CN110752034A

CN110752034A - Psychological data processing method and equipment

Info

Publication number: CN110752034A
Application number: CN201910821238.3A
Authority: CN
Inventors: 任满钧
Original assignee: Beijing Longxin Technology Co Ltd
Current assignee: Beijing Longxin Technology Co Ltd
Priority date: 2019-08-05
Filing date: 2019-09-02
Publication date: 2020-02-04
Also published as: CN110743074B; CN110752007A; CN110743079A; CN110743077A; CN110743074A; CN110743079B; CN110743078B; CN110743077B; CN110743078A

Abstract

The invention provides a psychological data processing method and equipment, wherein the method comprises the following steps: collecting a first physiological signal of a user; determining whether various psychological states are abnormal or not according to the first physiological signal; obtaining a psychological assessment scale fed back by a user, wherein the psychological assessment scale comprises a plurality of question data, and at least part of the question data is configured to correspond to a plurality of first risk factors; determining whether each first risk factor is abnormal according to a psychological assessment scale fed back by a user; and associating the abnormal psychological state with the abnormal first risk factor.

Description

Psychological data processing method and equipment

Technical Field

The invention relates to the field of psychotherapy, in particular to a psychological data processing method and equipment.

Background

Modern medicine indicates that human health includes both physical health and psychological health, and that simply pursuing physical health and neglecting psychological health not only causes mental diseases but also induces various somatic diseases. In modern society, people are more and more in psychological sub-health condition due to the acceleration of operation rhythm and the continuous aggravation of competition situation.

Psychological counseling and psychological treatment are increasingly receiving social attention as means for solving psychological problems. People can choose to determine and try to solve problems through psychological counseling and psychological treatment when doubts exist about possible abnormality of the psychological state of the people.

In the prior art, some schemes capable of determining or measuring psychological states are available, for example, whether the human psychology is normal can be determined through physiological signals or a psychological assessment scale, but when the psychology is abnormal, the reason of the abnormality cannot be determined, so that it is difficult to determine an effective improvement scheme.

Disclosure of Invention

In view of the above, the present invention provides a method for processing psychological data, comprising:

collecting a first physiological signal of a user;

determining whether various psychological states are abnormal or not according to the first physiological signal;

obtaining a psychological assessment scale fed back by a user, wherein the psychological assessment scale comprises a plurality of question data, and at least part of the question data is configured to correspond to a plurality of first risk factors;

determining whether each first risk factor is abnormal according to a psychological assessment scale fed back by a user;

and associating the abnormal psychological state with the abnormal first risk factor.

Optionally, determining whether each first risk factor is abnormal according to a psychological assessment scale fed back by a user includes:

quantifying answer data of the at least part of the question data fed back by the user;

and determining whether each first risk factor is abnormal according to the quantization result of the answer data.

Optionally, associating the abnormal psychological state with the abnormal first risk factor includes:

and generating a personal psychological data analysis result which comprises information for indicating whether the psychological state is abnormal or not, and taking the abnormal first risk factor as the reason information of the abnormal psychological state when the abnormal psychological state exists.

Optionally, at least a portion of the question data in the psychological assessment scale is configured to correspond to a number of second risk factors; the method further comprises the following steps: and determining whether each second risk factor is abnormal according to a psychological assessment scale fed back by the user, and generating information for prompting the user to perform psychological consultation when the abnormal second risk factors exist.

Optionally, the mental state comprises neural balance, mood, mental stress, physical fatigue, ability to adapt.

Optionally, determining the degree of abnormality of the plurality of psychological states according to the first physiological signal includes:

determining heart rate variability information from the first physiological signal;

and determining the abnormal degrees of various psychological states according to the heart rate variability information.

The invention also provides a group psychological data processing method, which comprises the following steps:

processing psychological data of a plurality of users by using the training data processing method, wherein the first risk factors in the psychological assessment table are configured to correspond to group assistance scheme data;

judging whether the number of users with abnormal first risk factors exceeds a set threshold value or not;

and when the number of the users exceeds a set threshold value, acquiring the abnormal group auxiliary scheme data corresponding to the first risk factor.

Optionally, after obtaining the community assistance scheme data corresponding to the abnormal first risk factor, the method further includes:

generating a group psychological data analysis result including the information of the number of users of the first risk factor having abnormality and the group assistance plan data.

Correspondingly, the invention also provides a psychological data processing device, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor, the instructions being executable by the at least one processor to cause the at least one processor to perform the above-mentioned mental data processing method.

Correspondingly, the invention also provides a psychological data processing device, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor, the instructions being executable by the at least one processor to cause the at least one processor to perform the above-mentioned group mental data processing method.

According to the psychological data processing method and the equipment provided by the invention, firstly, the physiological signal of the user is collected, and whether various psychological states of the user are abnormal or not is objectively determined based on the physiological signal, namely whether the psychological states are abnormal or not under each psychological dimension. And simultaneously, a psychological assessment scale fed back by the user is collected, the problems in the scale correspond to a plurality of risk factors, the problems and the risk factors can be set according to actual conditions of occupation, environment and the like of the user, and whether the user presents abnormity on certain risk factors is determined according to the feedback condition of the user on the problems in the scale. Finally, the abnormal psychological state determined based on the physiological signal is associated with the abnormal risk factor determined based on the scale, so that the risk factor causing the user psychological state abnormality can be determined, the risk factor represented by the scale is used as the cause of the psychological state abnormality, objective data basis is provided for the user to perform psychological adjustment, and the user is assisted to improve the psychological state.

According to the method and the equipment for processing the group psychological data, firstly, the psychological data of the individual users are collected and processed based on the technical scheme, then whether most of the group users present abnormity on certain risk factors is analyzed, when most of the users present abnormity on certain same risk factors, the group auxiliary scheme data corresponding to the abnormal risk factors are obtained, the group auxiliary scheme can be preset according to the specific content of the risk factors, and the group activity scheme suitable for improving the risk factors can be automatically determined according to the scheme, so that the group can be assisted to adjust the psychological state.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a flow chart of a psychomotor training method according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a psychomotor training system in an embodiment of the present invention;

fig. 3 is a flowchart of a psychological data processing method according to an embodiment of the invention.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the description of the present invention, it should be noted that the terms "first", "second", and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.

In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

The invention provides a psychological adjustment training method, which is executed by electronic equipment such as a tablet personal computer, a server and the like in cooperation with special training equipment and is used for training the psychological adjustment capability of a user. As shown in fig. 1, the method comprises the following steps:

and S1, collecting a first physiological signal of the user. The first physiological signal may be any signal capable of reflecting the psychological condition of the human body, such as a pulse signal, an electromyogram signal, an electroencephalogram signal, a blood oxygen signal, and the like. In a preferred embodiment, the first physiological signal is a heart rate signal. The signal may be acquired by contact and/or non-contact sensors.

And S2, determining abnormal degrees of various psychological states according to the first physiological signal. The mental state may include some or all of neural balance, mood, mental stress, physical fatigue, ability to adapt.

Whether the psychological states are normal or not and the degree of abnormality can be calculated according to the physiological signals. There are various specific algorithms, and in a preferred embodiment, the degree of abnormality of various psychological states is obtained according to information analysis of Heart Rate Variability (HRV).

In this embodiment, the R-R interval in the heart rate signal is used as the basis for the HRV information analysis. Obtaining standard deviation SDNN of R-R interval of sinus cardiac rhythm and root mean square RMSS of difference value of adjacent R-R interval through time domain analysis by R-R interval and heart rate sampling frequency; by performing frequency domain analysis on the R-R interval, low frequency power LF, high frequency power HF, total power TP, and a ratio of low frequency power to high frequency power LF/HF may be obtained.

And obtaining power spectrum density and frequency through the specific numerical value and sampling rate of the R-R interval, and obtaining an LF value, an HF value and a TP value through the power spectrum density and frequency. The LF value is a low-frequency part of 0.04-0.14Hz on the power spectrum density, a plurality of power values of 0.04-0.14Hz on the power spectrum density are obtained according to a preset data length, the obtained plurality of powers are summed, and then the sum is multiplied by a preset coefficient to obtain the LF value. The HF value is a high-frequency part of 0.15-0.4Hz on the power spectral density, a plurality of power values of 0.15-0.4Hz on the power spectral density are obtained according to a preset data length, the obtained plurality of powers are summed, and then the sum is multiplied by a preset coefficient to obtain the HF value.

And the TP value is the total energy of 0-04Hz on the power spectrum density, a plurality of power values of 0-0.4Hz on the power spectrum density are obtained according to the preset data length, the obtained plurality of powers are summed, and then the sum is multiplied by a preset coefficient to obtain the TP value. The preset data lengths of the three parts can be the same or different.

After obtaining the psychological variability information, the abnormal degree of the neural equilibrium, the abnormal degree of the mental emotion, the abnormal degree of the mental stress, the abnormal degree of the physical fatigue and the abnormal degree of the adaptability of the user can be obtained according to the heart rate variability information.

Specifically, for example, quantified values of mood and nerve balance may be obtained from the ratio LF/HF of low frequency power to high frequency power; obtaining a quantized value of body fatigue according to the low-frequency power LF; obtaining a quantified value of the mental stress according to the high-frequency power HF; a quantified value of the adaptation capability is obtained from the total power, the standard deviation SDNN of the R-R interval of the sinus rhythm and the root mean square RMSSD of the difference values of the adjacent R-R intervals.

As an example, if the LF/HF value is greater than the first preset value, a random number X1 of LF/HF value + α is generated, otherwise, the random number X1 is directly taken as the LF/HF value, if the random number X1 is smaller than the second preset value, X1 × a is taken as the quantified value of the emotion, if the random number X1 is greater than the third preset value, X1 × b + c is taken as the quantified value of the emotion, if the value of the random number X1 is between the second preset value and the third preset value, d × X1 × e + f is taken as the quantified value of the emotion, wherein α, a, b, c, d, e, f are constants.

Regarding physical fatigue, if the LF value is smaller than a fourth preset value, a random number X2 with the LF value multiplied by β + gamma is generated, if the LF value is larger than the fourth preset value and smaller than a fifth preset value, the LF value is recorded as a random number X2., then the random number X2 is judged, if g is smaller than or equal to X2 and smaller than h, j X2-k is used as a quantized value of physical vigor, if m is smaller than or equal to X2 and smaller than n, p X X2-q is used as a quantized value of physical vigor, if h is smaller than or equal to X2 and smaller than m, r X2-s is used as a quantized value of physical vigor, wherein β, gamma, g, h, j, k, m, n, p, q, h, m, r and s are constants, and g, h, m and n are sequentially increased.

The quantified value of the mental stress can be obtained by judging the LF value, and the specific judgment method can be referred to the above method for judging the quantified value of the fatigue state, wherein the generated random number, the compared preset value and the multiplied coefficient are adaptively adjusted according to the LF value.

The adaptation capability is comprehensively judged through the total power, the standard deviation SDNN of the R-R interval of the sinus cardiac rhythm and the root mean square RMSSD of the difference value of the adjacent R-R intervals.

After the above numerical values are obtained, the degree of abnormality can be determined according to the magnitude of the numerical values. For example, in percent, the degree of abnormality in mental depression can be classified into three levels: the quantized values 20-30 are "light", the quantized values 10-20 are "medium", the quantized values 0-20 are "heavy", and the quantized values 30-70 are "healthy". Similarly, the level of mental anxiety can be divided into three levels: the quantized values 70-80 are "light", the quantized values 80-90 are "medium", and the quantized values 90-100 are "heavy".

Other mental state abnormality levels may refer to the above-described emotion level division method. For example, the abnormal level of physical fatigue may be classified as follows: a quantization value of 30-100 may be determined as "healthy", a quantization value of 20-30 may be determined as "light", a quantization value of 10-20 may be determined as "medium", and a quantization value of 0-10 may be determined as "heavy".

The abnormal level of mental stress may be classified as follows: a quantization value of 30-100 may be determined as "healthy", a quantization value of 20-30 may be determined as "light", a quantization value of 10-20 may be determined as "medium", and a quantization value of 0-10 may be determined as "heavy".

The abnormal level of adaptation capability may be divided as follows: quantization values of 0-70 may be determined as "healthy", quantization values of 70-80 may be determined as "light", quantization values of 80-90 may be determined as "medium", and quantization values of 90-100 may be determined as "heavy".

In the above example, the "light", "middle", and "heavy" are sequentially higher in the current level, and for example, the feeling of stress is stronger in the case where the level of the mental stress disorder is "heavy" than in the case where the level is "light".

As an alternative embodiment, a neural network classification model may also be used, the physiological signal of the user is used as input data of the model, and the output classification result is the level of the psychological state. Specifically, the classification result output by the model is vector data composed of a plurality of numerical values, wherein the numerical values are respectively used for representing a neural equilibrium abnormal level, a mental emotion abnormal level, a mental stress abnormal level, a physical fatigue abnormal level and an adaptability abnormal level.

Aiming at the five psychological states and the grades thereof, corresponding adjustment training schemes can be respectively determined. Unlike the treatment regimen, the adjustment training regimen is used to guide the user to autonomously adjust the mental state, and the regimen needs to be performed by various training devices.

And S3, determining a psychological adjustment training scheme according to the abnormal degrees of the various psychological states, wherein the psychological adjustment training scheme at least comprises information used for instructing the training equipment to execute the training action.

The training devices may include a variety of types, such as biofeedback devices, sound wave relaxation devices, breathing guidance devices, hypnosis devices, and the like, which perform different training actions, and the corresponding psychomotor training regimen includes content for instructing the various devices to perform the training actions.

This step may, for example, determine which device the user is adapted to use based on the degree of abnormality of various psychological states of the user, and may further determine the training intensity adapted to the user. Therefore, various information can be included in the mental adjustment training scheme, such as various parameters including device type information, the number of times and the time for which the device performs training, and the like.

As an example, the relationship between mental states and their degree of abnormality (grade) and the accommodative training regimen is shown in the following table:

in the above example, the 4 classes of mental states and 3 abnormal classes are combined as consistency, and thus 12 psychomotor training schemes can be corresponded. The contents of the 12 psychotropic training programs may be the same or different, and there may even be conflicts.

For example, if a user is light in stress level and heavy in physical effort level, two training protocols, protocol 4 and protocol 9, are first determined as alternatives. Since the user is required to be provided with a unique mental adjustment training scheme finally, when the contents of a plurality of schemes are different or conflict, the final training scheme is required to be generated according to the specific contents and abnormal grades in various alternatives in a coordinated mode.

More specifically, as an alternative embodiment, the number of times and frequency of training may be different for different psychological state levels. For example, the "lighter" the rank, the corresponding decrease in the number of trainings may be achieved, as may the corresponding decrease in the frequency.

For example, the content in the scenario 4 includes the training number of times equal to 1, and the content in the scenario 9 includes the training number of times equal to 4, and since the anomaly level corresponding to the scenario 9 is heavy, the training number of times in the finally determined training scenario is equal to 4. Other contents in the training scheme are similar to this example, and when it is determined that the user has a plurality of psychological states, the training schemes are not overlapped, and each training content is set according to the most serious level.

In a preferred embodiment, the training scheme comprises information for instructing a plurality of training devices to perform a training action. The information in the training scheme instructs various training devices to respectively execute training actions, and different action types are used for guiding the user to adjust the psychological state. Specifically, for example, for four types of training apparatuses, i.e., a biofeedback apparatus, a sound wave relaxation apparatus, a breathing guidance apparatus, and a hypnosis apparatus, information in the training program is divided into four groups, which are respectively applied to the four types of training apparatuses.

And S4, executing the training action by the training equipment according to the mental adjustment training scheme. This step may be performed passively, i.e. in response to user actions to perform a training action. By way of example, the training program may be stored in the server and associated with user information, and the user submits a personal information (login) query training program through the training device, determines how the training device should perform the training action, e.g., how many times it should perform, parameters that should be used during the performance (e.g., audio and video material, training duration, training goals), etc., and then initiates the training action.

According to the psychology adjustment training method provided by the invention, firstly, physiological signals of a user are collected, whether various psychological states of the user are abnormal or not is objectively determined based on the physiological signals, namely whether the various psychological states are abnormal or not under each psychological dimension respectively, the abnormal degree of each dimension is further determined, then a set of training scheme which can be executed by psychology adjustment training equipment is determined by combining the abnormal degrees of various psychological states, and the psychology adjustment training method has pertinence to various psychological state abnormalities of the user. And finally, one or more training devices are used for executing the scheme, and the training devices guide the user to learn and master the ability of adjusting the psychological state of the user, so that the psychological health of the user is promoted without the intervention of psychological experts.

Further, the training scheme may further include at least one of training frequency information, training material information, and training difficulty information of various types of training devices. The training frequency includes the total number and the usage frequency (e.g. several times per week, several times per month). The training material refers to video or audio material used by various training devices when performing training actions, for example, for a device which guides a user to adjust a psychological state by playing video or animation, the material information is used for indicating which videos or animations are used by the device; for example, for an apparatus that guides a user to adjust the psychological state by playing music, the material information is used to indicate what genre of music the apparatus uses; for example, for a device that guides a user to adjust the psychological state by playing a guidance word, the material information is used to indicate the content of the guidance word, and so on. The training difficulty information is information indicating that training conditions, completion conditions, and the like can affect the course of training actions performed by the training apparatus, and may be used to indicate at least the duration of a single training session, for example.

As an example, assuming that there are two types of training devices, step S3 determines that the information in the training scheme is as shown in the following table:

the scheme indicates which materials, times, frequencies and difficulties are respectively used by the two training devices to execute the training actions. Therefore, a detailed and targeted training scheme is provided for the user, the adjustment effect of the psychological state is optimized, and the work efficiency is high.

The total times of training in the table can be many times, and correspondingly, the difficulty information every time can be set to be different, for example, the training difficulty in front can be set to be easier and the training difficulty in back is gradually changed and difficult, the setting is to enable a user to adapt to the training process more quickly and easily, so that the ability of adjusting the psychological state is mastered more quickly, and the practicability and the efficiency of the method are improved.

When the user has a plurality of psychological states with abnormalities, the determined alternative training scheme may have the following conditions:

two alternative training scenarios are shown, namely a first row alternative training scenario corresponding to a severe abnormality in neuro-equilibrium and a second row alternative training scenario corresponding to a mild abnormality in mental stress. In the final training scheme, the parameters in the alternative with the abnormal grade of "heavy" can be directly adopted in terms of times, frequency and difficulty, but for material information, the parameters in the two alternatives should be integrated. For example, when the number of times of training is multiple, the material used each time can be set in the final training scheme so as to take account of the material a and the material b.

As an alternative embodiment, the difference between the current and historical mental state information and the difference between the current and historical mental adjustment training schemes can be determined, and the current mental adjustment training scheme can be adjusted according to the difference.

As an example, assuming that the current mental state level of a user is { A1}, the historical mental state level is { A0}, if { A1} represents that the mental state of the user is better (positive change) than { A0}, the historical mental adjustment training scheme has a better effect, in which case the current mental adjustment training scheme should be similar to the content thereof; if { A1} indicates that the user's mental state has not changed or even deteriorated compared to { A0}, it indicates that the historical psycho-adjustment training scheme is less effective, in which case a new training scheme different from its content should be provided.

The following describes the process of the training apparatus performing the training scheme. As a preferred embodiment, the training device acquires the physiological signals of the user in real time while performing the training action. Including for example heart rate, muscle power and respiratory rate, etc. The training devices are provided with corresponding sensors, the types of signals acquired by different types of training devices are different, for example, the physiological signals acquired by the biofeedback device include heart rate parameters, the physiological signals acquired by the breathing guidance device include breathing frequency, and the physiological signals acquired by the sound wave relaxation device include myoelectric parameters. For the purpose of distinguishing from the physiological signal acquired by the user terminal, the physiological signal acquired by the training device is referred to herein as a second physiological signal.

In a preferred embodiment, the training device collects a second physiological signal of the user during the execution of the psychometric training regimen, determines a target parameter based on the second physiological signal, and controls the execution of the training action based on a relationship between the second physiological signal and the target parameter over a period of time.

For example, the psychometric training scheme includes training difficulty information, and the training device may determine a coefficient according to the training difficulty information and determine the target parameter according to the second physiological signal and the coefficient.

Further, the training device adjusts the coefficient according to a relationship between the second physiological signal and the target parameter over a period of time.

As an example, the process of executing the training regimen may be divided into three phases (three time periods), where the first phase collects the second physiological signal of the user, and no action is performed to guide the psychological adjustment, but collects the current physiological signal of the user to provide basic information for the subsequent adjustment execution process. The training device 13 may determine the duration of the first stage according to the level of the psychological state. For example, a "light" level acquisition duration may be 3min, a "medium" level acquisition duration may be 3min, and a "heavy" level acquisition duration may be 5 min.

The training device calculates the average value of the physiological signal in the first phase as a physiological signal base value. Because the psychological state grades are different, and different psychological state grades correspond to different adjustment coefficients, a training target value (target parameter) can be determined according to the grades, namely the training target value is obtained by adjusting the physiological signal basic value by using the adjustment coefficients.

In order to ensure the training effect, the training target value can be set to be lower than the basic value, so that the user can relax the body and mind in the training process and master the method for autonomously reducing the physiological parameters. Taking heart rate as an example, if the base value is 80 times/min, the target value can be adjusted to 70-75 times/min. For example, when the psychological state level is "light", the adjustment factor may be 0.95-0.9; when the psychological state grade is 'middle', the adjusting coefficient can be 0.92-0.85; the adjustment factor may be 0.9-0.8 when the mental state level is "heavy". The more serious the psychological state grade is, the lower the corresponding adjustment coefficient is, so that the larger the difference between the basic value and the target value is, the more difficult the user wants to reduce the heart rate of the user to enable the heart rate to reach the target value. Conversely, the closer the training target value is to the base value, the lower the training difficulty, and the more suitable it is for the user with a lighter state.

The second phase is a guiding phase, and the training device plays video or audio and other materials to guide the user to adjust the state of the user so as to change the physiological signals. In the second phase the training device 13 will continuously monitor the physiological signal of the user and determine its relation to the target value, thereby controlling the process of the guiding operation.

The control methods executed by different types of training equipment are different, and the biofeedback training equipment is taken as an example for explanation, the biofeedback training equipment is provided with a display component, animation or video or virtual game scenes are displayed through the display component to improve the psychological state of a viewer, and the animation and the video or virtual game scenes are changed according to scenes corresponding to the second physiological information state. For example, when the heart rate is too high, the video/game is a scene which makes people feel worse, when the heart rate reaches a preset target, the video/game is a scene which makes people feel better, namely, as training progresses, the scene is controlled to be changed from worse to better through the second physiological signal, and the method and the used materials are contents which can influence the psychological state of the human body through psychological theory verification.

The following information may be included in a training protocol suitable for use with a biofeedback training device: training number information, i.e., the number of times the user should use the device; training time information, i.e., the playing time (video length or playing speed) of a video or game scene and training interval time information; the biofeedback training device can be used for pre-storing a plurality of video contents or game contents in the video material information or game scene information, namely specific contents of the video/game scene, and one of the video contents can be selected according to the video material information or the game scene information.

The specific control method of the biofeedback training equipment is as follows:

S1A, performing a guiding operation and comparing the physiological signal with the target parameter at a first preset time interval, wherein the physiological signal is a heart rate. Namely, the video is played to guide the user to adjust the psychological state and monitor the heart rate signal, if the number of the physiological signals is less than or equal to the target parameter, the step S1A is continuously executed, otherwise, the step S2A is executed.

And S2A, pausing the execution of the guide operation, counting and judging whether the pause time length exceeds the set time length, if not, executing the step S3A, otherwise, executing the step S4A. At this time, a guidance language can be played to prompt the user about the current situation so as to guide the user to adjust the psychological state.

S3A, comparing the physiological signal with the target parameter at a second preset time interval during the pause process, if the number of the physiological signals is larger than the target parameter, continuously executing the steps S2A-S3A, otherwise returning to the step S1A. Wherein the second predetermined time interval is less than the first predetermined time interval.

S4A, adjusting the coefficients to change the target parameters, and then returning to step S1A.

The third phase is a maintenance phase, in which the physiological signals are continuously collected but the comparison control is not performed, and the training is finished after the guiding action is continuously performed for a period of time.

In a specific embodiment, the biofeedback training equipment collects the heart rate basic value of the user, and obtains the heart rate state grade of the user, wherein the light collection time duration of the grade is 3min, the medium collection time duration of the grade is 3min, and the heavy collection time duration of the grade is 5 min; meanwhile, a guide word can be played, for example, the user can be prompted to start training immediately, and the training process and the attention matters in the training process can be explained.

After the basic values are collected, the training target value can be obtained according to the psychological state of the user, for example, the level "light" can be multiplied by 0.95 on the basis of the basic values, the level "medium" can be multiplied by 0.92 on the basis of the basic values, and the level "heavy" can be multiplied by 0.9 on the basis of the basic values, so that the training target value corresponding to the psychological state of the user is obtained.

And after the training target value is obtained, playing a guide word to prompt the user to start training, and playing a training material, namely a video material/game scene. At the moment, collecting a first physiological parameter, namely a heart rate parameter in real time, comparing a real-time collection value with a training target value, if the real-time collection value is smaller than or equal to the target value, continuously playing/continuously advancing a video scene, and collecting a modulation value and the training target value in real time again after a preset time interval of 20s for example;

if the real-time acquisition value is larger than the training target value, video pause/game scene switching is carried out, a guiding language is played, the user is prompted to not reach the training target, the user is guided to relax, and the real-time acquisition value and the training target value are compared once at regular time intervals, such as 3 s;

counting the pause time of the video, if the pause time exceeds a certain time, such as 30s, then increasing the training target value, for example, multiplying the original level as light by 0.95 on the basis of the basic value, continuing to play the video, judging the real-time acquisition value and the adjusted training target value, if the real-time acquisition value is less than or equal to the adjusted training target value, continuing to play the video, adjusting the training target value to the initial training target value, if the real-time acquisition value is greater than the training target value, pausing the playing of the video, and continuously comparing the adjusted training target value and the real-time acquisition value until the real-time acquisition value is less than or equal to the adjusted training target value, continuing to play the video, or after the training is finished.

If the heart rate signal of the user is not acquired in the training process, the guide words are played to prompt the user to correctly wear the physiological sensor.

The specific control method of the breathing guidance device is as follows:

S1B, executing a guiding operation and comparing the physiological signal with the target parameter at a first preset time interval, wherein the physiological signal is the breathing frequency. If the number of physiological signals is less than or equal to the target parameter, the step S1B is continuously performed, otherwise, the step S2B is performed.

S2B, the guidance operation is suspended, and a guidance phrase may be played to prompt the user about the current situation to guide the user in adjusting the breathing state.

S3B, comparing the physiological signal with the target parameter at a second preset time interval during the pause process, if the number of the physiological signals is larger than the target parameter, continuously executing the steps S2B-S3B, otherwise returning to the step S1B. Wherein the second predetermined time interval is less than the first predetermined time interval.

And a maintenance stage in the third stage, wherein the physiological signals are continuously acquired but the comparison control is not performed, and the training is finished after the guiding action is continuously performed for a period of time.

In a specific embodiment, the breathing guidance device collects a basic value of the breathing rate of the user, which may be referred to as the collection logic of the basic value of the heart rate in the above embodiment. And determining a training target value according to the basic value and the psychological state information of the user.

After the training target value corresponding to the psychological state of the user is obtained, the breathing of the user may be trained with reference to the training logic of the video apparatus in the above-described embodiment. The training logic of the respiratory training device and the video training device is similar, except that the respiratory training device does not modify the target parameter. The played video and the guide words can be adaptively adjusted according to different training projects of various devices.

The specific control method of the audio device is as follows:

S1C, executing a guiding operation for a period of time, namely playing music to guide a user to adjust the psychological state, and collecting a physiological signal which is a myoelectric signal at the moment.

And S2C, continuously executing the guiding operation and comparing the physiological signal with the target parameter at a first preset time interval, namely playing music to guide the user to adjust the psychological state and simultaneously collecting the electromyographic signal. The difference between the audio and video guiding operations is mainly that the video is a complete piece of content, the situation that the playing is finished and the audio is switched does not exist in the guiding process, and the audio is multiple, and the next piece of music needs to be switched after the playing is finished. Step S2C is performed if the number of physiological signals is less than or equal to the target parameter, otherwise step S3C is performed.

S3C, switching to another audio segment, and counting whether the switching reaches the set times, if not, executing step S2C, otherwise, executing step S4C. At this time, a guidance language can be played to prompt the user about the current situation so as to guide the user to adjust the psychological state.

S4C, adjusting the coefficients to change the target parameters, and then returning to step S2C.

In a specific embodiment, the audio device first collects the base value of the myoelectricity of the user, which may be referred to as the collection logic of the heart rate base value in the above embodiment.

And after the training target value is obtained, playing a guide word to prompt the user to start training and playing training music. Since a process is required for human relaxation, the average value of the myoelectric values collected for a certain period of time is compared with a training target value, and for example, the myoelectric values collected for the first three minutes of music playing may be averaged.

And if the average value is less than or equal to the training target value, continuing playing the music until the current music is played and switching to the next music. In this embodiment, the myoelectric average value of the first three minutes of each piece of music may be respectively compared with a training target value, if the average value is greater than the training target value, the music is switched, and a guide word is played to prompt the user to relax, if the music switching caused by the average value being greater than the training target value exceeds a preset number, for example, two, the training target value is adjusted upward, the original level "light" may be multiplied by 0.95 on the basis of the basic value, the level "medium" may be multiplied by 0.92X on the basis of the basic value, and the level "heavy" may be multiplied by medium 0.9 on the basis of the basic value, and the adjustment is: the level "light" may be multiplied by 0.98 on the basis of the basic value, the level "medium" may be multiplied by 0.96 on the basis of the basic value, and the level "heavy" may be multiplied by medium 0.95 on the basis of the basic value, and the music is continuously played.

If the average value is less than or equal to the adjusted training target value and the music can be played completely, the target value is adjusted to the initial training target value. If the average value is larger than the adjusted training target value, the adjusted training target value is used as the training target value to be compared with the average value until the average value is smaller than or equal to the adjusted training target value, and the music can be played completely or the training is finished.

The training device may perform the training action indicated by the adjustment training scheme without performing the control flow described above. For example, the training device is a hypnosis device, the hypnosis training device can collect electroencephalogram signals, play hypnosis music and guidance words, guide a user to sleep, determine the hypnosis duration according to the psychological state of the user, and play awakening guidance words after the set duration is reached. It follows that operations such as target value determination, suspension, etc. are not required during the hypnotic training.

The various durations and coefficients are all related to the difficulty information in the conditional training scheme, that is, the training difficulty information in the training scheme sent by the server 12 may be used by the training device to determine the durations and coefficients of the three phases.

In practical application, a user uses the system for multiple times to conduct psychological guidance training, so that the psychological health examination becomes a psychological health examination similar to physical examination. When the user uses the system for the first time, because no relevant record exists before, the psychological adjustment training scheme can be determined according to the mode in the embodiment, and when the method is continuously used later, the current scheme can be determined by integrating the psychological adjustment training scheme for one time or more times before. Specifically, the server 12 may determine a current mental state according to the current mental state, and then obtain historical mental state information and historical mental state information of the user, which are information obtained when the user uses the system before, and may be stored in the terminal or the server.

The embodiment of the invention also provides a psychological adjustment training system which comprises a data processing system and at least one training device. Wherein the data processing system is configured to perform the above steps S1-S3, and the training apparatus is configured to perform the step S4.

As an alternative embodiment, as shown in fig. 2, the psychomotor training system includes a terminal 11, a server 12, and a training device 13. Wherein the terminal 11 is adapted to perform steps S1-S2, the server is adapted to perform step S3, and the training device 13 is adapted to perform step S4. The terminal 11 is preferably a portable tablet computer and is equipped with contact and/or contactless heart rate and blood oxygen sensors.

The embodiment of the present invention further provides a method for processing psychological data, which can be executed by the terminal 11, or executed by the terminal 11 and the server 12 in a matching manner. As shown in fig. 3, the method comprises the following steps:

s1', the first physiological signal of the user is collected, which can be referred to as step S1 in the foregoing embodiment, and details are not repeated here.

S2', determining whether the psychological states are abnormal according to the first physiological signal, see step S2 in the foregoing embodiment, where the difference is that a specific abnormal degree may not be identified in this embodiment, and only two states, normal and abnormal, may be distinguished, and details are not described herein again.

And S3', obtaining a psychological assessment scale fed back by the user. For example, a psychological assessment scale may be provided to the user via the terminal 11, and the user's filling results of the scale may be received.

Specifically, the psychological assessment scale determines a numerical value according to psychological theory and psychological characteristics and behaviors such as the ability, personality, psychological health and the like of people. The psychological assessment table comprises a plurality of questions and corresponding several optional answers, for example, the question is "i easily fall asleep and sleep well", the corresponding answer is "none, sometimes, often and continuously", and the user can select one answer which is consistent with the condition of the user from the 4 answers as a feedback result of the questions.

At least some of the questions in the psychological assessment scale are configured to correspond to a number of first risk factors. Regarding the first risk factor, the specific content is the content which can have adverse effect on the mental health of the human, and may be some adverse tendency, such as a boon tendency, a happy tendency, etc.; or some experience or behavioral factors that can adversely affect the individual's mind, such as educational approaches, suffering penalties, etc. Through the feedback result of the user to the scale, it can be assessed whether the user has a certain bad tendency or whether the user is psychologically influenced by some experience or behavior, which is referred to as whether the user presents an abnormality on the risk factor in the invention.

For example, question 1 … i corresponds to a first risk factor A; the question i +1 … i + n corresponds to another first risk factor B, and all questions in the scale can represent multiple risk factors. The specific content of the first risk factor is related to the corresponding question data, for example, some question data in the scale reflect psychological questions brought by economic conditions, and the first risk factor corresponding to the questions is the "economic factor". Therefore, the first risk factor should be understood as a factor that generalizes some questions in the psychological assessment scale to a certain number of factors depending on the user's actual situation (occupation, environment, social identity, etc.).

And S4', determining whether each first risk factor is abnormal according to the psychological assessment scale fed back by the user. For example, it may be determined from at least the answer choices of the user to the question on which first risk factors the user presents an abnormality.

In a preferred embodiment, the feedback result of the user to the scale is converted into a numerical value (score) in a set quantification mode, and then whether each first risk factor of the user is abnormal or not is determined according to the numerical value, and the risk degree can be further measured. For example, the answer of the user to the question 1 … i is quantized to X, and the relationship between X and the set threshold is determined, so as to determine the risk degree of the user on the first risk factor a, which may be specifically classified as "normal", "light risk", "moderate risk" and "severe risk", and the meaning of these degrees is similar to the meaning of the above-mentioned psychological state grade, and will not be described herein again.

And S5', the abnormal psychological state is associated with the abnormal first risk factor. After determining the risk levels exhibited by the first risk factors, for the individual user, the risk levels of the respective first risk factors may be correlated with the mental states and levels to generate a mental analysis report for the individual user. For example, the mental state of a certain user is determined as physical fatigue and mental stress in an abnormal state (determined by the first physiological signal); and meanwhile, the risk degree (determined by the scale feedback result) of the first risk factor is determined to be that the social factors and the campus relationship are in abnormal states, and the physical fatigue and the mental stress abnormality are related to the social factors and the campus relationship abnormality.

Preferably, the personal psychological data analysis result may be generated to include information indicating whether or not the psychological state is abnormal, and when there is an abnormal psychological state, the abnormal first risk factor may be used as the information of the cause of the abnormal psychological state. Continuing with the above example, the report generated after association shows that "the cause of physical fatigue and mental stress is social factors and campus relations", that is, the first risk factor is the cause of the mental state abnormality.

In an alternative embodiment, another portion of the questions in the psychological assessment scale are configured to correspond to a number of second risk factors, the method further comprising: and determining whether each second risk factor is abnormal according to a psychological assessment scale fed back by the user, and generating information for prompting the user to perform psychological consultation when the abnormal second risk factors exist, wherein the information is used for supplementing or assisting a psychological state assessment result from a psychological angle.

The specific content of the second risk factor and the corresponding problem are related, but the specific content of the second risk factor is different from the first risk factor, and specifically can be content which has a larger influence on the mental health of people than the first risk factor, such as obsessive compulsive, anxiety, hostility, paranoia and the like.

Similarly to the risk degree determination manner of the first risk factor, the terminal 11 converts the question and answer results with the second risk factors into numerical values (scores) in a set quantitative manner, and then determines the risk degree presented by the user on each second risk factor according to the numerical values. The degree can be specifically classified as "normal", "mild sub-healthy", "moderate sub-healthy", and "severe sub-healthy", and the meaning of these degrees is similar to the above-mentioned psychological state grade meaning, and will not be described herein again.

For the individual user, after determining the degree of abnormality presented by the second risk factor, the psychological analysis report for the individual user may prompt the user to advise the user to perform psychological consultation, which is different from the above-mentioned psychological adjustment training scheme, and the psychological consultation specifically refers to a process of providing psychological assistance to a requester who has a problem in psychological adaptation and seeks to solve the problem by applying a psychological method by a psychologist.

The contents of the scale, the first risk factor, the second risk factor, etc. may be set according to different people, for example, the contents are different for minor, military police, official inspection, comprehensive treatment, and social personnel.

As a specific example, a suitable underage scale is provided, e.g. for underage characteristics, and the following 13 first risk class factors are selected: learning factors, family environment, physical and mental health, education and nourishment modes, interpersonal relationship, social factors, legal consciousness, deficiency and honor-mental tendency, curiosity tendency, victory-mental tendency, emotional stability, punishment and loss, and 6 second risk factors: adaptability, obsessive-compulsive, depression, anxiety, paranoia, enemy, etc. For the individuals with severe abnormality in the conclusion of the last 6 factors, the reason of the psychological abnormality can be found by the first 13 factors, and besides the training of relying on the training equipment, the psychological counseling can be pertinently suggested to the individuals.

The embodiment of the present invention further provides a group psychological data processing method, which can be configured and executed by the terminal 11 and the server 12, and first collect and process psychological data of a plurality of users according to the method shown in fig. 3. In this embodiment, the first risk factor in the psychometric scale is configured to correspond to the group assistance program data.

Each first risk factor corresponds to a group mental state assistance adjustment scheme (hereinafter referred to as a group assistance scheme). For example, the first risk factor a corresponds to a community assistance scheme a and the first risk factor B corresponds to a community assistance scheme B, wherein the content of the community assistance scheme a and the community assistance scheme B may be the same or different. The specific content of the community assistance scheme is related to the specific content of the first risk factor, for example, one first risk factor is "economic factor", and the corresponding community assistance scheme is to suggest participation in community activities for establishing correct value views, and the like.

After obtaining the heart rate data of the group, it is determined whether the number of users having the same and abnormal first risk factor exceeds a set threshold. And when the number exceeds a set threshold value, acquiring the community auxiliary scheme data corresponding to the abnormal first risk factor.

Specifically, the server 12 counts the risk degrees of the first risk factors of the group users, and obtains the group assistance scheme corresponding to a certain proportion of the first risk factors when the risk degrees of the first risk factors of the users exceed certain proportions and are all abnormal (including mild, moderate, and moderate).

Further, a group psychology data analysis result including the user number information of the first risk factor having the abnormality and the group assistance plan data may be generated. Prompt information may also be presented in a psychoanalytic report for the community suggesting that the community perform a community assistance program corresponding to the first risk factor.

In a preferred embodiment, the first risk factors are configured to correspond to several group risk factors, a plurality of first risk factors simultaneously corresponding to a certain group risk factor. For example, learning factors, home environment, physical and mental health, punishment, and loss of these 5 first risk factors correspond to a group risk factor of "stability"; the 6 first risk factors of social factors, legal consciousness, feeble and honor tendency, curiosity tendency, victory tendency and emotional stability correspond to the group risk factor of 'safety'; the 2 first risk factors of education, interpersonal relationship correspond to a team risk factor of "fitness", and so on.

The server 12 will determine whether the above-mentioned group risk factor is present based on the degree of abnormality of the first risk factors of the plurality of users. Specifically, the risk degree of a first risk factor of a user is counted, and when the risk degree of a certain first risk factor of the user exceeding a certain proportion is abnormal (including mild, moderate and moderate), if the first risk factor corresponds to a "group risk factor a", prompt information will be presented in a psychological analysis report for a group to prompt the group risk factor a of the group to have a higher risk.

As a specific example, a unit participating in the above evaluation has a total of 2000 people, wherein 35% (700 people) of "learning factors" are concluded as mild/moderate/severe, i.e. it is indicated that there is a higher risk in the group stability (group risk factor) of the unit, and it needs to be solved accordingly: the team is suggested to execute a group auxiliary scheme with the main topic of thinking and concentration, so that the adverse effect caused by the first risk factor is avoided from the perspective of group management.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, 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 specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.

Claims

1. A method for processing psychological data, comprising:

collecting a first physiological signal of a user;

2. The method of claim 1, wherein determining whether each of the first risk factors is abnormal according to a psychometric scale fed back by a user comprises:

3. The method according to claim 1, wherein associating the mental state of an abnormality with the first risk factor of an abnormality comprises:

4. The method of any one of claims 1-3, wherein at least a portion of the question data in the psychometric scale is configured to correspond to a number of second risk factors; the method further comprises the following steps: and determining whether each second risk factor is abnormal according to a psychological assessment scale fed back by the user, and generating information for prompting the user to perform psychological consultation when the abnormal second risk factors exist.

5. The method of claim 1, wherein the mental states include neural balance, mood, mental stress, physical fatigue, and ability to adapt.

6. The method of claim 1, wherein determining the degree of abnormality for the plurality of mental states based on the first physiological signal comprises:

7. A method for processing group psychological data, comprising:

processing mental data of a plurality of users using the method of any of claims 1-6, wherein the first risk factor in the mental metric scale is configured to correspond to group assistance program data;

8. The method of claim 7, further comprising, after obtaining community assistance program data corresponding to the abnormal first risk factor:

9. A psychological data processing device, characterized by comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to cause the at least one processor to perform a method of processing mental data according to any of claims 1-6.

10. A psychological data processing device, characterized by comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to cause the at least one processor to perform the group mental data processing method according to claim 7 or 8.