CN113907757B - Alertness testing method based on attention system theory - Google Patents

Alertness testing method based on attention system theory Download PDF

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CN113907757B
CN113907757B CN202111209243.2A CN202111209243A CN113907757B CN 113907757 B CN113907757 B CN 113907757B CN 202111209243 A CN202111209243 A CN 202111209243A CN 113907757 B CN113907757 B CN 113907757B
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李敬强
胡超
张希凝
周妍汝
王庆福
张璐
张焕晰
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Civil Aviation University of China
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Abstract

An alertness testing method based on attention system theory. The method comprises the steps of collecting the alertness level of a testee; obtaining continuous alertness, staged alertness and selective attention indexes and judging the corresponding degree of the testee; obtaining average reaction time data; calculating the standard deviation of the reaction time; calculating the coefficient of variation and the accuracy; determining the alertness level of the testee; comprehensively reflecting the overall alertness state of the testee and the like. The invention innovatively applies the attention system theory to the alertness test, can carry out the alertness test from the continuous alertness, the staged alertness and the selective attention to the dimensions, and more intuitively and comprehensively reflects the alertness level of a testee. The alertness grade of the testee is determined by two specific indexes of the variation coefficient and the accuracy of the testee in reaction, and the result is more scientific and accurate. The subjective test and the objective test of the alertness are organically combined together by combining the Carolina car somnolence scale, so that the alertness test is more comprehensive.

Description

Alertness testing method based on attention system theory
Technical Field
The invention belongs to the technical field of psychological characteristic testing, and particularly relates to an alertness testing method based on an attention system theory.
Background
Note that the direction and concentration of a certain object by mental activities are a common psychological characteristic accompanying psychological processes such as sensory perception, memory, thinking, imagination, and the like. Note that not just a single concept, but rather is related to a variety of psychological phenomena and cognitive activities. The attention system consists of an alert network, a directional network and an execution control network, wherein the alert network has the function of achieving and maintaining the alert state of a brain; the function of the directional network is to select information from sensory inputs; the function of the execution control network is to resolve conflicts.
The attention system theory proposed by the psychologist Persian divides attention into four components: persistent alertness, episodic alertness, selective attention, and persistent attention. Persistent alertness is the ability of a person to respond to any event in the environment and reflects the level of arousal or overall activation of an organism at any time. Staged alertness is the ability to react to an event after an alarm signal, and it is crucial to prepare and react to changes in the environment. Selective attention is the ability to produce a specific response to one stimulus and a different response to another stimulus, enabling irrelevant information to be filtered out of the environment. Persistent attention is the ability to effectively continue to react over a period of time (minutes to hours).
The alertness is used as an objective index, is applied to a plurality of fields such as safety, medical treatment and the like, and has great significance on monitoring the alertness of people such as drivers, controllers and the like in real time and sending out alarms in time. At present, most of the studies on alertness at home and abroad are combined with a physiological signal testing method and some subjective testing methods to test alertness.
1. Subjective testing method
The subjective test method is to judge the alertness by stages through the visual observation of people. The subjective test scales widely used include: carrolin squash scale, stanford squash test scale, Sman-Perelli7 grade fatigue scale, self-induced fatigue grading scale, visual simulation scale and the like.
2. Physiological signal testing method
1)fMRI
Functional magnetic resonance imaging (fMRI) is used by researchers to predict susceptibility to fatigue and to perform alertness tests. Spatial Working Memory Task (SWMT) test performance is negatively correlated with global brain activation level, left posterior parietal cortex activation level, and left dorsolateral prefrontal cortex activation level. It is concluded that individuals with low brain activation levels are prone to fatigue during fMRI testing, providing a new approach to predicting fatigue and alertness testing.
2) Electroencephalogram signal
With the progress of the electroencephalogram signal processing technology and the deep research on the electroencephalogram signals, people gradually find that the electroencephalogram signals have wide prospects in the aspect of alertness testing. Hundreds of millions of neurons in the brain activate and thus cause changes in the surface potential of the scalp, which we call as brain electricity, and there is abundant brain state information. The brain electricity directly reflects the activity of brain, and is an important index for measuring alertness.
3) Spatial threshold of skin
The existing human subject holds a tactile meter or two foot gauges, pulls the tactile meter or two foot gauges apart by a certain distance, touches the skin of the forearm of the human subject with the same force at the two ends, and gradually increases the distance between the two foot gauges from the distance that the human subject can not feel the two points until the human subject feels that the minimum distance between the two points is a skin space valve, which is also called a touch two-point distinguishing threshold. When the threshold value is quieter, the increase by 1.5-2 times is mild fatigue, and the increase by more than 2 times is severe fatigue.
4) Ocular electrical signals
Electrooculogram (EOG) is a measurement of the electrostatic potential of the retina that exists between the retinal pigment epithelium and the photoreceptor cells. According to the temporary distribution condition of the EOG oscillogram belonging to a certain category, the degree of the EOG belonging to the certain category is listed into a histogram, so that the blink type and the change condition at a certain moment can be clearly obtained, and the alertness level and whether fatigue is generated at the moment can be judged, and the method is also an important index of the alertness test.
5) Physical reaction signal
The physical reaction signals of the human body comprise: the eye closure degree, the eye closure time, the nodding frequency, the head position, the mouth state, the mental state, the gazing concentration degree and other face characteristics can be recorded by a video camera in the experimental process.
In summary, the present testing of alertness at home and abroad mainly focuses on the testing of alertness by combining a physiological signal testing method and some subjective testing methods. The alertness level obtained by analyzing the characteristics of the tested physiological signals is the most widely applied means of alertness tests at present, and although the alertness tests performed by depending on the physiological signals have more accurate test results and certain credibility, the alertness tests have more rigorous test conditions, have higher requirements on the test environment, complicated test instruments and test processes and more limited applicable environments, so the alertness level is not suitable for daily application and popularization.
Disclosure of Invention
In order to solve the above problems, the present invention provides an alertness testing method based on attention system theory.
In order to achieve the above purpose, the alertness testing method based on the attention system theory provided by the invention comprises the following steps which are carried out in sequence:
1) acquiring the alertness grade selected by a testee according to the real condition of the testee by referring to a Carolina sleepiness scale;
2) displaying three visual stimulation pictures on a screen, and then enabling a subject to observe whether two pictures are consistent or not and quickly react to obtain single reaction time data RT of the subject reacting to the J event Ji Single reaction time data RT for reflecting the persistent alertness index of the subject and reacting to the S event Si RT as single reaction time data reflecting the staged alertness index of the subject and reacting to F events Fi As a selective attention index reflecting the subject;
3) obtaining a continuous alertness probability based on the continuous alertness index, and judging the continuous alertness degree of the testee according to the continuous alertness probability;
4) acquiring a stage alertness probability based on the stage alertness index, and judging the stage alertness degree of the testee according to the stage alertness probability;
5) obtaining a selective attention probability based on the selective attention index, and judging the selective attention degree of the testee according to the selective attention probability;
6) single reaction time data RT for reacting a subject to a J event Ji Single reaction time data RT for reaction to S event Si And single reaction time data RT for reacting to F events Fi Collectively referred to as single reaction time data RT i Then all single reaction data RT i Average reaction time data obtained by averaging
Figure BDA0003308225760000042
7) According to all single reaction data RT i And average reaction time data
Figure BDA0003308225760000041
Calculating a standard deviation sigma of the reaction time;
8) according to standard deviation sigma of reaction time and average reaction time data
Figure BDA0003308225760000043
Calculating a variation coefficient X;
9) counting the times of the testee making correct response to the visual stimulation picture and the total times of the testee making all responses, and then calculating the correct rate Y;
10) determining the alertness grade of the testee according to the variation coefficient X and the accuracy Y;
11) determining the self-evaluation alertness state of the testee according to the alertness level acquired in the step 1); determining the continuous alertness state, the stage alertness state and the selective attention state of the human subject according to the continuous alertness degree, the stage alertness degree and the selective attention degree of the human subject obtained in the step 3), the step 4) and the step 5); determining the evaluation alertness grade of the testee according to the obtained alertness grade of the testee in the step 10), thereby comprehensively reflecting the overall state of the alertness of the testee.
In step 1), the carolina squash scale divides alertness into 9 levels: 1 ═ extreme alertness; 2 ═ very alert; 3 ═ alert; 4 ═ comparative alertness; 5 ═ neither alert nor sleepy; 6-there was some signs of fatigue; 7 is sleepy, but does not want to stay awake; 8, sleepy and wants to keep awake; 9 is very sleepy, trying to stay awake and struggle against fatigue.
In step 2), three visual stimulation pictures are displayed on the screen, and then the testee is allowed to observe whether two pictures are consistent and quickly react to obtain single reaction time data RT of the testee reacting to the J event Ji Single reaction time data RT for reflecting the persistent alertness index of the subject and reacting to the S event Si RT as single reaction time data reflecting the staged alertness index of the subject and reacting to F events Fi The method for reflecting the selective attention index of the subject is as follows:
displaying three visual stimulus pictures A1, B1 and B2 in 2-6s on a screen, wherein three visual stimulus pictures are randomly drawn from eight visual stimulus pictures with symbols; firstly, allowing a subject to observe whether symbols in a visual stimulation picture A1 and a visual stimulation picture B1 are consistent or not and quickly making a response, if the symbols in the visual stimulation picture A1 and the visual stimulation picture B1 are inconsistent, recording the response as a J event, and otherwise, recording the response as an F event; then observing whether the symbols in the visual stimulation picture A1 and the visual stimulation picture B2 are consistent, if the responses are inconsistent, recording the symbols as a J event, otherwise recording the symbols as an S event, and thus completing one test; recording the single reaction time data of the subject reacting to the J event as RT Ji As a continuous alert reflecting the subjectIndexes; recording the single reaction time data of the subject reacting to the S event as RT Si As a staged alertness index reflecting the subject; recording the single reaction time data of the subject reacting to the F event as RT Fi As a selective attention index reflecting the subject; the total test time is 10 minutes, and the test is repeated for a plurality of times; the single reaction time data refers to the time from the appearance of the visual stimulus to the reaction of the visual stimulus of the testee in the process of one stimulus, and the unit is ms.
In step 3), the method for obtaining the persistent alert probability based on the persistent alert indicator and judging the persistent alert degree of the subject according to the persistent alert probability includes:
single reaction time data RT for reacting all subjects to J events Ji Taking an average value to obtain average reaction time data of the human subject reacting to the J event
Figure BDA0003308225760000061
The formula is as follows:
Figure BDA0003308225760000062
wherein n is the number of data in all single reactions of the subject to react to the J event;
and then according to the single reaction time data RT of the tested person reacting to the J event Ji And average reaction time data of the subject reacting to the J event
Figure BDA0003308225760000063
Calculating the standard deviation sigma of the reaction time of the human subject reacting to the J event J The formula is as follows:
Figure BDA0003308225760000064
and then according to the average reaction time data of the tested person reacting to the J event
Figure BDA0003308225760000065
Standard deviation sigma of reaction time of the subject to react to J event J Calculating critical reaction time data RT of the human subject reacting to the J event J0 The formula is as follows:
Figure BDA0003308225760000066
single reaction time data RT for finally making the subject react to J event Ji Data RT greater than the critical reaction time of the subject to react to the J event J0 As the persistent alert probability P J And using the persistent alert probability P J Judging the continuous alertness degree of the testee, if the continuous alertness probability P is J < 0.059, indicating that the degree of persistent alertness of the subject is "good", otherwise "poor".
In step 4), the method for obtaining the staged alertness probability based on the staged alertness index and judging the staged alertness degree of the subject according to the staged alertness probability includes:
single reaction time data RT for reacting a subject to an S event Si Taking an average value to obtain average reaction time data of the subject reacting to the S event
Figure BDA0003308225760000071
The formula is as follows:
Figure BDA0003308225760000072
wherein n is the number of data in all single reactions of the subject to react to the S event;
then according to the single reaction time data RT of the subject reacting to the S event Si Average reaction time data of the subject reacting to the S event
Figure BDA0003308225760000073
Calculating the standard deviation sigma of the reaction time of the subject reacting to the S event S The formula is as follows:
Figure BDA0003308225760000074
then according to the average reaction time data of the tested person reacting to the S event
Figure BDA0003308225760000075
Standard deviation sigma of reaction time of the subject to react to the S event S Calculating critical reaction time data RT of the subject reacting to the S event S0 The formula is as follows:
Figure BDA0003308225760000076
finally, the single reaction time data of the subject reacting to the S event is larger than the critical reaction time data RT of the subject reacting to the S event S0 As a periodic alert probability P S And using the staged alertness probability P S And judging the stage alertness of the testee, wherein if the stage alertness probability Ps is less than 0.04, the stage alertness of the testee is 'good', otherwise, the stage alertness of the testee is 'poor'.
In step 5), the method for obtaining the selective attention probability based on the selective attention index and judging the selective attention degree of the subject according to the selective attention probability is as follows:
single reaction time data RT for reacting a subject to an F event Fi Taking an average value to obtain average reaction time data of the testee reacting to the F event
Figure BDA0003308225760000077
The formula is as follows:
Figure BDA0003308225760000078
wherein n is the number of data in all single reactions of the subject to react to the F event;
then according to the single reaction time data RT of the subject reacting to the F event Fi Average reaction time data of the subject reacting to the F event
Figure BDA0003308225760000081
Calculating the standard deviation sigma of the reaction time of the subject reacting to the F event F The formula is as follows:
Figure BDA0003308225760000082
and then according to the average reaction time data of the testee reacting to the F event
Figure BDA0003308225760000083
Standard deviation σ of reaction time with subject reacting to F event F Calculating critical reaction time data RT of the subject reacting to the F event F0 The formula is as follows:
Figure BDA0003308225760000084
finally, the single reaction time data of the subject reacting to the F event is larger than the critical reaction time data RT of the subject reacting to the F event F0 As selective attention probability P F And using the selective attention probability P F Judging the selective attention degree of the testee, if the selective attention probability P is F < 0.069, indicating that the subject's selective attention is "good", otherwise "poor".
In step 6), the average reaction time data
Figure BDA0003308225760000085
The formula of (1) is as follows:
Figure BDA0003308225760000086
wherein: n is the number of data of all single reaction times of the testee;
in step 7), the reaction standard deviation σ is formulated as follows:
Figure BDA0003308225760000087
in step 8), the formula of the coefficient of variation X is as follows:
Figure BDA0003308225760000088
in step 9), the formula of the accuracy rate Y is as follows:
the accuracy Y is (number of correct reactions/total number of total reactions) × 100%.
In step 10), the method for determining the alertness level of the subject is as follows:
the alertness level A is obtained when X is more than 0.84 and Y is more than or equal to 95 percent;
the alertness grade A is when X is more than 0.84 and Y is more than 85 percent and less than 95 percent;
the alertness grade A is when X is more than 0.84 and Y is less than 85%;
when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 95 percent, the level is alert B;
the alertness grade A is obtained when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade A when X is more than 0.67 and less than or equal to 0.84 and Y is less than 85 percent;
when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 95 percent, the alertness is grade C;
the alertness grade B is determined when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade A when X is more than 0.58 and less than or equal to 0.67 and Y is less than 85 percent;
when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 95 percent, the degree of alertness is grade D;
the alertness grade C is obtained when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade B when X is more than 0.51 and less than or equal to 0.58 and Y is less than 85 percent;
the alertness level E is obtained when X is less than or equal to 0.51 and Y is more than or equal to 95 percent;
the alertness grade D is when X is less than or equal to 0.51 and Y is more than or equal to 85% and less than 95%;
the alertness grade B is obtained when X is less than or equal to 0.51 and Y is less than 85 percent;
wherein, the alertness grade A represents that the subject is very tired; alertness level B represents subject fatigue; the alertness degree C indicates that the subject is neither tired nor alert; the level D of alertness represents the alertness of the testee; the alertness level E indicates that the subject is very alert.
The alertness testing method based on the attention system theory provided by the invention has the following beneficial effects: the invention innovatively applies the attention system theory to the alertness test, can test the alertness from the dimensions of continuous alertness, stage alertness and selective attention, and more intuitively and comprehensively reflects the alertness level of a testee. The invention adopts two specific indexes of the variation coefficient and the accuracy of the reaction time of the testee to determine the alertness level of the testee, and the result is more scientific and accurate. The invention combines the Carolins Scabiose scale, organically combines the subjective test and the objective test of the alertness together, and leads the alertness test to be more comprehensive. The invention can be integrated on the mobile terminal without the assistance of professional technicians, has simple test operation, higher reliability, small learning effect and small influence of individual difference, greatly reduces the test cost and eliminates the limitation of test conditions such as time, place and the like. Meanwhile, the invention has little influence on the physiology and the psychology of the testee during the test, and the test result can be quickly and intuitively displayed on the mobile terminal.
Drawings
Fig. 1 is a flowchart of an alertness testing method based on attention system theory according to the present invention.
FIG. 2 is a schematic diagram of three visual stimulus pictures displayed on a screen;
FIG. 3 is a schematic view of eight visual stimulus pictures with symbols;
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
As shown in fig. 1, the alertness testing method based on the attention system theory provided by the present invention includes the following steps performed in sequence:
1) acquiring the alertness grade selected by a testee according to the real condition of the testee by referring to a Carolina Selence scale (KSS scale) shown in a table 1;
the carolina squash scale divides alertness into 9 grades: 1 is extremely alert; 2 ═ very alert; 3 ═ alert; 4 ═ comparative alertness; 5 ═ neither alert nor sleepy; 6-there was some evidence of fatigue; 7 is sleepy, but does not want to stay awake; sleepy and want to stay awake; 9 is very sleepy, trying to stay awake and struggle against fatigue.
TABLE 1 Carolina hypersomnia Scale
Figure BDA0003308225760000111
2) Displaying three visual stimulation pictures on a screen, and then enabling a subject to observe whether two pictures are consistent or not and quickly react to obtain single reaction time data RT of the subject reacting to the J event Ji Single reaction time data RT for reflecting the persistent alertness index of the subject and reacting to the S event Si RT as single reaction time data reflecting the staged alertness index of the subject and reacting to F events Fi As a selective attention index reflecting the subject;
as shown in fig. 2, three visual stimulus pictures a1, B1, and B2, which are randomly drawn three pictures from the eight signed visual stimulus pictures shown in fig. 3, are displayed on the screen within 2-6 s; firstly, allowing a subject to observe whether symbols in a visual stimulation picture A1 and a visual stimulation picture B1 are consistent or not and quickly making a response, if the symbols in the visual stimulation picture A1 and the visual stimulation picture B1 are inconsistent, recording the response as a J event, and otherwise, recording the response as an F event; then observing whether the symbols in the visual stimulus picture A1 and the visual stimulus picture B2 are consistent or not, and recording the symbols as the symbols if the responses are inconsistentThe J event is recorded as the S event if not, and therefore, one test is completed; recording the single reaction time data of the subject reacting to the J event as RT Ji As a persistent alertness index reflecting the subject; recording the single reaction time data of the subject reacting to the S event as RT Si As a staged alertness index reflecting the subject; recording the single reaction time data of the subject reacting to the F event as RT Fi As a selective attention index reflecting the subject; the total test time is 10 minutes, and the test is repeated for a plurality of times; the single reaction time data refers to the time from the appearance of the visual stimulus to the reaction of the visual stimulus of the testee in the process of one stimulus, and the unit is ms.
3) Obtaining a continuous alertness probability based on the continuous alertness index, and judging the continuous alertness degree of the testee according to the continuous alertness probability;
single reaction time data RT for reacting all subjects to J events Ji Taking an average value to obtain average reaction time data of the human subject reacting to the J event
Figure BDA0003308225760000121
The formula is as follows:
Figure BDA0003308225760000122
wherein n is the number of data in all single reactions of the subject to react to the J event;
and then according to the single reaction time data RT of the tested person reacting to the J event Ji And average reaction time data of the subject reacting to the J event
Figure BDA0003308225760000123
Calculating the standard deviation sigma of the reaction time of the human subject reacting to the J event J The formula is as follows:
Figure BDA0003308225760000124
and then according to the average reaction time data of the tested person reacting to the J event
Figure BDA0003308225760000125
Standard deviation σ of reaction time with subject reacting to J event J Calculating critical reaction time data RT of the human subject reacting to the J event J0 The formula is as follows:
Figure BDA0003308225760000126
single reaction time data RT for finally making the subject react to J event Ji Data RT greater than the critical reaction time of the subject to react to the J event J0 As the persistent alert probability P J And using the persistent alert probability P J Judging the continuous alertness degree of the testee, if the continuous alertness probability P is J < 0.059, indicating that the degree of persistent alertness of the subject is "good", otherwise "poor".
4) Acquiring a stage alertness probability based on the stage alertness index, and judging the stage alertness degree of the testee according to the stage alertness probability;
single reaction time data RT for reacting a subject to an S event Si Taking an average value to obtain average reaction time data of the subject reacting to the S event
Figure BDA0003308225760000131
The formula is as follows:
Figure BDA0003308225760000132
wherein n is the number of data in all single reactions of the subject to react to the S event;
then according to the single reaction time data RT of the subject reacting to the S event Si And average reaction hours of the subject reacting to the S eventAccording to
Figure BDA0003308225760000133
Calculating the standard deviation sigma of the reaction time of the subject reacting to the S event S The formula is as follows:
Figure BDA0003308225760000134
then according to the average reaction time data of the tested person reacting to the S event
Figure BDA0003308225760000135
Standard deviation sigma of reaction time of the subject to react to the S event S Calculating critical reaction time data RT of the subject reacting to the S event S0 The formula is as follows:
Figure BDA0003308225760000136
finally, the single reaction time data of the human subject reacting to the S event is larger than the critical reaction time data RT of the human subject reacting to the S event S0 As the staged alertness probability P S And using the staged alertness probability P S And judging the stage alertness of the testee, wherein if the stage alertness probability Ps is less than 0.04, the stage alertness of the testee is 'good', otherwise, the stage alertness of the testee is 'poor'.
5) Obtaining a selective attention probability based on the selective attention index, and judging the selective attention degree of the testee according to the selective attention probability;
single reaction time data RT for reacting a subject to an F event Fi Taking an average value to obtain average reaction time data of the testee reacting to the F event
Figure BDA0003308225760000141
The formula is as follows:
Figure BDA0003308225760000142
wherein n is the number of data in all single reactions of the subject to react to the F event;
then according to the single reaction time data RT of the subject reacting to the F event Fi Average reaction time data of the subject reacting to the F event
Figure BDA0003308225760000143
Calculating the standard deviation sigma of the reaction time of the subject reacting to the F event F The formula is as follows:
Figure BDA0003308225760000144
and then according to the average reaction time data of the testee reacting to the F event
Figure BDA0003308225760000145
Standard deviation sigma of reaction time of subject to react to F event F Calculating critical reaction time data RT of the subject reacting to the F event F0 The formula is as follows:
Figure BDA0003308225760000146
finally, the single reaction time data of the subject reacting to the F event is larger than the critical reaction time data RT of the subject reacting to the F event F0 As selective attention probability P F And using the selective attention probability P F Judging the selective attention degree of the testee, if the selective attention probability P is F < 0.069, indicating that the subject's selective attention is "good", otherwise "poor".
6) Single reaction time data RT for reacting a subject to a J event Ji Single reaction time data RT for reaction to S event Si And a single reaction to F eventTime-dependent data RT Fi Collectively referred to as single reaction time data RT i Then all single reaction data RT i Average reaction time data obtained by averaging
Figure BDA0003308225760000147
The formula is as follows:
Figure BDA0003308225760000148
wherein: n is the number of data of all single reactions of the testee;
7) according to all single reaction data RT i And average reaction time data
Figure BDA0003308225760000151
Calculating the standard deviation sigma of the reaction time, wherein the formula is as follows:
Figure BDA0003308225760000152
8) according to standard deviation sigma of reaction time and average reaction time data
Figure BDA0003308225760000154
Calculating the variation coefficient X, wherein the formula is as follows:
Figure BDA0003308225760000153
9) counting the times of the testee making correct response to the visual stimulation picture and the total times of the testee making all responses, and then calculating the correct rate Y, wherein the formula is as follows:
the accuracy Y is (number of correct reactions/total number of total reactions) × 100%
10) Determining the alertness grade of the subject according to the variation coefficient X and the accuracy Y, as shown in Table 2:
the alertness level A is obtained when X is more than 0.84 and Y is more than or equal to 95 percent;
when X is more than 0.84 and Y is more than or equal to 85 percent and less than 95 percent, the degree of alertness is grade A;
alertness grade A when X is greater than 0.84 and Y is less than 85%;
when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 95 percent, the level is alert B;
the alertness grade A is obtained when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade A when X is more than 0.67 and less than or equal to 0.84 and Y is less than 85 percent;
when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 95 percent, the alertness is grade C;
the alertness grade B is obtained when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade A when X is more than 0.58 and less than or equal to 0.67 and Y is less than 85 percent;
when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 95 percent, the degree of alertness is grade D;
the alertness grade C is obtained when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade B when X is more than 0.51 and less than or equal to 0.58 and Y is less than 85 percent;
the alertness level E is obtained when X is less than or equal to 0.51 and Y is more than or equal to 95 percent;
the alertness grade D is obtained when X is less than or equal to 0.51 and Y is less than or equal to 85% and less than 95%;
the alertness grade B is obtained when X is less than or equal to 0.51 and Y is less than 85 percent;
wherein, the alertness grade A represents that the subject is very tired; alertness grade B represents subject fatigue; the alertness degree C indicates that the subject is neither tired nor alert; the level D of alertness represents the alertness of the testee; alertness level E indicates that the subject is very alert.
TABLE 2 alertness rating
Figure BDA0003308225760000161
11) Determining the self-evaluation alertness state of the testee according to the alertness level acquired in the step 1); determining the continuous alertness state, the stage alertness state and the selective attention state of the human subject according to the continuous alertness degree, the stage alertness degree and the selective attention degree of the human subject obtained in the step 3), the step 4) and the step 5); determining the evaluation alertness grade of the testee according to the obtained alertness grade of the testee in the step 10), thereby comprehensively reflecting the overall state of the alertness of the testee.

Claims (7)

1. An alertness testing method based on attention system theory is characterized in that: the alertness testing method based on the attention system theory comprises the following steps which are carried out in sequence:
1) acquiring the alertness grade selected by a testee according to the real condition of the testee by referring to a Carolina sleepiness scale;
2) displaying three visual stimulation pictures on a screen, and then enabling a subject to observe whether two pictures are consistent or not and quickly react to obtain single reaction time data RT of the subject reacting to the J event Ji Single reaction time data RT for reflecting the persistent alertness index of the subject and reacting to the S event Si RT as single reaction time data reflecting the staged alertness index of the subject and reacting to F events Fi As a selective attention index reflecting the subject;
3) obtaining a continuous alertness probability based on the continuous alertness index, and judging the continuous alertness degree of the testee according to the continuous alertness probability;
4) acquiring a stage alertness probability based on the stage alertness index, and judging the stage alertness degree of the testee according to the stage alertness probability;
5) obtaining a selective attention probability based on the selective attention index, and judging the selective attention degree of the testee according to the selective attention probability;
6) single reaction time data RT for reacting a subject to a J event Ji Single reaction time data RT for reaction to S event Si And single reaction time data RT for reacting to F events Fi Collectively referred to as single reaction time data RT i Then all single reaction data RT i Average reaction time data obtained by averaging
Figure FDA0003805986890000011
7) According to all single reaction data RT i And average reaction time data
Figure FDA0003805986890000012
Calculating a standard deviation sigma of the reaction time;
8) according to standard deviation sigma of reaction time and average reaction time data
Figure FDA0003805986890000013
Calculating a variation coefficient X;
9) counting the times of the testee making correct response to the visual stimulation picture and the total times of the testee making all responses, and then calculating the correct rate Y;
10) determining the alertness grade of the testee according to the variation coefficient X and the accuracy Y;
11) determining the self-evaluation alertness state of the testee according to the alertness level acquired in the step 1); determining the continuous alertness state, the stage alertness state and the selective attention state of the human subject according to the continuous alertness degree, the stage alertness degree and the selective attention degree of the human subject obtained in the step 3), the step 4) and the step 5); determining the evaluation alertness grade of the testee according to the obtained alertness grade of the testee in the step 10), thereby comprehensively reflecting the overall state of the alertness of the testee;
in step 2), displaying three visual stimulation pictures on the screen, and then enabling the testee to observe whether two pictures are consistent and quickly react to obtain single reaction time data RT of the testee reacting to the J event Ji Single reaction time data RT for reflecting the persistent alertness index of the subject and reacting to the S event Si RT as single reaction time data reflecting the staged alertness index of the subject and reacting to F events Fi The method for reflecting the selective attention index of the subject is as follows:
three visual stimulus pictures A1, B1 and B2 are displayed in 2-6s on the screen, and the three visual stimulus pictures are marked by eight picturesRandomly extracting three visual stimulation pictures; firstly, allowing a subject to observe whether symbols in a visual stimulation picture A1 and a visual stimulation picture B1 are consistent or not and quickly making a response, if the symbols in the visual stimulation picture A1 and the visual stimulation picture B1 are inconsistent, recording the response as a J event, and otherwise, recording the response as an F event; then observing whether the symbols in the visual stimulation picture A1 and the visual stimulation picture B2 are consistent, if the responses are inconsistent, recording the symbols as a J event, otherwise recording the symbols as an S event, and thus completing one test; recording the single reaction time data of the subject reacting to the J event as RT Ji As a persistent alertness index reflecting the subject; recording the single reaction time data of the subject reacting to the S event as RT Si As a staged alertness index reflecting the subject; recording the single reaction time data of the subject reacting to the F event as RT Fi As a selective attention index reflecting the subject; the total test time is 10 minutes, and the test is repeated for a plurality of times; the single reaction time data refers to the time from the appearance of the visual stimulus to the reaction of the visual stimulus of the testee in the process of one stimulus, and the unit is ms.
2. The alertness test method based on the attention system theory as claimed in claim 1, wherein: in step 1), the carolina squash scale divides alertness into 9 levels: 1 is extremely alert; 2 ═ very alert; 3 ═ alert; 4 ═ comparative alertness; 5 ═ neither alert nor sleepy; 6-there was some evidence of fatigue; 7-sleepy, but without the feeling of wanting to stay awake; 8, sleepy and wants to keep awake; 9 is very sleepy, trying to stay awake and struggle against fatigue.
3. The alertness test method based on the attention system theory as claimed in claim 2, wherein: in step 3), the method for obtaining the persistent alert probability based on the persistent alert indicator and judging the persistent alert degree of the subject according to the persistent alert probability includes:
single reaction time data RT for reacting all subjects to J events Ji Taking an average value to obtain the response of the testee to the J eventAverage reaction time data of
Figure FDA0003805986890000031
The formula is as follows:
Figure FDA0003805986890000032
wherein n is the number of data in all single reactions of the subject to react to the J event;
and then according to the single reaction time data RT of the tested person reacting to the J event Ji And average reaction time data of the subject reacting to the J event
Figure FDA0003805986890000033
Calculating the standard deviation sigma of the reaction time of the human subject reacting to the J event J The formula is as follows:
Figure FDA0003805986890000034
and then according to the average reaction time data of the tested person reacting to the J event
Figure FDA0003805986890000035
Standard deviation sigma of reaction time of the subject to react to J event J Calculating critical reaction time data RT of the human subject reacting to the J event J0 The formula is as follows:
Figure FDA0003805986890000041
single reaction time data RT for finally making the subject react to J event Ji Data RT greater than the critical reaction time of the subject to react to the J event J0 As the persistent alert probability P J And using the persistent alert probability P J Persistence of the subjectJudging the degree of sexual alertness, if the probability of sexual alertness P is continuous J < 0.059, indicating that the degree of persistent alertness of the subject is "good", otherwise "poor".
4. The alertness test method based on the attention system theory as claimed in claim 2, wherein: in step 4), the method for obtaining the staged alertness probability based on the staged alertness index and judging the staged alertness level of the subject according to the staged alertness probability includes:
single reaction time data RT for reacting a subject to an S event Si Taking an average value to obtain average reaction time data of the subject reacting to the S event
Figure FDA0003805986890000042
The formula is as follows:
Figure FDA0003805986890000043
wherein n is the number of data in all single reactions of the subject to react to the S event;
then according to the single reaction time data RT of the subject reacting to the S event Si Average reaction time data of the subject reacting to the S event
Figure FDA0003805986890000044
Calculating the standard deviation sigma of the reaction time of the subject reacting to the S event S The formula is as follows:
Figure FDA0003805986890000045
then according to the average reaction time data of the tested person reacting to the S event
Figure FDA0003805986890000046
And is testedStandard deviation σ of the reaction time of a person to S event S Calculating critical reaction time data RT of the subject reacting to the S event S0 The formula is as follows:
Figure FDA0003805986890000047
finally, the single reaction time data of the subject reacting to the S event is larger than the critical reaction time data RT of the subject reacting to the S event S0 As the staged alertness probability P S And using the staged alertness probability P S And judging the stage alertness of the testee, wherein if the stage alertness probability Ps is less than 0.04, the stage alertness of the testee is 'good', otherwise, the stage alertness of the testee is 'poor'.
5. The alertness test method based on the attention system theory as claimed in claim 2, wherein: in step 5), the method for obtaining the selective attention probability based on the selective attention indicator and judging the selective attention degree of the subject according to the selective attention probability is as follows:
single reaction time data RT for reacting a subject to an F event Fi Taking an average value to obtain average reaction time data of the testee reacting to the F event
Figure FDA0003805986890000051
The formula is as follows:
Figure FDA0003805986890000052
wherein n is the number of data in all single reactions of the subject to react to the F event;
then according to the single reaction time data RT of the subject reacting to the F event Fi Average reaction time data of the subject reacting to the F event
Figure FDA0003805986890000053
Calculating the standard deviation sigma of the reaction time of the subject reacting to the F event F The formula is as follows:
Figure FDA0003805986890000054
and then according to the average reaction time data of the testee reacting to the F event
Figure FDA0003805986890000055
Standard deviation sigma of reaction time of subject to react to F event F Calculating critical reaction time data RT of the subject reacting to the F event F0 The formula is as follows:
Figure FDA0003805986890000056
finally, the single reaction time data of the subject reacting to the F event is larger than the critical reaction time data RT of the subject reacting to the F event F0 As the selective attention probability P F And using the selective attention probability P F Judging the selective attention degree of the testee, if the selective attention probability P is F < 0.069, indicating that the subject's selective attention is "good", otherwise "poor".
6. The alertness test method based on the attention system theory as claimed in claim 1, wherein: in step 6), the average reaction time data
Figure FDA0003805986890000061
The formula (c) is as follows:
Figure FDA0003805986890000062
wherein: n is the number of data of all single reactions of the testee;
in step 7), the reaction standard deviation σ is formulated as follows:
Figure FDA0003805986890000063
in step 8), the formula of the coefficient of variation X is as follows:
Figure FDA0003805986890000064
in step 9), the formula of the accuracy rate Y is as follows:
the accuracy Y is (number of correct reactions/total number of total reactions) × 100%.
7. The alertness test method based on the attention system theory as claimed in claim 1, wherein: in step 10), the method for determining the alertness level of the subject is as follows:
the alertness level A is obtained when X is more than 0.84 and Y is more than or equal to 95 percent;
when X is more than 0.84 and Y is more than or equal to 85 percent and less than 95 percent, the degree of alertness is grade A;
the alertness grade A is when X is more than 0.84 and Y is less than 85%;
the alertness class B is determined when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 95 percent;
the alertness grade A is obtained when X is more than 0.67 and less than or equal to 0.84 and Y is more than or equal to 85 and less than 95 percent;
the alertness grade A is when X is more than 0.67 and less than or equal to 0.84 and Y is less than 85 percent;
when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 95 percent, the alertness is grade C;
the alertness grade B is obtained when X is more than 0.58 and less than or equal to 0.67 and Y is more than or equal to 85 and less than 95 percent;
the alertness grade A is when X is more than 0.58 and less than or equal to 0.67 and Y is less than 85 percent;
when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 95 percent, the degree of alertness is grade D;
the alertness grade C is obtained when X is more than 0.51 and less than or equal to 0.58 and Y is more than or equal to 85 and less than 95 percent;
the alertness is grade B when X is more than 0.51 and less than or equal to 0.58 and Y is less than 85 percent;
the alertness level E is obtained when X is less than or equal to 0.51 and Y is more than or equal to 95 percent;
the alertness grade D is when X is less than or equal to 0.51 and Y is more than or equal to 85% and less than 95%;
the alertness grade B is obtained when X is less than or equal to 0.51 and Y is less than 85 percent;
wherein, the alertness grade A represents that the subject is very tired; alertness grade B represents subject fatigue; the alertness degree C indicates that the subject is neither tired nor alert; the level D of alertness represents the alertness of the testee; the alertness level E indicates that the subject is very alert.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5911581A (en) * 1995-02-21 1999-06-15 Braintainment Resources, Inc. Interactive computer program for measuring and analyzing mental ability
CN103019383A (en) * 2012-12-18 2013-04-03 北京大学 Steady state visual evoked potential brain-computer interface signal identification method
CN109833048A (en) * 2019-01-23 2019-06-04 中国民航大学 A kind of alertness measurement method based on psychomotor abilities

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7682024B2 (en) * 2003-03-13 2010-03-23 Plant Charles P Saccadic motion sensing
CA3113322C (en) * 2018-09-18 2023-08-22 NeuroSteer Ltd. Systems and methods for cooperative invasive and noninvasive brain stimulation

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5911581A (en) * 1995-02-21 1999-06-15 Braintainment Resources, Inc. Interactive computer program for measuring and analyzing mental ability
CN103019383A (en) * 2012-12-18 2013-04-03 北京大学 Steady state visual evoked potential brain-computer interface signal identification method
CN109833048A (en) * 2019-01-23 2019-06-04 中国民航大学 A kind of alertness measurement method based on psychomotor abilities

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
A study of the effective way to release scent to maintain alertness;Yukie Hirata;《JSAE Review》;20011231(第22期);全文 *
Estimation of driver alertness to different colors and intensities using brain visual evoked potentials;Mones Bekdash et al;《2016 6th International Conference on Intelligent and Advanced Systems (ICIAS)》;20161231;全文 *
基于视频人脸图像的警觉度估计研究;吴天翔;《中国优秀硕士学位论文全文数据库 信息科技辑》;20130715(第07期);全文 *
飞行人员疲劳风险分析及测量研究;田万里;《中国优秀硕士学位论文全文数据库》;20170315(第03期);全文 *

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