CN116636846B - Mental stress monitoring and intervention management system - Google Patents
Mental stress monitoring and intervention management system Download PDFInfo
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- 230000003340 mental effect Effects 0.000 title claims abstract description 65
- 238000012544 monitoring process Methods 0.000 title claims abstract description 26
- 238000001514 detection method Methods 0.000 claims abstract description 38
- 230000006996 mental state Effects 0.000 claims abstract description 14
- 238000007781 pre-processing Methods 0.000 claims abstract description 10
- 238000012216 screening Methods 0.000 claims abstract description 8
- 230000003247 decreasing effect Effects 0.000 claims description 16
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- 230000008451 emotion Effects 0.000 claims description 5
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Abstract
The invention discloses a mental stress monitoring and intervention management system, which comprises: mental stress analyzer: quantitatively evaluating the mental stress of the user; and a data recording module: extracting a pressure value; and a data preprocessing module: acquiring all pressure values at this time, generating a reference set, and calculating the difference value between each pressure value and a preset normal pressure value; and a screening module: acquiring the difference value, screening out elements with absolute values larger than or equal to a preset change threshold value, and generating a detection sequence; and an analysis module: calculating the change interval between adjacent items of the detection sequence, and judging the type of each node; and an intervention module: and judging the mental state of the user, and sending an adjustment request at the beginning of the next detection period. Compared with the prior art, the method and the device can reflect the mental change index of the user in the detection period, and further achieve the effect of monitoring the period change rule of the user.
Description
Technical Field
The invention relates to the technical field of mental stress monitoring, in particular to a mental stress monitoring and intervention management system.
Background
Mental stress, also called psychological stress, is a major factor in mental sub-health and is also a major cause of mental diseases. Psychological diseases are common diseases in modern society, and a highly developed industrial system brings abundant substances to people, creates huge wealth and brings a great deal of pressure on work and life. Mental stress is almost caged on all people, especially young people in the age of twenty-three years, the current population experiencing the greatest stress in all ages in china. Psychological stress cannot be released in time, and mental diseases can be caused. For example, the excessive pressure can lead to sub-health of the body, and direct morbidity can be caused in severe cases, wherein the most common diseases are many, such as the pressure can lead to infertility, so that many people are insomnia for a long time, many young people suffer from stomach diseases and the like, and the pressure is the biggest healthy killer.
Therefore, mental stress analyzers or other similar products appear in the market, and biological feedback sensors are used as media to detect HRV, pulse, EEG and other physiological indexes of the testee, and intelligently analyze and evaluate the physical and mental states of the testee, so that mental stress of a user is quantitatively evaluated, and mental conditions of the user are detected in real time.
However, the mental stress is an index with obvious floating change, and even if the mental stress is evaluated and quantified by corresponding equipment, the change rule of the mental stress is difficult to find, so that in the prior art, most mental stress monitoring management only detects and intervenes on the current mental stress state, and corresponding feedback cannot be made on the mental stress change in a period of time.
Disclosure of Invention
The invention aims to provide a management system for monitoring and intervening mental stress, which solves the technical problems that:
the aim of the invention can be achieved by the following technical scheme:
a mental stress monitoring and intervention management system, comprising:
mental stress analyzer: monitoring various physiological indexes of a user, quantitatively evaluating the mental stress of the user, and generating a stress value;
and a data recording module: extracting a pressure value from the mental pressure analyzer according to a preset extraction period, and sending the extracted pressure value to a data preprocessing module for backup after a detection period T;
and a data preprocessing module: acquiring all pressure values in the current detection period T and generating a reference set P= (P) t ，P 2t ，...，P T ) Wherein t is the extraction period, P t For the pressure value extracted after the time t of the beginning of the detection period, a difference set Δp= (Δp) is generated 1 ，ΔP 2 ，...，ΔP T/t-1 ) Wherein ΔP T/t-1 Representing P T/t And P T/t-1 A difference between them;
and a screening module: acquiring the difference set delta P, and screening out a change threshold delta P with an absolute value larger than or equal to a preset value max The elements are arranged in time sequence to generate a detection sequence delta P t ＝ΔP t1 ，ΔP t2 ，ΔP t3 ，...ΔP tn ；
And an analysis module: calculating a change interval between adjacent items of the detection sequence, and generating a change interval set Δt= (Δt) 1 ，Δt 2 ，...，Δt i ，...，Δt n-1 ) Wherein Δt is n-1 ＝t n -t n-1 I is a positive integer and i e (1, n-1);
when Deltat i When =t:
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＞P (ti+1)t ＞P (ti)t Then determine P (ti+2)t 、P (ti+1)t 、P (ti)t Is a monotonically increasing node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＜P (ti+1)t ＜P (ti) t, then determine P (ti+2)t 、P (ti+1)t 、P (ti)t Is a monotonically decreasing node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＜P (ti+1)t ，P (ti+1)t ＞P (ti)t When it is, then determine P (ti+1)t Is a peak node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＞P (ti+1)t ，P (ti+1)t ＜P (ti)t When it is, then determine P (ti+1)t Is a peak node;
and an intervention module: and judging the mental state of the user according to the number of the monotonically increasing nodes, the monotonically decreasing nodes and the peak value nodes in the current detection period, and sending an adjustment request when the next detection period starts.
As a further scheme of the invention: in the process of judging the nodes, the judging priority of the peak value node is larger than that of the monotonically decreasing node and the monotonically increasing node; when a node is determined to be both a monotonic node and a peak node, the system adjusts the determination of the node to be only the peak node, wherein the monotonic node comprises a monotonic decreasing node and a monotonic increasing node.
As a further scheme of the invention: in the analysis module, when deltat i And when the current node is more than t, judging that the user enters the emotion restoration period, and not judging the current node.
As a further scheme of the invention: in the intervention module, a specific judgment method for the mental state of the user is as follows:
acquiring the monotonically increasing node, the monotonically decreasing node and the peak value node;
dividing the monotonically increasing nodes and the monotonically decreasing nodes into a plurality of test groups by taking peak nodes as boundaries;
the reference scores for each test group were calculated:
wherein Kn represents the reference coefficient of the nth group, P first To test the first term pressure value in the group when time ordered, P last For the last pressure value in the test set in time-ordered, N represents the number of test sets, S represents the number of nodes within the test set, P p For the average pressure value of the test group, m is a preset work and rest correction coefficient, deltalambda is the range of the test group, and L is the number of more than 1 element in the change interval set Deltat;
calculating the total score of the detection period
And judging the mental state of the user according to the deviation degree of the total score K and the set normal threshold value interval.
As a further scheme of the invention: the normal threshold interval of the user mental stress is (P average +ΔP max ，P average -ΔP max ) Wherein P is average Is a preset normal pressure value, delta P max Is a preset change threshold.
As a further scheme of the invention: in the data recording module, when the pressure value is acquired, the pressure value exceeds the set pressure limit section (P limit+ ，P limit- ) When the user is in a state of being frightened, the current state of the user is judged, and an adjustment request is sent to the mental stress analyzer through the intervention module to adjust the mental state of the user, wherein P is as follows limit+ To limit mental stress, P limit Negative stress limit.
As a further scheme of the invention: the detection period T is an integer multiple of the extraction period T, a clock unit is arranged in the data recording module, and after the pressure value of one detection period T is extracted and packaged and sent to the data preprocessing module, the clock unit returns to zero and the timing of the next detection period is restarted.
The invention has the beneficial effects that: the invention is based on the mental pressure management scheme extended by the mental pressure analyzer in the prior art, the mental pressure analyzer uses a biofeedback sensor as a medium to detect the physical indexes of the testee such as HRV, pulse, EEG and the like, intelligently analyzes and evaluates the physical and psychological states of the testee, and is simultaneously used for monitoring the change of the central body state in the training intervention process in real time; adopting HRV+SCL+EEG to evaluate the psychological state, the autonomic nervous system state and the peripheral vascular state of a subject, adopting HRV+EEG to perform biofeedback training, improving the autonomic nerve coordination state, improving the physical and psychological autonomic balance ability, the personal psychological quality and the autonomic adaptation pressure ability, improving the emotion regulation ability in brain function, promoting the relaxation of the brain, promoting the generation of positive emotion and improving concentration; namely, the device mainly comprises two functions, namely, on one hand, quantitative evaluation of mental stress (corresponding to a stress value in the invention) and on the other hand, adjustment of the mental stress of a user through biofeedback (corresponding to adjustment of the user after the mental stress analyzer receives an adjustment request in the invention); and dividing each group of data by taking a peak node as a limit, wherein each independent test group is the quantitative representation of abnormal change of mental pressure in the time period, and comprises two types of pressure value increment and pressure value decrement, and the pressure value increment and the pressure value decrement exceed a safe threshold interval, so that the monitoring is needed, and the mental state of a user is comprehensively analyzed by combining the change times, thereby reflecting the mental change index of the user in a detection period and further playing the effect of monitoring the period change rule of the user.
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The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a mental stress monitoring and intervention management system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention is a mental stress monitoring and intervention management system, comprising:
mental stress analyzer: monitoring various physiological indexes of a user, quantitatively evaluating the mental stress of the user, and generating a stress value;
and a data recording module: extracting a pressure value from the mental pressure analyzer according to a preset extraction period, and sending the extracted pressure value to a data preprocessing module for backup after a detection period T;
and a data preprocessing module: acquiring all pressure values in the current detection period T and generating a reference set P= (P) t ，P 2t ，...，P T ) Wherein t is the extraction period, P t For the pressure value extracted after the time t of the beginning of the detection period, a difference set Δp= (Δp) is generated 1 ，ΔP 2 ，...，ΔP T/t-1 ) Wherein ΔP T/t-1 Representing P T/t And P T/t-1 A difference between them;
and a screening module: acquiring the difference set delta P, and screening out a change threshold delta P with an absolute value larger than or equal to a preset value max The elements are arranged in time sequence to generate a detection sequence delta P t ＝ΔP t1 ，ΔP t2 ，ΔP t3 ，...ΔP tn ；
And an analysis module: calculating a change interval between adjacent items of the detection sequence, and generating a change interval set Δt= (Δt) 1 ，Δt 2 ，...，Δt i ，...，Δt n-1 ) Wherein Δt is n-1 ＝t n -t n-1 I is a positive integer and i e (1, n-1);
when Deltat i When =t:
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＞P (ti+1)t ＞P (ti)t Then determine P (ti+2)t 、P (ti+1)t 、P (ti)t Is a monotonically increasing node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＜P (ti+1)t ＜P (ti)t Then determine P (ti+2)t 、P (ti+1)t 、P (ti)t Is a monotonically decreasing node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P% ti+2 ) t ＜P( ti+1 ) t ，P( ti+1 ) t ＞P (ti)t When it is, then determine P (ti+1)t Is a peak node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P (ti+2)t ＞P (ti+1)t ，P (ti+1)t ＜P (ti)t When it is, then determine P (ti+1)t Is a peak node;
and an intervention module: and judging the mental state of the user according to the number of the monotonically increasing nodes, the monotonically decreasing nodes and the peak value nodes in the current detection period, and sending an adjustment request when the next detection period starts.
It is noted that the present invention is based on a mental stress management scheme extended from a mental stress analyzer in the prior art, in which the mental stress analyzer uses a biofeedback sensor as a medium to detect physiological indexes such as HRV, pulse, EEG, etc. of a subject, and intelligently analyze and evaluate the physical and psychological states of the subject, and is simultaneously used for monitoring the central body state change in the training intervention process in real time; adopting HRV+SCL+EEG to evaluate the psychological state, the autonomic nervous system state and the peripheral vascular state of a subject, adopting HRV+EEG to perform biofeedback training, improving the autonomic nerve coordination state, improving the physical and psychological autonomic balance ability, the personal psychological quality and the autonomic adaptation pressure ability, improving the emotion regulation ability in brain function, promoting the relaxation of the brain, promoting the generation of positive emotion and improving concentration; namely, the device mainly comprises two functions, namely, quantitative evaluation of mental stress (corresponding to a stress value in the invention) and adjustment of mental stress of a user through biofeedback (corresponding to adjustment of the mental stress analyzer after receiving an adjustment request in the invention).
In another preferred embodiment of the present invention, in determining the nodes, the determination priority of the peak node is greater than but monotonically decreasing and monotonically increasing nodes; when a node is determined to be both a monotonic node and a peak node, the system adjusts the determination of the node to be only the peak node, wherein the monotonic node comprises a monotonic decreasing node and a monotonic increasing node.
In the present embodiment, in the analysis module, when Δt i And when the current node is more than t, judging that the user enters the emotion restoration period, and not judging the current node.
In another preferred embodiment of the present invention, in the intervention module, a specific method for determining the mental state of the user is as follows:
acquiring the monotonically increasing node, the monotonically decreasing node and the peak value node;
dividing the monotonically increasing nodes and the monotonically decreasing nodes into a plurality of test groups by taking peak nodes as boundaries;
the reference scores for each test group were calculated:
wherein Kn represents the reference coefficient of the nth group, P first To test the first term pressure value in the group when time ordered, P last For the last pressure value in the test set in time-ordered, N represents the number of test sets, S represents the number of nodes within the test set, P p For the average pressure value of the test group, m is a preset work and rest correction coefficient, deltalambda is the range of the test group, and L is the number of more than 1 element in the change interval set Deltat;
calculating the total score of the detection period
And judging the mental state of the user according to the deviation degree of the total score K and the set normal threshold value interval.
As the invention is inThe scheme of one step: the normal threshold interval of the user mental stress is (P average +ΔP max ，P average -ΔP max ) Wherein P is average Is a preset normal pressure value, delta P max Is a preset change threshold.
It can be understood that in the invention, each group of data is divided by taking the peak node as a limit, each independent test group is the quantitative representation of abnormal change of mental pressure in the time period, wherein the quantitative representation comprises two types of pressure value increment and pressure value decrement, the pressure value increment and the pressure value decrement exceed a safe threshold interval, monitoring is needed, and the mental state of a user is comprehensively analyzed by combining the change times, so that the mental change index of the user in a detection period can be reflected, and the effect of monitoring the period change rule of the user is further achieved.
In another preferred embodiment of the present invention, in the data recording module, when the received pressure value exceeds the set pressure limit interval (P limit+ ，P limit (-) determining the current state of the user as a frightened state and sending an adjustment request to the mental stress analyzer through the intervention module to adjust the mental state of the user, wherein P limit+ To limit mental stress, P limit Negative stress limit.
In another preferred embodiment of the present invention, the detection period T is an integer multiple of the extraction period T, and a clock unit is disposed in the data recording module, and after the pressure value of one detection period T is extracted and packaged and sent to the data preprocessing module, the clock unit is reset to zero, and the timing of the next detection period is restarted.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (6)
1. A mental stress monitoring and intervention management system, comprising:
mental stress analyzer: monitoring various physiological indexes of a user, quantitatively evaluating the mental stress of the user, and generating a stress value;
and a data recording module: extracting a pressure value from the mental pressure analyzer according to a preset extraction period, and sending the extracted pressure value to a data preprocessing module for backup after a detection period T;
and a data preprocessing module: acquiring all pressure values in the current detection period T and generating a reference set P= (P) t ，P 2t ，...，P T ) Wherein t is the extraction period, P t For the pressure value extracted after the time T from the beginning of the detection period, the detection period T is an integer multiple of the extraction period T, and a difference set DeltaP= (DeltaP) is generated 1 ，ΔP 2 ，...，ΔP T/t-1 ) Wherein ΔP T/t-1 Representing P T/t And P T/t-1 A difference between them;
and a screening module: acquiring the difference set delta P, and screening out a change threshold delta P with an absolute value larger than or equal to a preset value max The elements are arranged in time sequence to generate a detection sequence delta P t =ΔP t1 ，ΔP t2 ，ΔP t3 ，...ΔP tn ；
And an analysis module: calculating a time change interval between adjacent items of the detection sequence, and generating a change interval set Δt= (Δt) 1 ，Δt 2 ，...，Δt i ，...，Δt n-1 ) Wherein Δt is n-1 =t n -t n-1 I is a positive integer and i e (1, n-1);
when Deltat i When =t:
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P （ti+2）t ＞P （ti+1）t ＞P （ti）t Then determine P （ti+2）t 、P （ti+1）t 、P （ti）t Is a monotonically increasing node;
when DeltaP ti+1 And DeltaP ti Symbol phaseAnd P is as follows （ti+2）t ＜P （ti+1）t ＜P （ti）t Then determine P （ti+2）t 、P （ti+1）t 、P （ti）t Is a monotonically decreasing node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P （ti+2）t ＜P （ti+1）t ，P （ti+1）t ＞P （ti）t When it is, then determine P （ti+1）t Is a peak node;
when DeltaP ti+1 And DeltaP ti The symbols are the same, and P （ti+2）t ＞P （ti+1）t ，P （ti+1）t ＜P （ti）t When it is, then determine P （ti+1）t Is a peak node;
and an intervention module: and judging the mental state of the user according to the number of the monotonically increasing nodes, the monotonically decreasing nodes and the peak value nodes in the current detection period, and sending an adjustment request when the next detection period starts.
2. A mental stress monitoring and intervention management system as in claim 1, wherein in determining nodes, the peak nodes have a higher priority of determination than the monotonically decreasing nodes and the monotonically increasing nodes; when a node is determined to be both a monotonic node and a peak node, the system adjusts the determination of the node to be only the peak node, wherein the monotonic node comprises a monotonic decreasing node and a monotonic increasing node.
3. The mental stress monitoring and intervention management system of claim 2, wherein said analysis module, when Δt i And when the current node is more than t, judging that the user enters the emotion restoration period, and not judging the current node.
4. A mental stress monitoring and intervention management system according to claim 3, wherein the normal threshold interval of mental stress of the user is (P average +ΔP max ，P average -ΔP max ) Wherein P is average Is a preset normal pressure value, delta P max Is a preset change threshold.
5. The mental stress monitoring and intervention management system according to claim 1, wherein, in said data recording module, when said pressure value is obtained, when the pressure value exceeds a set pressure limit interval (P limit+ ，P limit- ) When the user is in a state of being frightened, the current state of the user is judged, and an adjustment request is sent to the mental stress analyzer through the intervention module to adjust the mental state of the user, wherein P is as follows limit+ To limit mental stress, P limit- Is a negative limit of mental stress.
6. The mental stress monitoring and intervention management system according to claim 1, wherein a clock unit is arranged in the data recording module, and after the pressure value of one detection period T is extracted and packaged and sent to the data preprocessing module, the clock unit is reset to zero, and the timing of the next detection period is restarted.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10137228A (en) * | 1996-11-07 | 1998-05-26 | Nissan Motor Co Ltd | Mental stress judging device |
| JP2010234000A (en) * | 2009-03-31 | 2010-10-21 | Yamaguchi Prefectural Industrial Technology Institute | Mental stress evaluation, device using the same, mental stress evaluation method, and program for the same |
| CN106419937A (en) * | 2016-09-12 | 2017-02-22 | 南京邮电大学 | Mental stress analysis system based on heart sound HRV theory |
| CN107913075A (en) * | 2017-11-15 | 2018-04-17 | 重庆邮电大学 | A kind of stress apparatus for evaluating and its appraisal procedure based on multi-parameter |
| CN111920429A (en) * | 2020-09-11 | 2020-11-13 | 深圳市爱都科技有限公司 | Mental stress detection method and device and electronic equipment |
| WO2021097731A1 (en) * | 2019-11-20 | 2021-05-27 | 林千寻 | Human mental stress test method and system |
| CN114668397A (en) * | 2022-03-14 | 2022-06-28 | 中国人民解放军总医院第八医学中心 | Psychological pressure monitoring method based on fusion attention mechanism |
| CN115251925A (en) * | 2022-08-01 | 2022-11-01 | 陕西思尔生物科技有限公司 | Psychological assessment analysis method and device based on multiple indexes and computer readable medium thereof |
-
2023
- 2023-05-29 CN CN202310617147.4A patent/CN116636846B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10137228A (en) * | 1996-11-07 | 1998-05-26 | Nissan Motor Co Ltd | Mental stress judging device |
| JP2010234000A (en) * | 2009-03-31 | 2010-10-21 | Yamaguchi Prefectural Industrial Technology Institute | Mental stress evaluation, device using the same, mental stress evaluation method, and program for the same |
| CN106419937A (en) * | 2016-09-12 | 2017-02-22 | 南京邮电大学 | Mental stress analysis system based on heart sound HRV theory |
| CN107913075A (en) * | 2017-11-15 | 2018-04-17 | 重庆邮电大学 | A kind of stress apparatus for evaluating and its appraisal procedure based on multi-parameter |
| WO2021097731A1 (en) * | 2019-11-20 | 2021-05-27 | 林千寻 | Human mental stress test method and system |
| CN113194829A (en) * | 2019-11-20 | 2021-07-30 | 林千寻 | Human body mental stress testing method and system |
| CN111920429A (en) * | 2020-09-11 | 2020-11-13 | 深圳市爱都科技有限公司 | Mental stress detection method and device and electronic equipment |
| CN114668397A (en) * | 2022-03-14 | 2022-06-28 | 中国人民解放军总医院第八医学中心 | Psychological pressure monitoring method based on fusion attention mechanism |
| CN115251925A (en) * | 2022-08-01 | 2022-11-01 | 陕西思尔生物科技有限公司 | Psychological assessment analysis method and device based on multiple indexes and computer readable medium thereof |
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