CN106923846B - Psychological stress assessment and feedback system - Google Patents
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Abstract
The invention is suitable for the technical field of health control, and provides a psychological stress assessment and feedback system, which comprises the following steps: receiving sample data acquired by physiological data acquisition equipment and a psychological data acquisition terminal, wherein the sample data is a characteristic data matrix which is specifically constructed by physiological characteristic data and psychological characteristic data; performing preliminary evaluation on the psychological characteristic data and the physiological characteristic data by using a fuzzy C-means algorithm and an ordered weighted arithmetic mean operator respectively to obtain respective classification recognition results; performing secondary classification on whether the classification recognition result with the psychological pressure exists or not according to the decision-making layer fusion model, and outputting a secondary classification result with the psychological pressure; and taking the secondary classification result as the input of a statistical model, and obtaining the individual psychological pressure quantized value according to a Cylinder pressure quantized function based on the pressure system theoretical model. The invention realizes the graded quantitative evaluation of the psychological pressure.
Description
Technical Field
The invention belongs to the technical field of health control, and particularly relates to a psychological stress assessment and feedback system.
Background
Psychosomatic Medicine (Psychosomatic Medicine) is a border Medicine of multidisciplinary junction for researching the relationship among various factors such as biology, psychology and sociology which influence human health and the occurrence and development process of diseases, and prompts people to know the essence of life, health and diseases more comprehensively and deeply. Psychosomatic diseases are a group of somatic diseases related to mental stress, have manifestations of organic lesions or defined pathophysiological processes, and psychosocial factors play an important role in the occurrence, development, treatment and prognosis of diseases. According to the investigation of some developed countries, in outpatients of a comprehensive hospital, a little higher than 1/3 is body disease, less than 1/3 is neurosis, and the rest 1/3 is psychosomatic disease, and the academic world considers that the psychology and related social factors and the like are clinically applied to the multi-aspect, multi-level and multi-dimensional analysis of the psychosomatic disease so as to make two-way diagnosis, evaluation and intervention of 'organic disease' of the biological body and 'maladaptation' of the psychology and society.
The existing chinese patent CN103211603A provides a psychological pressure detection tracking feedback system, which includes a signal collector for collecting an electrocardiographic signal when a human body receives training; the signal converter is used for converting the acquired physiological signals into digital signals; the processor is used for converting the digital signal into a coordination value, storing the coordination value into the memory, comparing and calculating the coordination value and outputting a result to the display; the display is used for displaying the HRV curve and data in real time and displaying the training system, the detection method and the feedback training are simple, and the evaluation result is rough.
The existing psychological pressure detection feedback system only refers to physiological monitoring data for evaluation, and can not achieve subjective and objective combination, and multi-level quantification is used for evaluating the psychological pressure for feedback.
Disclosure of Invention
The embodiment of the invention provides a psychological pressure assessment and feedback system, and aims to solve the problems that evaluation is carried out only by referring to physiological monitoring data, subjective and objective combination cannot be achieved, and psychological pressure is assessed in a multi-level quantification mode to carry out effective feedback.
Providing a psychological stress assessment and feedback system, the system comprising: the physiological data acquisition equipment and the psychological data acquisition terminal are respectively communicated with the pressure data processing terminal through a wireless or wired network, the pressure data processing terminal is communicated with the pressure feedback terminal through a wireless or wired network, wherein,
the physiological data acquisition device is used for acquiring physiological characteristic data, and the physiological characteristic data comprises: the method comprises the steps of obtaining an electrocardiosignal and a characteristic value thereof, and obtaining a respiratory signal and a characteristic value thereof, wherein the electrocardiosignal and the characteristic value thereof comprise characteristics based on an electrocardiogram waveform, heart rate rhythm mode and heart rate variation; the respiratory signal and the characteristic value thereof comprise a respiratory rhythm mode characteristic, a respiratory statistic characteristic and a respiratory waveform characteristic;
the psychological data acquisition terminal is used for acquiring psychological characteristic data, and the psychological characteristic data comprises: the system comprises an autonomous evaluation scale characteristic and a social behavior evaluation scale characteristic, wherein the autonomous evaluation scale characteristic comprises individual information, thinking ability, emotional health and complete personality; the social behavior evaluation scale features comprise environmental adaptation, living habits and interpersonal communication;
the pressure data processing end comprises:
the data receiving unit is used for receiving sample data acquired by the physiological data acquisition equipment and the psychological data acquisition terminal;
the primary classification unit is used for performing primary evaluation on the physiological characteristic data and the psychological characteristic data by using a fuzzy C-means algorithm and an ordered weighted arithmetic mean operator respectively to obtain respective classification recognition results;
the secondary classification unit is used for carrying out secondary classification on whether the classification recognition result with psychological pressure exists according to the decision-making layer fusion model and outputting a secondary classification result with psychological pressure;
and the pressure quantization unit is used for taking the secondary classification result as statistical model input and acquiring an individual psychological pressure quantization value according to a Cylinder pressure quantization function based on a pressure system theoretical model.
Further, the classification recognition result includes a health status, a moderate psychological pressure and a severe psychological pressure, the classification recognition result with the psychological pressure is specifically the moderate psychological pressure and the severe psychological pressure, the secondary classification unit is specifically configured to determine whether the classification recognition result with the moderate psychological pressure and the severe psychological pressure is a benign pressure according to the decision-making layer fusion model, if the classification recognition result with the moderate psychological pressure and the severe psychological pressure is a benign pressure, the current classification recognition result is classified as a no-pressure status, i.e., a health status, and if the classification recognition result with the moderate psychological pressure is not a benign pressure, the current classification recognition result is classified as a secondary classification result with the psychological pressure.
Further, the pressure data processing end further comprises:
the pressure judging unit is used for judging whether the individual psychological pressure quantized value is larger than a preset threshold value or not;
the pressure feedback unit is used for sending the information of the existing psychological pressure to the pressure feedback terminal to perform pressure feedback training if the quantized value of the individual psychological pressure is larger than a preset threshold value;
further, the pressure feedback terminal is used for receiving the existing psychological pressure information and performing physiological intervention on the physiological characteristic data respectively, and performing psychological intervention on the physiological characteristic data.
Further, the Cylinder pressure quantization function f (t) is specifically:
wherein rho is the density of the liquid and is also the stress category or the cause of pressure generation, L is the length of the bottom and is also the maximum pressure bearing capacity of an individual, H is the stress intensity and is also the pressure intensity, the value range of H is 1< H < H, and t is time, namely the pressure duration.
The embodiment of the application has the following advantages:
the method has the advantages that multiple physiological parameter characteristic values are adopted, psychological scale characteristic values are combined, active psychological pressure is eliminated through subjective and objective combination, the psychological pressure is accurately classified in a multi-stage mode through combination of a fuzzy theory and a decision layer information fusion model, influence mechanisms of environmental adaptation, cognitive interaction and autonomous evaluation on the psychological pressure are fully considered, a Cylinder quantization function based on a pressure system model is established, accordingly, graded and quantitative evaluation on the psychological pressure is achieved, meanwhile, high fusion of psychological pressure evaluation and personalized biofeedback intervention is achieved, and physical and psychological adjustment of pressure crowds is facilitated.
Drawings
Fig. 1 is a block diagram illustrating a detailed structure of a psychological stress assessment and feedback system according to an embodiment of the present invention;
fig. 2 is a block diagram of a detailed structure of a pressure data processing end according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a Cylinder pressure quantification model provided in the first embodiment of the present invention;
fig. 4 is a Cylinder space model diagram and a mathematical model diagram of the Cylinder according to the first embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following detailed description of the implementation of the present invention is made with reference to specific embodiments:
example one
Fig. 1 is a block diagram showing a detailed structure of a psychological stress assessment and feedback system according to an embodiment of the present invention, and only the parts related to the embodiment of the present invention are shown for convenience of illustration. In this embodiment, the psychological stress assessment and feedback system includes a physiological data collecting device 1, a psychological data collecting terminal 2, a stress data processing terminal 3 and a stress feedback terminal 4, wherein the physiological data collecting device 1 and the psychological data collecting terminal 2 are respectively communicated with the stress data processing terminal 3 through a wireless or wired network, the stress data processing terminal 3 is communicated with the stress feedback terminal 4 through a wireless or wired network,
the physiological data acquisition device 1 is configured to acquire physiological characteristic data, which includes: the method comprises the steps of obtaining an electrocardiosignal and a characteristic value thereof, and obtaining a respiratory signal and a characteristic value thereof, wherein the electrocardiosignal and the characteristic value thereof comprise characteristics based on an electrocardiogram waveform, heart rate rhythm mode and heart rate variation; the respiratory signal and the characteristic value thereof comprise a respiratory rhythm mode characteristic, a respiratory statistic characteristic and a respiratory waveform characteristic;
the psychological data acquisition terminal 2 is used for acquiring psychological characteristic data, and the psychological characteristic data comprises: the system comprises an autonomous evaluation scale characteristic and a social behavior evaluation scale characteristic, wherein the autonomous evaluation scale characteristic comprises individual information, thinking ability, emotional health and complete personality; the social behavior evaluation scale features comprise environmental adaptation, living habits and interpersonal communication;
wherein, the pressure data processing terminal 3 shown in fig. 2 includes:
the data receiving unit 31 is used for receiving sample data acquired by the physiological data acquisition equipment and the psychological data acquisition terminal;
and the primary classification unit 32 is used for performing primary evaluation on the physiological characteristic data and the psychological characteristic data by using a fuzzy C-means algorithm and an ordered weighted arithmetic mean operator respectively to obtain respective classification recognition results.
In this embodiment, the classification recognition result includes a health status, a moderate psychological stress and a severe psychological stress, wherein the classification recognition result of the psychological stress is specifically the moderate psychological stress and the severe psychological stress. In the following description, the health state, the moderate psychological stress and the severe psychological stress are taken as three clustering centers, the fuzzy C-means algorithm is a very effective fuzzy clustering algorithm, and specifically, the set of the psychological stress state levels to be classified is assumed as follows:
the collection is limited data, namely a collection of physiological characteristic data and psychological characteristic data, the element x is a d-dimensional vector, and a fuzzy partition matrix (u) is foundij)c×nAnd c cluster center points V ═ V1,v2,...,vcLet the objective function:
satisfies the following conditions:
wherein m ∈ [1, + ∞]Called fuzzy weight coefficient, uijCalled degree of membership, xjRepresenting the degree of membership of the vector to the centre point, d (x)jVi) is the objective function xjEuclidean distance from vi.
There are a number of factors due to the development of psychological stress: psychological, physiological, social and environmental factors and the like, wherein the influence of the factors on the formation and development of psychological stress is different from person to person, the clustering method has obvious subjectivity and individual difference, and a clustering result obtained by only a fuzzy C-means algorithm has many unreasonable conditions, such as different tolerances of environmental difference, social status difference and physical condition difference on the psychological stress, so that the unreasonable conditions formed by the individual difference are reduced as much as possible by constructing an ordered weighted average operator.
In addition, the ordered weighted arithmetic mean operator OWA for the psychographic data can be defined as:
let function OWA: Rn→ R, if:
Its advantage is high effect on the psychological and physiological characteristics of magnitude data1,a2,...,an) Re-ordering in descending order and clustering by weight, due to the magnitude aiAnd the weight value wjHas no relation with the position of the magnitude in the aggregation process, so that the psycho-physiological characteristic vector x of the sample individual can be obtained by using the ordered weighted arithmetic mean operatori(i 1,2, 3..) are aggregated to obtain a comprehensive attribute value Zi(w) according to Zi(w) the schemes are ranked and preferred according to the size, so that individual differences caused by various factors such as environment, social status and the like can be well eliminated.
And the secondary classification unit 33 is configured to perform secondary classification on whether the classification recognition result with the psychological stress is benign or not according to the decision-making layer fusion model, and output a secondary classification result with the psychological stress.
In this embodiment, the classification recognition result with psychological stress specifically includes moderate psychological stress and severe psychological stress, the secondary classification of whether the classification recognition result with psychological stress is benign or not is performed according to the decision-making layer fusion model, and the outputting the secondary classification result with psychological stress specifically includes:
and judging whether the classification recognition results of the moderate psychological pressure and the severe psychological pressure are benign pressure or not according to the decision-making layer fusion model, if so, classifying the current classification recognition results into a non-pressure state, namely a healthy state, and if not, classifying the current classification recognition results into a secondary classification result with the psychological pressure.
Among them, psychological stress can be regarded as positive, i.e., benign stress to some extent, and can enhance alertness and productivity of people, especially when arousal reaches an optimal level. However, this is limited and, once exceeded, can cause serious problems for the individual and may even result in directly life-threatening symptoms. The step S102 can identify three states of health, moderate psychological pressure and severe psychological pressure for the primary classification of the psychological pressure, but whether the psychological pressure is benign or not can not be evaluated, so the secondary classification is carried out on the moderate and severe psychological pressure states in the step, a decision layer fusion model based on a D-S evidence theory is constructed for the secondary classification, the method has the advantages that the physical relation among various information sources is not required to be accurately known, feature processing and identification methods suitable for different types of information sources can be respectively adopted, only the result of classification identification needs to be applied to the fusion model, and the established fusion model is independent of various types of specific information and has universal applicability.
Specifically, a fusion function is constructed according to the characteristic that uncertainty reasoning is carried out on the basis of a basic probability distribution function mass in a D-S evidence theory, and a final fusion result is obtained. Assuming that two types of targets to be identified and three types of local judgment processes exist in the fusion system, different information sources represent different evidence bodies, and identification of the mental stress state is taken as a research target, the mental stress identification framework is represented as { Pr1, Pr2}, wherein Pr1 represents the state of mental stress, and Pr2 represents the state of no mental stress. Assuming that C is a recognition space and the whole subset is 2C, m: 2C → [0, 1], referred to as a basic probability assignment, that is, assigning probabilities according to the magnitude of the psychological stress correlation to eigenvalues satisfying the condition in the recognition space, wherein the assigned probabilities need to satisfy the condition:
where m (a) represents the fundamental probability assignment for each psychographic feature data. The trust function of the recognition target A (with pressure or not) is represented as Bel (A), and is a lower limit function of the trust degree of the recognition target, and the relationship between the trust function and the basic probability assignment is shown as the following formula:
the likelihood function of the recognition target A is expressed as Pls (A), is an upper limit function of the confidence level that the recognition target A has the pressure state, and is established on the basis that the object which is opposite to the A in the recognition space, namely the object without the mental pressure state is considered to be false, and the calculation method of Pls (A) is shown as the following formula;
the uncertainty of identifying object a is formed by a likelihood function pls (a) and a confidence function bel (a), i.e. the difference between the probability of trusting object a as stressed and the probability of trusting object a as true, expressed as m (Δ) as follows:
m(Δ)＝Pls(A)-Bel(A)
when there are multiple evidence bodies, the probability assignment for identifying the target is the subject of the fusion process by combining the multiple evidence bodies according to a certain combination rule. Fusing a plurality of evidence bodies to obtain a trust function of A as shown in the following formula:
in the formula, K represents the degree of conflict between evidence bodies, namely, the tolerance to psychological stress is inconsistent, physiological characteristics are changed, psychological characteristics are not changed, when the value of K is closer to 1, the conflict between the evidence bodies is larger, and when K is equal to or larger than 1, the evidence bodies are completely rejected, so that the degree of conflict between the evidence bodies is calculated before fusion, and only when the value of K is in the range of (0, 1), namely, the psychological characteristics show consistent reaction to psychological stress, the relevant evidence bodies can be fused. K is calculated as follows:
in the recognition space of the present embodiment, there are only two recognition targets, i.e. psychological stress and no psychological stress, so the likelihood function pls (a) and the confidence function bel (a) are the same, and the uncertainty probability is zero. Thus, Bel (A) becomes the most important reference and decision criterion for mental stress state. The decision of the psychological stress assessment result is according to the following rules:
the finally judged target identification state trust function value is the largest among all the target trust function values;
the finally judged target identification state trust function value meets Bel (F)i) > 0.5 and at least 2 times the value of the other objective belief functions.
And the pressure quantification unit 34 is used for taking the secondary classification result as statistical model input and obtaining an individual psychological pressure quantification value according to a Cylinder pressure quantification function based on a pressure system theoretical model.
In this embodiment, the pressure system theoretical model is shown in fig. 3, the Cylinder theoretical model regards the stressness of the internal and external environment as pressure "liquid", the level of the liquid in the Cylinder represents the stressness strength, the hydraulic pressure borne by the cross bar reflects the current pressure level of the individual, the width of the Cylinder corresponds to the individual's ability to handle the pressure, the density of the "liquid" reflects the concentration of the internal and external stressness, and the chronic pressure will lead to the increase of the height of the "liquid" in the Cylinder, and thus the pressure borne by the cross bar. When the level of the liquid reaches a threshold level, the individual may feel significant stress, and when the level reaches a threshold level, physical and psychological functions may be severely impaired, and diseases may be induced or even death may result. Different exciting factors are divided into a trigger factor and a relieving factor, the trigger factor raises the liquid height, and the relieving factor lowers the liquid height, so that the influence of the trigger factor can be reduced by applying a proper intervention means, the function of the relieving factor is enhanced, and the purpose of releasing pressure is achieved.
Mapping the Cylinder theoretical model to a three-dimensional space and a two-dimensional plane, as shown in FIG. 4, and performing mathematical modeling
F＝P×S
Where P represents the weight of the liquid, S represents the area of the bottom, and F represents the pressure to which the bottom is subjected.
If the length 'L', height 'H', and density 'ρ' of the liquid, and the acceleration of weight 'g' (time constant) are given as follows, the functional expression of the established personal pressure evaluation model is as follows:
F(t)＝P(t)×S(t)＝∫∫δρgh(t)dxdy
calculating the Cylinder pressure quantification function F (t) by the formula:
wherein rho is the density of the liquid and is also the stress category or the cause of pressure generation, L is the length of the bottom and is also the maximum pressure bearing capacity of an individual, H is the stress intensity and is also the pressure intensity, the value range of H is 1< H < H, and t is time, namely the pressure duration.
The Cylinder theoretical model comprehensively considers physiological, psychological, social and environmental factors, researches the relationship between the multi-source information characteristic vector and the model factor through the information fusion technology, and finally obtains the personalized psychological pressure assessment quantitative index through continuous experimental optimization and correction.
Further, the classification recognition result includes a health status, a moderate psychological pressure and a severe psychological pressure, the classification recognition result with the psychological pressure is specifically the moderate psychological pressure and the severe psychological pressure, the secondary classification unit 33 is specifically configured to determine whether the classification recognition result with the moderate psychological pressure and the severe psychological pressure is a benign pressure according to the decision-making layer fusion model, if the classification recognition result with the moderate psychological pressure and the severe psychological pressure is a benign pressure, the current classification recognition result is classified as a no-pressure status, i.e., a health status, and if the classification recognition result with the moderate psychological pressure is not a benign pressure, the current classification recognition result is classified as a secondary classification result with the psychological pressure.
Further, after the obtaining of the individual mental stress quantified value, the classifying identification result being severe mental stress, and the classifying identification result being classified as a secondary classifying result with mental stress, the stress data processing end further includes:
the pressure judging unit 35 is configured to judge whether the individual psychological pressure quantized value is greater than a preset threshold value;
and the pressure feedback unit 36 is configured to send the existence psychological pressure information to the pressure feedback terminal for performing pressure feedback training if the individual psychological pressure quantization value is greater than a preset threshold value.
Further, the pressure feedback terminal is used for receiving the existing psychological pressure information and performing physiological intervention on the physiological characteristic data respectively, and performing psychological intervention on the physiological characteristic data.
Further, the Cylinder pressure quantization function f (t) is specifically:
wherein rho is the density of the liquid and is also the stress category or the cause of pressure generation, L is the length of the bottom and is also the maximum pressure bearing capacity of an individual, H is the stress intensity and is also the pressure intensity, the value range of H is 1< H < H, and t is time, namely the pressure duration.
In the embodiment, multiple physiological parameter characteristic values are adopted, psychological scale characteristic values are combined, active psychological pressure is eliminated through subjective and objective combination, the psychological pressure is accurately classified in a multi-stage mode through combination of a fuzzy theory and a decision layer information fusion model, influence mechanisms of environmental adaptation, cognitive interaction and autonomous evaluation on the psychological pressure are fully considered, and a Cylinder quantization function based on a pressure system model is established, so that graded quantitative evaluation on the psychological pressure is realized, meanwhile, high fusion of the psychological pressure evaluation and personalized biofeedback intervention is realized, and physical and psychological adjustment of pressure crowds is facilitated.
It should be noted that, in the above system embodiment, each included unit is only divided according to functional logic, but is not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, controller, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application 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.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. 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 terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create a controller 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 terminal 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 terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The psychological stress assessment and feedback system provided by the present application is introduced in detail above, and the principle and the implementation of the present application are explained in the present application by applying specific examples, and the description of the above examples is only used to help understanding the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (4)
1. A psychological stress assessment and feedback system, said system comprising: the physiological data acquisition equipment and the psychological data acquisition terminal are respectively communicated with the pressure data processing terminal through a wireless or wired network, the pressure data processing terminal is communicated with the pressure feedback terminal through a wireless or wired network, wherein,
the physiological data acquisition device is used for acquiring physiological characteristic data, and the physiological characteristic data comprises: the method comprises the steps of obtaining an electrocardiosignal and a characteristic value thereof, and obtaining a respiratory signal and a characteristic value thereof, wherein the electrocardiosignal and the characteristic value thereof comprise characteristics based on an electrocardiogram waveform, heart rate rhythm mode and heart rate variation; the respiratory signal and the characteristic value thereof comprise a respiratory rhythm mode characteristic, a respiratory statistic characteristic and a respiratory waveform characteristic;
the psychological data acquisition terminal is used for acquiring psychological characteristic data, and the psychological characteristic data comprises: the system comprises an autonomous evaluation scale characteristic and a social behavior evaluation scale characteristic, wherein the autonomous evaluation scale characteristic comprises individual information, thinking ability, emotional health and complete personality; the social behavior evaluation scale features comprise environmental adaptation, living habits and interpersonal communication;
the pressure data processing end comprises:
the data receiving unit is used for receiving sample data acquired by the physiological data acquisition equipment and the psychological data acquisition terminal;
the primary classification unit is used for performing primary evaluation on the physiological characteristic data and the psychological characteristic data by using a fuzzy C-means algorithm and an ordered weighted arithmetic mean operator respectively to obtain respective classification recognition results;
the secondary classification unit is used for carrying out secondary classification on whether the classification recognition result with psychological pressure exists according to the decision-making layer fusion model and outputting a secondary classification result with psychological pressure;
the pressure quantization unit is used for taking the secondary classification result as statistical model input and acquiring an individual psychological pressure quantization value according to a Cylinder pressure quantization function based on a pressure system theoretical model;
the ordered weighted arithmetic mean operator OWA for the psychological characteristic data is defined as:
function OWA Rn→ R, if:
the Cylinder pressure quantification function F (t) is specifically as follows:
wherein rho is the density of the liquid and is also the cause of irritability or pressure generation, L is the length of the bottom and is also the maximum bearing capacity of an individual, H is the intensity of irritability and is also the pressure intensity, the value range of H is 1< H < H, and t is time, namely the pressure duration.
2. The system for assessing and feeding back psychological stress according to claim 1, wherein the classification recognition results include a healthy state, a moderate psychological stress and a severe psychological stress, the classification recognition results of the psychological stresses are specifically the moderate psychological stress and the severe psychological stress, the secondary classification unit is specifically configured to determine whether the classification recognition results of the moderate psychological stress and the severe psychological stress are benign stress according to the decision-level fusion model, if so, the current classification recognition result is classified as a healthy state without stress, and if not, the current classification recognition result is classified as a secondary classification result with psychological stresses.
3. The psychological stress assessment and feedback system according to claim 1, wherein said stress data processing terminal further comprises:
the pressure judging unit is used for judging whether the individual psychological pressure quantized value is larger than a preset threshold value or not;
and the pressure feedback unit is used for sending the information of the existing psychological pressure to the pressure feedback terminal to perform pressure feedback training if the quantized value of the individual psychological pressure is larger than a preset threshold value.
4. The mental stress assessment and feedback system according to claim 3, wherein said stress feedback terminal is configured to receive said existing mental stress information for performing a physiological intervention on said physical characteristic data and for performing a psychological intervention on said physical characteristic data, respectively.
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| WO2019037045A1 (en) * | 2017-08-24 | 2019-02-28 | 华为技术有限公司 | Psychological stress assessment method and apparatus |
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