and summarize the training, encourage the trainer, and increase the self-rescue psychology of the trainer and the psychology of the winning rioter;
s7, simulating punishment and labor scenes of a rioter after the rioter is taken away through a VR technology; the operator and the trainer enter the virtual scene again at the same time, and the operator performs psychological intervention on the trainer, so that the trainer can understand the punishment required to be received after the riot is applied.
As a further preferred aspect of the present invention, the model in step S2 is derived through machine learning training using multiple sets of data including video of the rioter and victim, tags identifying the rioter and victim in the video, including scene at the time of the riot, action, language, mood and expression of the rioter, action, language, mood and expression of the victim; the victims are classified into self-rescue type and self-rescue type.
As a further preferred aspect of the present invention, the specific steps of the intervention plan in step S3 are:
s3.1, simulating a scene before violence occurs through a VR technology;
s3.2, after entering a scene and adapting, reminding the trainer to observe the current scene through voice, and monitoring the physiological state of the trainer through biofeedback equipment;
s3.3, simulating a riot person to enter a scene and riot;
s3.4, before the riot, the physical state of the trainer changes to a certain extent, the trainer is reminded to observe the behavior of the riot through voice pacifying the trainer, and the trainer is guided to reduce the riot probability of the riot through language;
s3.5, if the riot is unavoidable, guiding the trainer to send a distress signal to the outside; if the help-seeking signal cannot be sent, waiting for later self-rescue or sending the help-seeking signal again;
s3.6, when the riot is riot, the physical state of the trainer changes obviously, the trainer is pacified and encouraged through voice, and self-rescue consciousness of the trainer is stimulated;
s3.7, when the physiological state of the trainer is close to a self-rescue default value, teaching the trainer how to use props in a scene to save self or send a distress signal to the outside by using the props through voice;
s3.8, after the help seeking signal is successfully sent, the trainer is continuously taught to self-protect through voice to wait for rescue until the person is rescued;
s3.9, when the transmission of the distress signal fails, the trainer is encouraged by voice continuously, and the survival indication and the countermeasure psychology of the trainer are stimulated until the riot leaves;
s3.10, repeating the steps S1-S10 until the training person self-rescue, the riot person is taken away, and the training is finished.
As a further preferable aspect of the present invention, the step S3.7 is that the physiological state index when the trainer generates the self-rescue idea is set as the further preferable aspect of the present invention, and in the step S3, a physiological state threshold and a physiological state threshold are set, where the physiological state threshold is used to monitor whether the trainer needs to train repeatedly the current step, and the physiological state threshold is used to monitor whether the trainer can train continuously; in the steps S3.1-S3.5, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; stopping subsequent training when the physiological state of the trainer changes and the physiological state critical value does not reach the upper limit of the physiological state threshold value, and repeating the current and previous training steps; when the physiological state of the trainer changes and does not reach the critical value of the physiological state, continuing training; in the step S3.6-3.9, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; when the physiological state of the trainer changes and the upper limit of the physiological state threshold is not reached, training is continued.
As a further preferred aspect of the invention, in step S3, the model gradually reduces the speech alert and teaching after repeated training a number of times based on real-time video analysis.
As a further preferred aspect of the present invention, in step S5, the model adjusts the self-rescue default value, the physiological state threshold value, and the physiological state threshold value for the next training according to the real-time video analysis.
As a further preferred aspect of the present invention, in step S7, the VR technique simulates a penalty on the storm from the injury the storm caused to the trainer in the training scenario.
The invention has the advantages that: according to the invention, the scene is fully simulated by utilizing the machine learning and virtual reality technology, and the trainer is enabled to continuously learn how to perform self-protection and self-rescue by utilizing the props of the surrounding environment through voice pacifying, encouraging, reminding and teaching; through repeated training, the trainer increases the psychological diathesis of the trainer, and the violence person is in front of the violence, so as to overcome the violent fear psychology; the operator communicates with the trainer after training, summaries, and assists the trainer in setting up the correct, powerful psychology.
Detailed Description
The present invention will be specifically described with reference to the following specific examples.
The method for evaluating and intervening the fear psychology based on the virtual reality technology is characterized by comprising the following steps:
s1, acquiring videos of the trainers when symptoms appear in daily life.
S2, inputting the video into a model, and evaluating and grading the symptoms of the trainer according to the video by the model.
S3, an operator makes a corresponding intervention training plan for the trainer according to the evaluation and symptom level given by the model.
The specific steps of the intervention plan in the step S3 are as follows:
s3.1, simulating a scene before violence occurs through a VR technology;
s3.2, after entering a scene and adapting, reminding the trainer to observe the current scene through voice, and monitoring the physiological state of the trainer through biofeedback equipment;
s3.3, simulating a riot person to enter a scene and riot;
s3.4, before the riot, the physical state of the trainer changes to a certain extent, the trainer is reminded to observe the behavior of the riot through voice pacifying the trainer, and the trainer is guided to reduce the riot probability of the riot through language;
s3.5, if the riot is unavoidable, guiding the trainer to send a distress signal to the outside; if the help-seeking signal cannot be sent, waiting for later self-rescue or sending the help-seeking signal again;
s3.6, when the riot is riot, the physical state of the trainer changes obviously, the trainer is pacified and encouraged through voice, and self-rescue consciousness of the trainer is stimulated;
s3.7, when the physiological state of the trainer is close to a self-rescue default value, teaching the trainer how to use props in a scene to save self or send a distress signal to the outside by using the props through voice;
s3.8, after the help seeking signal is successfully sent, the trainer is continuously taught to self-protect through voice to wait for rescue until the person is rescued;
s3.9, when the transmission of the distress signal fails, the trainer is encouraged by voice continuously, and the survival indication and the countermeasure psychology of the trainer are stimulated until the riot leaves;
s3.10, repeating the steps S1-S10 until the training person self-rescue and the training is finished.
S4, when the trainer performs intervention training, the state of the trainer during training is recorded through the camera and the biofeedback equipment and is transmitted to the model.
And S5, evaluating the model according to the received real-time video, and giving a report and a training adjustment plan.
S6, an operator performs psychological dispersion, pacifying and encouragement on the trained trainer; after the physiological state of the trainer is restored to the normal state, the operator and the trainer analyze and summarize the training, encourage the trainer, and increase the self-rescue psychology of the trainer and the psychology of the winning rioter.
S7, simulating punishment and labor scenes of a rioter after the rioter is taken away through a VR technology; the operator and the trainer enter the virtual scene again at the same time, and the operator performs psychological intervention on the trainer, so that the trainer can understand the punishment required to be received after the riot is applied.
The model in the step S2 is obtained through machine learning training by using multiple groups of data, wherein the multiple groups of data comprise videos of a rioter and a victim and labels for identifying the rioter and the victim in the videos, and the videos comprise scenes during riot, actions, languages, mood and expression of the rioter and actions, languages, mood and expression of the victim; the victims are classified into self-rescue type and self-rescue type.
And S3.7, the self-rescue default value is a physiological state index when the set trainer generates self-rescue ideas.
In step S3, a physiological state critical value and a physiological state threshold value are set, wherein the physiological state critical value is used for monitoring whether a trainer needs to train repeatedly the current step, and the physiological state threshold value is used for monitoring whether the trainer can train continuously; in the steps S3.1-S3.5, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; stopping subsequent training when the physiological state of the trainer changes and the physiological state critical value does not reach the upper limit of the physiological state threshold value, and repeating the current and previous training steps; when the physiological state of the trainer changes and does not reach the critical value of the physiological state, continuing training; in the step S3.6-3.9, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; when the physiological state of the trainer changes and the upper limit of the physiological state threshold is not reached, training is continued.
In step S3, the model gradually reduces the speech alert and teaching after repeated training multiple times according to the real-time video analysis.
In step S5, the model adjusts the self-rescue default value, the physiological state critical value and the physiological state threshold value for the next training according to the real-time video analysis.
In step S7, the VR technology simulates the punishment of the rioter according to the harm of the rioter to the trainer in the training scene, and different punishments can clearly tell the trainer that the riot is to be punished, so as to correctly guide the trainer to set up correct psychological ideas.
The invention has the advantages that: according to the invention, the scene is fully simulated by utilizing the machine learning and virtual reality technology, and the trainer is enabled to continuously learn how to perform self-protection and self-rescue by utilizing the props of the surrounding environment through voice pacifying, encouraging, reminding and teaching; through repeated training, the trainer increases the psychological diathesis of the trainer, and the violence person is in front of the violence, so as to overcome the violent fear psychology; the operator communicates with the trainer after training, summaries, and assists the trainer in setting up the correct, powerful psychology.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be appreciated by persons skilled in the art that the above embodiments are not intended to limit the invention in any way, and that all technical solutions obtained by means of equivalent substitutions or equivalent transformations fall within the scope of the invention.
Claims (7)
1. The method for evaluating and intervening the fear psychology based on the virtual reality technology is characterized by comprising the following steps:
s1, acquiring videos of a trainer when symptoms appear in daily life;
s2, inputting the video into a model, and evaluating and grading the symptoms of the trainer according to the video by the model;
s3, an operator makes a corresponding intervention training plan for a trainer according to the evaluation and symptom level given by the model;
s4, when the trainer performs intervention training, recording the state of the trainer during training through a camera and biofeedback equipment, and transmitting the state to the model;
s5, the model evaluates according to the received real-time video and gives a report and a training adjustment plan;
s6, an operator performs psychological dispersion, pacifying and encouragement on the trained trainer; after the physiological state of the trainer is restored to a normal state, the operator and the trainer analyze and summarize the training, encourage the trainer, and increase the self-rescue psychology of the trainer and the psychology of the winning rioter;
s7, simulating punishment and labor scenes of a rioter after the rioter is taken away through a VR technology; the operator and the trainer enter the virtual scene again at the same time, and the operator performs psychological intervention on the trainer, so that the trainer can understand the punishment required to be received after the riot is applied;
the specific steps of the intervention plan in the step S3 are as follows:
s3.1, simulating a scene before violence occurs through a VR technology;
s3.2, after entering a scene and adapting, reminding the trainer to observe the current scene through voice, and monitoring the physiological state of the trainer through biofeedback equipment;
s3.3, simulating a riot person to enter a scene and riot;
s3.4, before the riot, the physical state of the trainer changes to a certain extent, the trainer is reminded to observe the behavior of the riot through voice pacifying the trainer, and the trainer is guided to reduce the riot probability of the riot through language;
s3.5, if the riot is unavoidable, guiding the trainer to send a distress signal to the outside; if the help-seeking signal cannot be sent, waiting for later self-rescue or sending the help-seeking signal again;
s3.6, when the riot is riot, the physical state of the trainer changes obviously, the trainer is pacified and encouraged through voice, and self-rescue consciousness of the trainer is stimulated;
s3.7, when the physiological state of the trainer is close to a self-rescue default value, teaching the trainer how to use props in a scene to save self or send a distress signal to the outside by using the props through voice;
s3.8, after the help seeking signal is successfully sent, the trainer is continuously taught to self-protect through voice to wait for rescue until the person is rescued;
s3.9, when the transmission of the distress signal fails, the trainer is encouraged by voice continuously, and the survival indication and the countermeasure psychology of the trainer are stimulated until the riot leaves;
s3.10, repeating the steps S3.1-S3.10 until the training person self-rescue, the riot person is taken away, and the training is finished.
2. The method of claim 1, wherein the model in step S2 is obtained by machine learning training using a plurality of sets of data, the plurality of sets of data including video of the rioter and the victim, labels identifying the rioter and the victim in the video, the video including scene of the riot, action of the rioter, language, mood and expression, action of the victim, language, mood and expression; the victims are classified into self-rescue type and self-rescue type.
3. The method for intervention in assessment of violent fear psychology based on virtual reality technology according to claim 1, wherein the self-rescue default value in step S3.7 is a physiological state index when the self-rescue idea is generated for the set trainer.
4. The method for intervention in assessment of violent fear psychology based on virtual reality technology according to claim 1, wherein in step S3, a physiological state threshold and a physiological state threshold are set, the physiological state threshold is used for monitoring whether the trainer needs to train repeatedly the current step, and the physiological state threshold is used for monitoring whether the trainer can train continuously; in the steps S3.1-S3.5, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; stopping subsequent training when the physiological state of the trainer changes and the physiological state critical value does not reach the upper limit of the physiological state threshold value, and repeating the current and previous training steps; when the physiological state of the trainer changes and does not reach the critical value of the physiological state, continuing training; in the step S3.6-3.9, when the physiological state of the trainer changes and reaches the upper limit of the physiological state threshold, stopping training; when the physiological state of the trainer changes and the upper limit of the physiological state threshold is not reached, training is continued.
5. The method of intervention in assessment of violent fear psychology based on virtual reality technology according to claim 1, wherein in step S3, the model gradually reduces the speech alert and teaching after repeated training a number of times according to real-time video analysis.
6. The method of intervention in assessment of violent fear psychology based on virtual reality technology according to claim 1, wherein in step S5, the model adjusts the self-rescue default value, physiological state critical value and physiological state threshold value for the next training according to real-time video analysis.
7. The method of claim 1, wherein in step S7, the VR technique simulates a penalty of the rioter based on the harm the rioter poses to the trainer in the training scenario.
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