CN108175424B - Test system for cognitive ability value test - Google Patents
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Abstract
The invention provides a test system for testing cognitive ability values, which is characterized in that the test system sets at least one piece of stimulation information based on psychology characteristic parameters of each cognitive dimension; testing the at least one piece of stimulation information on a sample person and obtaining the validity of the sample; testing the validity of the sample by utilizing a normal distribution model; retaining the at least one stimulation information with the sample validity conforming to the normal distribution model. The invention reasonably selects stimulation information with high effectiveness based on a normal distribution model, and dynamically compiles lie detection stimulation information and guiding stimulation information according to the change of the physiological state and the psychological state of the tester, thereby obtaining the real cognitive ability value data of the tester.
Description
The invention is a divisional application with application number of 201510484841.9, application date of 2015, 08 and 07, application type of invention and application name of a stimulus information compiling method for cognitive ability value test.
Technical Field
The invention relates to the technical field of testing machines, in particular to a testing system for testing a cognitive ability value and a stimulus information compiling method.
Background
Cognitive abilities (cognitive abilities) refer to the ability of the human brain to process, store and extract information, i.e., the ability of people to grasp the relationship between the composition and performance of things and other things, the dynamics of development, the development direction and the basic rules. It is the most important psychological condition for people to successfully complete activities. The abilities of perception, memory, attention, thinking and imagination are all considered cognitive abilities.
The current testing means in the testing technical field mainly takes a question and answer test paper mode. The test questions in the test paper obtain the feedback information of the testers in a mode of setting a contextual model. The test questions are obtained by testing a large number of sample persons and then calculating the identification indexes and the difficulty level of the sample persons, so that the cognitive abilities of different persons are distinguished. Those in various fields are then tested to form a normal model. And comparing the scores of the ordinary testers with the normal scores during testing. The stimulation information of the test questions is tedious and can not fully mobilize the sense organ and the information state of the testers. Moreover, the feedback information of the testers is the answer fed back after the brain analyzes the test questions and judges the possible trend of the test questions by combining with common knowledge, and is not the direct and real reaction of the testers. Therefore, the method of compiling the stimulus information into the test question form cannot obtain the best test result, and has a large test error.
Patent (CN 104363948A) discloses a stimulus presentation system that determines a psychological state by measuring a line of sight and a brain function of a user, and changes presentation contents of a problem based on the determined psychological state. The technical problem to be solved is as follows: in the case where it is inferred that the user is paying attention, or concentrating, it cannot be inferred whether there is concern or danger is perceived. In this way, when there are a plurality of psychological states as possibilities, if the external device is automatically operated without discriminating the psychological state, it is not always possible to perform an appropriate operation. Although the system can present various stimulation information, the compiling method of the stimulation information is not disclosed, and the stimulation information is not completely suitable for testing the cognitive ability value.
US patent (US8048002B2) discloses a method of improving cognitive and motor time and discloses the content: providing a series of stimuli to a subject; receiving a sensor signal associated with a subject's response to a stimulus; and recording a response time from the sensor signal, wherein the recorded response time is associated with the subject's response to the series of stimuli, and wherein the response time has a correlation profile. The method also includes analyzing the distribution of the subject's response times to determine variability of the subject's expected times relative to the stimulus, and generating a subject feedback signal corresponding to the analysis results to train the subject to improve the subject's expected times. However, this patent does not disclose the technical feature of the present invention of comparing the test score of the test person with the score of the valid sample person in the normal distribution model to confirm the distribution of each cognitive dimension of the test person. The test system of the invention can obtain more accurate test results.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a stimulus information compiling method for testing a cognitive ability value, which is characterized by at least comprising the following steps:
selecting at least one piece of stimulation information of which the test validity of the sample personnel conforms to normal distribution;
setting at least one reasonable ranking for the test person to select according to personal interests based on the validity and cognitive dimensionality of the at least one stimulation message;
dynamically programming lie detection stimulation information and/or reverse stimulation information according to physiological information and/or psychological state of a tester so as to test the reliability of the tester;
and comparing the test scores of the testers with the scores of the valid sample personnel in the normal distribution model so as to confirm the distribution condition of each cognitive dimension of the testers.
According to a preferred embodiment, the stimulation information compiling method further comprises:
and dynamically adjusting the test sequence of the stimulation information based on the physiological information and/or the psychological state of the test person so as to obtain a real test result of the test person maintaining a good psychological state.
According to a preferred embodiment, the step of selecting at least one stimulation information with a test validity of the sample population fitting a normal distribution comprises at least:
setting at least one piece of stimulation information based on the psychological characteristic parameters of each cognitive dimension;
testing the at least one piece of stimulation information on a sample person and obtaining the validity of the sample;
testing the validity of the sample by utilizing a normal distribution model;
retaining the at least one stimulation information with the sample validity conforming to the normal distribution model.
According to a preferred embodiment, the step of selecting at least one stimulation information with a test validity of the sample population fitting a normal distribution comprises at least:
performing a second test on the at least one piece of stimulation information with the sample validity conforming to the normal distribution model for sample personnel of different ethnicities, different ages, different blood types and/or different cultural backgrounds;
and selecting the at least one piece of stimulation information with the second sample validity conforming to the normal distribution model.
According to a preferred embodiment, the stimulation information compiling method further comprises:
and dynamically inserting guiding stimulation information based on the physiological information and/or the psychological state of the test person so as to guide the psychological state of the test person with poor psychological state to recover to a good state.
According to a preferred embodiment, the stimulation information compiling method further comprises:
regulating the presentation speed of the stimulation information based on the recorded response time index of the tester in the test process, measuring the seriousness of the tester by the response time index and guiding the tester to adjust the seriousness,
wherein the means for guiding the test person to adjust the level of seriousness comprises alerting and/or presenting guiding stimulus information.
According to a preferred embodiment, the physiological information comprises at least brain information, facial muscle movement information, eye movement information, body movement information, sound wave information, reaction time information, pulse information, blood pressure information and/or body temperature information.
According to a preferred embodiment, the stimulus information comprises virtual reality context information for enabling the test person to blend in a real context, the virtual reality context information comprising at least auditory stimulus information, visual stimulus information, olfactory stimulus information and/or tactile stimulus information.
According to a preferred embodiment, the stimulation information is holographic scenario stimulation information at least comprising auditory stimulation information and holographic image stimulation information matched with the auditory stimulation information, and the holographic scenario stimulation information presents real scenario stimulation in a three-dimensional stereoscopic image mode so as to obtain a real-time cognitive ability test value of the test person;
the holographic image stimulation information comprises a static holographic image and a dynamic holographic image.
According to a preferred embodiment, the tactile stimulation information comprises braille tactile stimulation information.
The invention has the beneficial technical effects that:
(1) stimulation information with high effectiveness is selected based on a normal distribution model, so that the method is suitable for a wide range of people and has more accurate test effect.
(2) The sequence of the stimulation information is dynamically adjusted or the guiding stimulation information is programmed according to the physiological state and the psychological state of the testers, so that the testers can test under a good psychological state, and the test error caused by psychological factors is reduced.
(3) And dynamically and randomly compiling lie detection stimulation information to reduce the situation that the tester feeds back false information based on result trends.
(4) The virtual reality contextual information or the holographic contextual stimulus information is adopted for testing, compared with the test questions of the stroke test contextual model, the visual test contextual model is more real, and the real stimulus response can be fed back by the testers to obtain the real cognitive competence value of the testers.
Drawings
FIG. 1 is a logic block diagram of a stimulation information generation method; and
FIG. 2 is a schematic diagram of a normal distribution model.
Detailed Description
The following detailed description is made with reference to the accompanying drawings.
The invention provides a stimulation information compiling method for cognitive ability value testing. The invention selects the brain stimulation information, the visual stimulation information, the auditory stimulation information and/or the tactile stimulation information with high effectiveness based on the normal distribution model. Wherein the tactile stimulation information comprises braille tactile stimulation information.
And arranging various sorts of the stimulation information in a scientific and reasonable mode. Or simultaneously, thereby being suitable for wide social personnel, in particular for the disabled such as the blind, the deaf-mute and the like.
In the invention, the dimensions of cognitive ability at least comprise perception, memory, attention, concept acquisition, imagination, thinking, operation, reasoning, judgment, creation, problem solving, language and meta cognition.
Perception is that people have information about the outside world through their senses. The information is processed (integrated and interpreted) through the brain, and a psychological phenomenon reflecting the whole object, namely perception, is generated.
Memory is a psychological process of accumulating and preserving individual experience in the mind of people by means of learning, keeping, reproducing (recalling ), and the like. The term of information processing is used, namely the process of encoding, storing and extracting externally input information by human brain.
Note the direction and concentration of mental activity or awareness to certain objects.
Concept acquisition, also known as "concept mastering," is a type of intelligent learning. The essence of the method is that the individual grasps the common key characteristics (or essential characteristics) of the same things or phenomena through the active thinking activity.
Imagination is the process of processing and modifying the existing expression in the mind to create a new image.
Thinking is the generalization and indirect reflection of objective things that the human brain accomplishes by means of speech, appearance and action. Mainly manifested in the activities of people to solve problems.
Thinking operations are the speed and efficiency that have been demonstrated in solving new problems using previous experience.
Inference, or logical reasoning, refers to the mental activities of inducing general rules from specific things or drawing new conclusions from the existing knowledge. And essentially falls within the scope of problem resolution.
Judgment is a form of thinking about the object and its characteristics in positive or negative.
Creating or creating an activity is an activity that provides a novel, pioneering, socially significant product. It is an exploratory activity with no existing solutions and procedures to solve the problem.
The problem solution has two meanings:
1 generally refers to the mental activities that are triggered by the problem and point out its solution.
2 refers to a series of cognitive operations directed to the target. I.e., the process of achieving a goal through a series of purposeful, directed, cognitive sequences of operations. It is of two types: one is conventional problem solving, i.e. the problem is solved by using the existing methods and procedures; another is the inventive solution to the problem, i.e. applying new methods and procedures to solve the problem.
The broad language (language) is a tool for symbolizing human thoughts and emotions and communicating emotions with others, and it is a narrow language (speaking) such as speech, characters, sign language, music, pictures, sculptures, etc.
Meta-cognition is also called reflexive cognition and postpresumed cognition and refers to the cognition of an individual to the cognitive course of the individual. From the psychology of learning point of view, it comprises two components (or two levels): (1) and (4) meta-cognitive knowledge. (2) Meta cognitive skills.
In psychology testing, efficacy refers to the degree of coincidence between measured psychological traits, or to the accuracy of a psychology test.
The total variance + error variance + related variance + independent stable variance + error variance, i.e.:
the definition of efficacy is: the ratio of the true variance (effective variance) to the total variance associated with the measurement.
Namely:
the validity is continuous, and the test validity is usually expressed by a correlation coefficient and only varies in degree. The efficacy value is generally between 0.4 and 0.7. The greater the value, the higher the efficacy.
The validity mainly comprises content validity, conception validity, validity standard validity and demonstration validity.
The test dimensions of validity include surface validity, content validity, programming validity, and experience validity.
The significance response test predicts the effectiveness degree of the individual performance under a certain situation. The predicted behavior is a criterion for checking validity, called validity criterion for short. The validity in the present invention mainly refers to validity standard validity.
The correlation method is the most commonly used method for evaluating the validity of the validity criterion, and is to find the correlation between the test score and the validity criterion, and the correlation coefficient is called validity coefficient.
The calculation method of the validity coefficient comprises a product difference correlation method, a point two-row correlation method, a two-row correlation method and a Juspen multi-row correlation method.
As shown in fig. 1, the stimulation information preparation method of the present invention at least includes:
selecting at least one piece of stimulation information of which the test validity of the sample personnel conforms to normal distribution;
setting at least one reasonable ranking based on the validity and cognitive dimensionality of at least one piece of stimulation information for the tester to select according to personal interests;
dynamically programming lie detection stimulation information and/or reverse stimulation information according to the physiological information and/or the psychological state of the testers so as to test the reliability of the testers;
and comparing the test scores of the testers with the scores of the valid sample personnel in the normal distribution model so as to confirm the distribution condition of each cognitive dimension of the testers.
And setting psychological characteristic parameters according to a psychological classical theory based on each cognitive dimension. At least one stimulation information is set for each characteristic parameter. The stimulation information may be a stimulation information group composed of a plurality of stimulation information.
The set stimulation information is regarded as pre-selected stimulation information and is used for testing corresponding characteristic parameters of a large number of sample persons, so that the sample validity of the test sample persons is obtained.
The invention utilizes a normal distribution model to test the validity of the sample.
The normal distribution model is: if the random variable x obeys a probability distribution with a position parameter of mu and a scale parameter of sigma and its probability density function is
The random variable is called a normal random variable, and the distribution obeyed by the normal random variable is called a normal distribution and is recorded as X-N (mu, sigma)2) Read as X obeys X to N (mu, sigma)2) Or X follows a normal distribution.
When μ is 0 and σ is 1, the normal distribution is called a standard normal distribution
As shown in fig. 2, the sample validity is entered into a standard normal distribution model. And dividing the distribution situation of each cognitive dimension level of the sample personnel in the normal distribution graph into: very poor (5%), poor (20%), normal (50%), good (20%), good (5%) five levels. And if the distribution of the sample validity conforms to the trend of a normal distribution model, selecting stimulation information with high validity distributed near the central axis of the model. The stimulation information distributed closer to the central axis has a higher efficacy coefficient.
According to a preferred embodiment, the sample persons are divided into different groups according to race, age, blood type, cultural background. And testing the retained at least one stimulation message for the sample personnel of each group, and obtaining the sample validity of the test of the sample personnel of each group.
And carrying out a second test on the validity of the sample by using a normal distribution model. And keeping at least one stimulation information with high validity of the second sample distributed in the normal distribution model.
And the cognitive dimension values of the sample personnel selected by the stimulation information are distributed according to a normal distribution model. The distribution in the normal distribution diagram is divided into: very poor (5%), poor (20%), normal (50%), good (20%), good (5%) five levels.
And classifying the stimulation information according to the tested cognitive dimension types, and arranging the presentation sequence of the stimulation information according to the sequence of testing the cognitive dimensions. The testing of one cognitive dimension includes testing of multiple stimulus information. And calculating a score value corresponding to the feedback information of the tester. And comparing the distribution areas of the normal distribution models corresponding to the score values corresponding to the cognitive dimensions, so as to determine the grade corresponding to the cognitive dimensions of the tester.
The present invention is not limited to the use of a normal distribution model to select stimulation information with high effectiveness.
According to a preferred embodiment, the statistical model for selecting the stimulation information further comprises one or more of a least square model, a perceptron algorithm model, a Boost method model, a hidden markov model, a gaussian mixture model, a neural network model and a deep learning model.
According to a preferred embodiment, the validity of the stimulus information is calculated using a model of the perceptron algorithm.
The calculation steps of the sensor algorithm model are as follows:
s01: variables and parameters are set.
f (-) is the activation function, y (n) is the actual output of the network, d (n) is the expected output, η is the learning rate, n is the number of iterations, and e is the error between the actual output and the expected output.
S02: initialization
Each component of the weight vector W (1) is assigned a small random non-zero value, and n is set to 1.
S03: inputting a set of samples x (n) ═ 1, x1(n)，x2(n)，…xm(n)]And gives its desired output d (n).
S04: calculating the actual output:
s05: calculating the desired output and the actual output, calculating the variance e ═ d (n) -y (n)
Judging whether the current output meets the condition according to the error, wherein the error is zero or smaller than a preset value for all samples generally, finishing the writing algorithm, otherwise, increasing the value by 1, and adjusting the weight by using the following formula;
w(n+1)＝w(n)+η[d(n)-y(n)]x(n)
then, the process goes to S03, and the next round of calculation is performed.
According to the sensor model algorithm, a stimulation information sample with known validity is input into the sensor algorithm model, so that the sensor algorithm model learns and calculates the validity value of the stimulation information, and learns the grade classification of the validity. And then inputting a plurality of pieces of stimulation information into the sensor algorithm model, and calculating the validity of the newly input stimulation information and dividing the level of the validity by the sensor calculation model.
According to a preferred embodiment, the level of validity of the stimulation information is counted using a neural network model.
Neural Networks (NN) are complex network systems formed by a large number of simple processing units (called neurons) widely interconnected, reflect many basic features of human brain functions, and are highly complex nonlinear dynamical learning systems. The neural network has the capabilities of large-scale parallel, distributed storage and processing, self-organization, self-adaptation and self-learning, and is particularly suitable for processing inaccurate and fuzzy information processing problems which need to consider many factors and conditions simultaneously.
Learning is one of the most important and most compelling features of neural networks. In the development process of neural networks, the research of learning algorithms is of great importance. At present, neural network models proposed by people are all corresponding to learning algorithms. In neural networks, patterns provided by the external environment are learned and trained, and such patterns can be stored, and are called perceptrons. The cognitive machine has adaptability to the external environment, can automatically extract the change characteristics of the external environment, and is called a cognitive machine. The neural network is generally divided into two types of learning with teachers and learning without teachers in learning. The perceptron adopts the teacher signal to learn, and the cognitor adopts the non-teacher signal to learn.
And inputting stimulation information samples with determined validity into the neural network model, so that the neural network model learns how to modify the weight of each factor according to each calculation node through learning, thereby learning how to calculate the validity and grading the validity. Factors influencing the validity calculation include artificial errors, system errors, background errors, physiological errors and the like. And after the neural network model learns to calculate the validity of the stimulation information and the calculation is stable, fixing the weight of each factor. Validity of the plurality of stimulus information for each cognitive dimension is then calculated. The stimulation information is classified into at least two levels according to the effectiveness value.
And (3) carrying out statistics on the effectiveness coefficients of the stimulation information of sample personnel of different populations, different cultural backgrounds, different ages, different blood types and different sexes by utilizing a least square method model, a perceptron algorithm model, a Boost method model, a hidden Markov model, a Gaussian mixture model, a neural network model and/or a deep learning model. And selecting stimulation information with higher effectiveness for testing each sample person as test stimulation information.
And reasonably sequencing the stimulation information according to the type of the tested cognitive dimensionality, and performing pre-compilation. At least one sorting mode. The sequencing of the stimulation information is the sequencing of various different sequences with the same test effect, so that a tester can conveniently select the sequence for testing the cognitive dimensionality according to personal interest in a normal state.
After the stimulation information is sequenced, the pre-programmed stimulation information is used for testing the cognitive ability value of a common tester. And the test scores of the testers are compared with the scores of the effective sample personnel in the statistical model so as to confirm the score distribution condition of each cognitive dimension of the testers.
Meanwhile, in order to prevent the tester from feeding back false information due to non-serious attitude, the test result is not accurate. The stimulation programming method of the invention also comprises the steps of collecting physiological information of the testers and distinguishing the psychological states of the testers in the test process. The invention can dynamically compile lie detection stimulation information and/or reverse stimulation information according to the physiological information and/or the psychological state of the testers in the testing process so as to test the reliability of the testers.
The lie-detecting stimulus information may appear as "i would sometimes want something to do with someone. And the tester is required to feed back whether the condition of the tester is met. If the information fed back by the tester is not very compliant, the tester is dishonest.
The lie detection stimulus information also includes presenting both forward and reverse stimulus information.
For example: presenting the forward stimulus information first "i am courageous and straight ahead in the face of adversity". The feedback information of the testing personnel is very suitable for the situation of the testing personnel. The counter stimulus information is then presented "i never take the risk without sufficient grasp". If the feedback information of the tester is not in accordance with the condition of the tester, the answer is honest, and if the feedback information of the tester is in accordance with the condition of the tester, the tester is dishonest. And if the attitude of the tester is found to be dishonest, repeatedly presenting the stimulus information presented near the lie-detecting stimulus information, and repeatedly testing. The following prompts appear: "please see the question clearly and answer again".
And regulating and controlling the presentation speed of the stimulation information according to the response time of the tester in the test process recorded by the test system so as to adapt to the test speed of the tester. The invention can also measure the seriousness of the testers by taking the reaction time as an index. The way of guiding the tester to adjust the degree of seriousness includes warning and/or presenting guidance stimulus information.
If the attitude of the tester is not serious, the information is fed back without reflecting the stimulation information. The test system presenting the stimulus information issues a warning message to bring the tester back into a serious attitude.
Alternatively, according to a preferred embodiment, the guiding stimulus information is dynamically inserted based on the physiological information and/or the psychological state of the test person to guide the psychological state of the test person with bad psychological state to return to a good state.
For example, guidance stimulus information that reverses the psychological state of non-recognition is inserted into the stimulus information, thereby guiding the test person to return to recognition. The guiding stimulation information can guide the poor psychological state to be restored to the better psychological state.
The physiological information collected by the invention at least comprises brain information, facial muscle movement information, eyeball movement information, body movement information, sound wave information, reaction time information, pulse information, blood pressure information and/or body temperature information.
Brain information includes, but is not limited to, brain activity delay time, Oxy-Hb signal, Deoxy-Hb signal, Total-Hb signal, interval designation, channel designation, maximum value, latency, half-value width, average value, discrete value, median value, number of additions, phase difference, heart rate, and FFT component.
Facial muscle movement information includes, but is not limited to, facial expressions, facial muscle activity tracks, and the like.
Eye movement information includes, but is not limited to, viewing angle, central viewing angle (within 20 degrees), peripheral viewing angle (outside 20 degrees), gaze coordinates range, gaze time dispersion, gaze direction, eye dwell time, eye dwell range, number of blinks, blink speed, eye closure time, saccade distance, saccade frequency, pupil aperture, gaze pattern, and number of gaze patterns.
Body motion information includes, but is not limited to, swallowing, salivation, salivary content, brain wave bands, phenomenon-associated potentials, blood pressure, heart beat, and skin potentials.
The sound wave information includes, but is not limited to, the size of the sound, the level of the sound, and the speaking speed.
According to the collected physiological information parameters, the psychological state of the test person can be distinguished, such as whether the test person is nervous or excited abnormally.
According to a preferred embodiment, the test sequence of the stimulus information is dynamically adjusted based on the physiological information and/or the psychological state of the test person to obtain a real test result of the test person maintaining a good psychological state.
If the reaction time of the tester is prolonged in the process of testing a certain cognitive dimension according to the acquired physiological information parameters, the eyeball activity is slowed down, and the psychological state of the tester is identified to be boring. And the test system pre-adjusts the sequence of subsequent cognitive dimensions and adjusts the next cognitive dimension into a cognitive dimension test with less active stimulation information. Thus, the next cognitive dimension tested by the tester will be relaxed and interesting, and the psychological state will be restored to the better state.
According to a preferred embodiment, the stimulus information of the present invention further includes virtual reality scenario information for enabling the test person to blend in the real scenario, the virtual reality scenario information including at least auditory stimulus information, visual stimulus information, olfactory stimulus information, and/or tactile stimulus information.
Auditory stimulation information and visual stimulation information are presented to a tester through a virtual reality instrument, so that the tester feels the real interactive scene, the truest stress response is generated, and an accurate test result is obtained.
According to a preferred embodiment, the stimulation information is holographic scene stimulation information at least comprising auditory stimulation information and holographic image stimulation information matched with the auditory stimulation information, and the holographic scene stimulation information presents real scene stimulation in a three-dimensional stereo image mode so as to obtain a real-time cognitive ability test value of a tester; the holographic image stimulation information comprises a static holographic image and a dynamic holographic image.
The hologram is a three-dimensional image that can be reconstructed by illuminating a light source on the hologram, the frequency and transmission direction of the light source being identical to the reference beam. The viewer can see the sides of the object from different angles, but not visible because only images are recorded.
And simultaneously presenting the auditory stimulation information and the three-dimensional holographic image to a tester. The sense of the tester is activated, and the vivid contextual model is beneficial for the tester to quickly show the real level of cognitive ability. The tester can also speak to express the feedback behavior or psychological feeling of the tester.
When the olfactory stimulus information and the three-dimensional dynamic hologram are simultaneously presented to the tester, for example, a stranger invites the tester to taste a delicious real object. The tester gives real test answers based on own behaviors, but does not give test answers after three thoughts by recalling daily life. Because the behavior result after the memory judgment of the testers is not necessarily the real behavior, but the stress behavior facing the stereoscopic image expression is more real. Therefore, compiling the auditory stimulation information, the olfactory stimulation information and the visual stimulation information is more favorable for obtaining an accurate result of the cognitive ability value test.
The invention selects high-efficiency stimulation information through a scientific normal distribution model or other statistical models, and utilizes a three-dimensional holographic image or a virtual reality scene to compile vivid stimulation information to obtain more real stress behaviors of testers, thereby obtaining an accurate test result.
It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and figures are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents.
Claims (5)
1. A method for programming stimulation information for cognitive ability value testing, the method comprising at least:
selecting at least one stimulation information for which the test validity of the sample population conforms to a normal distribution, wherein,
setting at least one piece of stimulation information based on the psychological characteristic parameters of each cognitive dimension;
testing the at least one piece of stimulation information on a sample person and obtaining the validity of the sample;
testing the validity of the sample by utilizing a normal distribution model;
retaining the at least one stimulation information with the sample validity conforming to the normal distribution model;
setting a reasonable ordering of the at least one stimulation information based on the validity and cognitive dimensions of the at least one stimulation information for the tester to select according to personal interests;
dynamically programming lie detection stimulation information and/or reverse stimulation information according to physiological information and/or psychological state of a tester so as to test the reliability of the tester;
comparing the test scores of the testers with the scores of the valid sample personnel in a normal distribution model so as to confirm the distribution condition of each cognitive dimension of the testers;
the method comprises the steps of classifying stimulation information according to the types of tested cognitive dimensions, arranging a stimulation information presentation sequence according to the sequence of testing the cognitive dimensions, testing one cognitive dimension by a plurality of stimulation information, calculating score values corresponding to feedback information of a tester, and comparing distribution areas of normal distribution models corresponding to the score values corresponding to the cognitive dimensions so as to determine the grade corresponding to the cognitive dimensions of the tester.
2. The stimulus information formulation method for a cognitive ability value test according to claim 1, further comprising:
and dynamically adjusting the test sequence of the stimulation information based on the physiological information and/or the psychological state of the test person so as to obtain a real test result of the test person maintaining a good psychological state.
3. The method for formulating stimulation information for use in a cognitive ability value test as claimed in claim 2, wherein the step of selecting at least one stimulation information whose test validity of the sample population conforms to a normal distribution at least comprises:
performing a second test on the at least one piece of stimulation information with the sample validity conforming to the normal distribution model for sample personnel of different ethnicities, different ages, different blood types and/or different cultural backgrounds;
and selecting the at least one piece of stimulation information with the second sample validity conforming to the normal distribution model.
4. The stimulus information formulation method for a cognitive ability value test according to claim 3, further comprising:
and dynamically inserting guiding stimulation information based on the physiological information and/or the psychological state of the test person so as to guide the psychological state of the test person with poor psychological state to recover to a good state.
5. The stimulus information formulation method for a cognitive ability value test according to claim 4, further comprising:
regulating the presentation speed of the stimulation information based on the recorded response time index of the tester in the test process, measuring the seriousness of the tester by the response time index and guiding the tester to adjust the seriousness,
wherein the means for guiding the test person to adjust the level of seriousness comprises alerting and/or presenting guiding stimulus information.
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| WO2017024845A1 (en) * | 2015-08-07 | 2017-02-16 | Beijing Huandu Institute Of Wisdom-Mind Technology Ltd. | Stimulus information compiling method and system for tests |
| CN105433962A (en) * | 2015-12-23 | 2016-03-30 | 牡丹江师范学院 | Intelligent psychological teaching and psychological testing experiment device |
| JP6196402B2 (en) * | 2016-02-29 | 2017-09-13 | ダイキン工業株式会社 | Determination result output device, determination result providing device, and determination result output system |
| CN106388833A (en) * | 2016-09-09 | 2017-02-15 | 宇龙计算机通信科技(深圳)有限公司 | Virtual reality mental quality assessment method and system |
| US10639448B2 (en) * | 2018-04-13 | 2020-05-05 | The Regents Of The University Of California | Cognition and memory enhancement via multiple odorant stimulation |
| CN109445578A (en) * | 2018-10-12 | 2019-03-08 | 上海陈天桥脑疾病研究所 | A kind of cognitive ability assessment system and method |
| CN109589122B (en) * | 2018-12-18 | 2022-02-15 | 中国科学院深圳先进技术研究院 | Cognitive ability evaluation system and method |
| SG10201907343SA (en) * | 2019-08-08 | 2021-03-30 | Symrise Ag | Prediction of the long-term hedonic response to a sensory stimulus |
| CN111045520B (en) * | 2019-12-27 | 2021-08-17 | 电子科技大学 | Method for regulating and controlling user time perception and telepresence in virtual reality |
| CN112674769B (en) * | 2020-12-10 | 2023-07-18 | 成都探马网络科技有限公司 | Psychological test method based on psychological projection |
| CN113080969B (en) * | 2021-03-29 | 2022-06-21 | 济南大学 | Multi-mode feature-based lie detection data processing method and system |
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| CN1739451A (en) * | 2005-07-21 | 2006-03-01 | 高春平 | Method and device for monitoring psycological and professional test truth |
| WO2014075029A1 (en) * | 2012-11-10 | 2014-05-15 | The Regents Of The University Of California | Systems and methods for evaluation of neuropathologies |
| CN103440864A (en) * | 2013-07-31 | 2013-12-11 | 湖南大学 | Personality characteristic forecasting method based on voices |
| CN103745084A (en) * | 2013-12-16 | 2014-04-23 | 北京工业大学 | Chinese medicine tongue color perception quantification method based on psychophysical test |
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| CN105105772B (en) | 2018-01-09 |
| CN108175424A (en) | 2018-06-19 |
| CN108186031A (en) | 2018-06-22 |
| CN108186031B (en) | 2021-02-09 |
| HK1217628A1 (en) | 2017-01-20 |
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