CN112950609A - Intelligent eye movement recognition analysis method and system - Google Patents
Intelligent eye movement recognition analysis method and system Download PDFInfo
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Abstract
The invention discloses an intelligent eye movement recognition analysis method and system, which are used for reading and testing a person to be tested, acquiring eye movement information and voice information of the person to be tested through intelligent glasses, obtaining correct information and error information read by the person to be tested based on the voice information, analyzing eye movement conditions corresponding to the correct information and the error information in the test process, and judging whether the eye movement conditions meet normal standards or not based on eye movement rules under normal conditions.
Description
Technical Field
The invention relates to the technical field of intelligent recognition, in particular to an intelligent eye movement recognition analysis method and system.
Background
Research shows that compared with the functions of regulation, convergence and dispersion, the eyeball movement function of a normal individual develops slowly and runs through the whole primary school stage. In addition, with the widespread use of information technology, the extremely large eye load for near distance use also causes eye movement dysfunction to various degrees. Therefore, the abnormal function of the eyeball movement can occur in any stage, which further influences the learning and cognitive function of the patient, causes the learning difficulty of reading and writing disorder and the like, interferes the learning, the work and the life of the patient, and brings great economic and psychological burden to individuals, families and society. The international association for read-write impediments (IDA for short) points out: read-write disorders affect nearly 10-20% of the population and comprise a significant proportion of adults. According to statistics, about 15% of school-age children in the uk suffer from varying degrees of difficulty in reading and writing, and the U.S. prevalence is between 15% and 20%, with boys 3-4 times higher than girls. The concern on the read-write disorder in China is late, in 2016, Chinese read-write difficulty and experts on international development forum indicate that the prevalence rate of read-write disorder patients in China is about 10%, and children patients are about 1500 ten thousand. The study finds that the eye movement function abnormality is the main reason of learning difficulty, and Hoffman et al analyzes 107 children with learning difficulty in 5-14 years old to find that 95% of children have eye movement abnormality, and only 24% of people with normal learning ability have eye movement function abnormality. Lieberman et al also presented the same findings. In addition, various psychological disorders and nervous system disorders also show different types of eye movement dysfunction.
Therefore, accurate and objective evaluation and treatment of the eye movement function are important for improving reading, concentration, various cognitive abilities, assisting psychology, nerves and other specialized diagnoses and treatments, are one of important means for improving learning difficulty and improving treatment effects of psychology and nervous system diseases, and have good clinical application value. Therefore, various eye movement function detection devices should be operated, and with the development of infrared technology, electronic information technology, high-performance camera technology and image processing technology, higher-precision eye movement detection equipment has been applied to clinical applications, such as eye link II type eye tracker, general gold field eye tracker, and the like.
However, the existing equipment is expensive, high in inspection cost and not beneficial to clinical popularization and screening, and further cannot realize self-inspection of families, so that a method or a system is urgently needed for detecting patients at an initial stage and realizing the effect of pre-judging and preventing in advance.
Disclosure of Invention
Based on the technical problem, the invention provides an intelligent eye movement recognition analysis method, which comprises the following steps:
s1, setting reading test questions based on education levels;
s2, selecting corresponding reading test questions according to the education level of the target to be tested, performing reading test, and collecting voice information, reading time information and eye movement information of the target to be tested in the reading process;
s3, based on the reading test questions, identifying the voice information to obtain reading correct information and reading error information of the target to be tested;
s4, obtaining average speech speed information of the target to be detected through reading duration information based on the character scale of the reading test question;
s5, setting the average speech speed information as a threshold value, identifying the reading speed between characters of the target to be detected, and constructing a reading quality evaluation model of the target to be detected based on the correct reading information and the wrong reading information;
and S6, based on the reading quality evaluation model, establishing an eye movement information evaluation model through the eye movement information corresponding to the reading evaluation model, wherein the eye movement information evaluation model is used for evaluating the eye movement condition of the target to be measured.
Preferably, the length of the reading test question is at most 300 words;
the contents of the reading test questions are divided into preschool ages, primary schools, junior high schools, high schools and universities according to the education level;
content includes, but is not limited to, images, numbers, Chinese characters, foreign languages.
Preferably, S3 further includes obtaining the accuracy of the target to be measured according to the accuracy information.
Preferably, S4 further includes determining the average speech rate information based on the correct rate, and when the correct rate is greater than or equal to 85%, performing S5, otherwise performing S2.
Preferably, S5 further includes, when the speech rate information corresponding to the reading correct information is smaller than the threshold, adding the reading correct information corresponding to the speech rate information to the reading incorrect information, and constructing the reading evaluation model of the target to be measured.
Preferably, the eye movement information includes, but is not limited to, eye saccades, eye fixations and eye returns.
Preferably, S4 further includes that when the average speech rate information is lower or higher than the normal reading level, the target to be tested has problems, including but not limited to learning difficulties such as reading disorder, eye diseases, lack of knowledge level, and inattention;
the reading normal level is an interval value obtained by detecting the reading speeds of a plurality of persons with normal vision.
An intelligent eye movement recognition analysis system is characterized by comprising
The intelligent testing system comprises intelligent glasses and an intelligent testing terminal connected with the intelligent glasses;
the intelligent glasses comprise glasses and a glasses intelligent control system arranged on the glasses, wherein the glasses intelligent control system comprises,
an image acquisition device arranged at one end of a spectacle frame of the spectacles,
a first communication module arranged at the front end or the rear end of the glasses legs,
a voice input device arranged at one side of the glasses legs,
a voice receiving device arranged at one end of the glasses legs close to the ears of the human body,
the control system module is arranged at one end of the glasses leg close to the glasses frame and is respectively connected with the image acquisition device, the first communication module, the voice input device and the voice receiving device,
the first power supply management module is used for supplying power to the intelligent glasses;
the intelligent test terminal comprises a test terminal body,
the display module is used for displaying the reading test questions and selecting the corresponding reading test questions to test according to the requirements,
the display module control system is connected with the display module and comprises a circuit board,
and a chip integrated on the circuit board,
the storage module is connected with the chip and used for storing data information generated by the intelligent test terminal;
a second communication module connected with the chip and used for connecting the intelligent control system of the glasses,
a voice recognition module connected with the chip and used for recognizing the voice information of the intelligent control system of the glasses,
an image recognition module connected with the chip and used for collecting eye movement information,
and the second power management module is arranged at one end of the intelligent test terminal and used for supplying power to the intelligent test terminal.
Preferably, the first communication module and the second communication module are wireless transmission modules;
the wireless transmission module comprises but is not limited to a Bluetooth module and a Wifi module;
the first communication module is arranged at one side, far away from the control system, of the front end of the glasses leg;
the intelligent glasses are also connected with the mobile terminal through the first communication module;
the mobile terminal includes but is not limited to a mobile phone and a tablet computer.
Preferably, the first communication module and the second communication module are wired transmission modules;
wired transmission modules include, but are not limited to, fiber optic modules;
the first communication module is arranged at the rear end of the glasses leg;
the display module is a touch screen.
The positive progress effects of the invention are as follows:
compared with the prior art, the device has a simple structure, can determine whether the person to be detected has learning obstacle conditions such as difficulty in reading and the like by detecting the reading quality of the person to be detected, is suitable for general investigation and family self-investigation of large sample groups, is beneficial to early discovery of abnormal eye movement functions, and further realizes early prevention and intervention of the difficulty in learning.
Drawings
FIG. 1 is a flow chart of a method according to the present invention;
fig. 2 is a schematic diagram of a system according to the present invention, in which 1 is a first communication module, 2 is an image capture device, 3 is a voice receiving device, 4 is a voice input device, 5 is a control system module, 6 is an intelligent test terminal, and 7 is a first power management module;
fig. 3 is a schematic system diagram of the intelligent test terminal according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
There are 3 basic types of human eye movement: gaze, eye jump and follow-up movements are closely related to learning and reading cognitive processes, and at present, many studies have proved the close correlation between eye movements and learning and reading, wherein the main relevant eye movements are saccades, fixations and returns. The scanning time is about 10% of the reading process, the average scanning amplitude is about-8-9 character distance, the viewing angle is about 2 degrees, and the relative fixation and the static state are not formed between two scanning. For a normal reader, the average duration of fixation is about 200ms to 250 ms. An important feature of eye movement is diversity in normal reading situations. The saccade amplitude varies from 2 character spacing to 18 character spacing, and the duration of fixation varies from 100ms to 500 ms. Another important feature of reading eye movement is return. Return, i.e., right-to-left eye movement, corresponds to a reverse saccadic movement, which in an experienced reader is about 10-20% of the time. A return may occur when gazing targets are exceeded, the article understands incorrectly or cannot understand.
As shown in fig. 1-3, the present invention provides an intelligent eye movement recognition analysis method, which comprises the following steps:
s1, setting reading test questions based on education levels;
s2, selecting corresponding reading test questions according to the education level of the target to be tested, performing reading test, and collecting voice information, reading time information and eye movement information of the target to be tested in the reading process;
s3, based on the reading test questions, identifying the voice information to obtain reading correct information and reading error information of the target to be tested;
s4, obtaining average speech speed information of the target to be detected through reading duration information based on the character scale of the reading test question;
s5, setting the average speech speed information as a threshold value, identifying the reading speed between characters of the target to be detected, and constructing a reading quality evaluation model of the target to be detected based on the correct reading information and the wrong reading information;
and S6, based on the reading quality evaluation model, establishing an eye movement information evaluation model through the eye movement information corresponding to the reading evaluation model, wherein the eye movement information evaluation model is used for evaluating the eye movement condition of the target to be measured.
Preferably, the length of the reading test question is at most 300 words;
the contents of the reading test questions are divided into preschool ages, primary schools, junior high schools, high schools and universities according to the education level;
content includes, but is not limited to, images, numbers, Chinese characters, foreign languages.
S3 further includes obtaining the accuracy of the target according to the accuracy information.
S4 also includes, based on the correct rate, judging the average speed information, when the correct rate is greater than or equal to 85%, executing S5, otherwise executing S2.
S5 further comprises the step of adding the reading correct information corresponding to the speech speed information to the reading error information when the speech speed information corresponding to the reading correct information is smaller than a threshold value, and constructing a reading evaluation model of the target to be detected.
Eye movement information includes, but is not limited to, eye saccades, eye fixations and eye returns.
S4, when the average speed of speech information is lower or higher than the normal reading level, the target to be detected has problems, including but not limited to learning difficulties such as reading disorder, eye diseases, lack of knowledge level and attention deficit;
the reading normal level is an interval value obtained by detecting the reading speeds of a plurality of persons with normal vision.
As shown in fig. 2-3, an intelligent eye movement recognition analysis system is characterized by comprising
The intelligent testing system comprises intelligent glasses and an intelligent testing terminal connected with the intelligent glasses;
the intelligent glasses comprise glasses and a glasses intelligent control system arranged on the glasses, wherein the glasses intelligent control system comprises,
an image acquisition device 2 arranged at one end of the spectacle frame of the spectacles,
a first communication module 1 arranged at the front end or the rear end of the glasses legs of the glasses,
a voice input device 4 arranged at one side of the glasses legs,
a voice receiving device 3 arranged at one end of the glasses legs close to the ears of the human body,
the control system module 5 is arranged at one end of the glasses leg close to the glasses frame and is respectively connected with the image acquisition device 2, the first communication module 1, the voice input device 4 and the voice receiving device 3,
the first power management module 7 is used for supplying power to the intelligent glasses;
the intelligent test terminal comprises a test terminal body,
the display module is used for displaying the reading test questions and selecting the corresponding reading test questions to test according to the requirements,
the display module control system is connected with the display module and comprises a circuit board,
and a chip integrated on the circuit board,
the storage module is connected with the chip and used for storing data information generated by the intelligent test terminal;
a second communication module connected with the chip and used for connecting the intelligent control system of the glasses,
a voice recognition module connected with the chip and used for recognizing the voice information of the intelligent control system of the glasses,
an image recognition module connected with the chip and used for collecting eye movement information,
and the second power management module is arranged at one end of the intelligent test terminal and used for supplying power to the intelligent test terminal.
The first communication module 1 and the second communication module are wireless transmission modules;
the wireless transmission module comprises but is not limited to a Bluetooth module and a Wifi module;
the first communication module 1 is arranged on one side, far away from the control system, of the front end of the glasses leg;
the intelligent glasses are also connected with the mobile terminal through the first communication module 1;
the mobile terminal includes but is not limited to a mobile phone and a tablet computer.
The first communication module 1 and the second communication module are wired transmission modules;
wired transmission modules include, but are not limited to, fiber optic modules;
the first communication module 1 is arranged at the rear end of the glasses leg;
the display module is a touch screen.
Example 1: leading a tested person to a fixed position, leading the tested person to wear intelligent glasses, starting the intelligent glasses and an intelligent test terminal, knowing the education level of the tested person in an inquiry mode, selecting a corresponding test question to carry out initial test, informing the tested person to keep a posture as much as possible or standing still at the fixed position, starting the test, informing the tested person to relax the mood, reading line by line according to characters on the intelligent test terminal according to a voice prompt in a usual reading mode, checking specific conditions when the accuracy is low through a system, if the tested person belongs to more unrecognized characters, indicating that the test question is not suitable for a target to be tested, reducing difficulty for continuous test, and if other conditions are normal conditions, obtaining eye movement information of the tested person in the reading process through a system analysis result, and according to the conventional eye movement condition, and judging whether the tested person has vision-related learning obstacle conditions or not, and performing targeted training on the tested person according to the eye movement information so as to realize early prevention and intervention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes, or substitutions do not depart from the spirit and scope of the present invention in its spirit and scope. Are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An intelligent eye movement recognition analysis method is characterized by comprising the following steps:
s1, setting reading test questions based on education levels;
s2, selecting the corresponding reading test questions according to the education level of the target to be tested, performing reading test, and collecting voice information, reading time information and eye movement information of the target to be tested in the reading process;
s3, based on the reading test questions, identifying the voice information to obtain reading correct information and reading error information of the target to be detected;
s4, obtaining average speech speed information of the target to be detected through the reading duration information based on the character scale of the reading test question;
s5, setting the average speech speed information as a threshold value, identifying the inter-character reading speed of the target to be detected, and constructing a reading quality evaluation model of the target to be detected based on the reading correct information and the reading error information;
and S6, based on the reading quality evaluation model, establishing an eye movement information evaluation model through the eye movement information corresponding to the reading evaluation model, wherein the eye movement information evaluation model is used for evaluating the eye movement condition of the target to be measured.
2. The intelligent eye movement recognition analysis method of claim 1,
the length of the reading test question is at most 300 words;
the content of the reading test questions is divided into preschool age, primary school, junior high school, high school and university according to the education level;
the content includes, but is not limited to, images, numbers, Chinese characters, foreign languages.
3. The intelligent eye movement recognition analysis method of claim 1,
the step S3 further includes obtaining a correctness of the target to be measured according to the correctness information.
4. The intelligent eye movement recognition analysis method of claim 3,
the S4 further includes determining the average speech rate information based on the correct rate, and if the correct rate is greater than or equal to 85%, executing the S5, otherwise executing S2.
5. The intelligent eye movement recognition analysis method of claim 3,
the S5 further includes adding the reading correct information corresponding to the speech rate information to the reading incorrect information when the speech rate information corresponding to the reading correct information is smaller than the threshold value, and constructing a reading evaluation model of the target to be measured.
6. The intelligent eye movement recognition analysis method of claim 1,
the eye movement information includes, but is not limited to, eye saccades, eye fixations and eye returns.
7. The intelligent eye movement recognition analysis method of claim 1,
the S4 further includes that when the average speech rate information is lower or higher than the normal reading level, the target to be detected has problems, including but not limited to learning difficulties such as reading disorder, eye diseases, lack of knowledge level, and inattention;
the reading normal level is an interval value obtained by detecting the reading speeds of a plurality of persons with normal vision.
8. An intelligent eye movement recognition analysis system according to any one of claims 1 to 7, comprising
The intelligent testing system comprises intelligent glasses and an intelligent testing terminal connected with the intelligent glasses;
the intelligent glasses comprise glasses and a glasses intelligent control system arranged on the glasses, wherein the glasses intelligent control system comprises,
an image acquisition device arranged at one end of the glasses frame of the glasses,
a first communication module disposed at a front end or a rear end of the temples of the glasses,
a voice input device arranged at one side of the glasses legs,
the voice receiving device is arranged at one end of the glasses leg close to the ear of the person,
the control system module is arranged at one end of the glasses leg close to the glasses frame and is respectively connected with the image acquisition device, the first communication module, the voice input device and the voice receiving device,
the first power management module is used for supplying power to the intelligent glasses;
the intelligent test terminal comprises
A display module for displaying the reading test questions and selecting the corresponding reading test questions to test according to the requirement,
a display module control system connected with the display module and including a circuit board,
and a chip integrated on the circuit board,
the storage module is connected with the chip and used for storing the data information generated by the intelligent test terminal;
a second communication module connected with the chip and used for connecting the intelligent control system of the glasses,
a voice recognition module connected with the chip and used for recognizing the voice information of the intelligent control system of the glasses,
an image recognition module connected with the chip and used for collecting the eye movement information,
and the second power management module is arranged at one end of the intelligent test terminal and used for supplying power to the intelligent test terminal.
9. The intelligent eye movement recognition analysis system of claim 8,
the first communication module and the second communication module are wireless transmission modules;
the wireless transmission module comprises but is not limited to a Bluetooth module and a Wifi module;
the first communication module is arranged on one side, far away from the control system, of the front end of the glasses leg;
the intelligent glasses are further connected with a mobile terminal through the first communication module;
the mobile terminal includes but is not limited to a mobile phone and a tablet computer.
10. The intelligent eye movement recognition analysis system of claim 8,
the first communication module and the second communication module are wired transmission modules;
the wired transmission module includes, but is not limited to, a fiber optic module;
the first communication module is arranged at the rear end of the glasses leg;
the display module is a touch screen.
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| CN202110289185.2A CN112950609A (en) | 2021-03-13 | 2021-03-13 | Intelligent eye movement recognition analysis method and system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113712539A (en) * | 2021-08-31 | 2021-11-30 | 刘宏图 | Intelligent healthy glasses for children |
| CN113842113A (en) * | 2021-07-22 | 2021-12-28 | 陆烁 | Developing reading disorder intelligent identification method, system, equipment and storage medium |
| CN114468977A (en) * | 2022-01-21 | 2022-05-13 | 深圳市眼科医院 | Ophthalmologic vision examination data collection and analysis method, system and computer storage medium |
-
2021
- 2021-03-13 CN CN202110289185.2A patent/CN112950609A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113842113A (en) * | 2021-07-22 | 2021-12-28 | 陆烁 | Developing reading disorder intelligent identification method, system, equipment and storage medium |
| CN113712539A (en) * | 2021-08-31 | 2021-11-30 | 刘宏图 | Intelligent healthy glasses for children |
| CN113712539B (en) * | 2021-08-31 | 2023-11-14 | 刘宏图 | Intelligent healthy glasses for children |
| CN114468977A (en) * | 2022-01-21 | 2022-05-13 | 深圳市眼科医院 | Ophthalmologic vision examination data collection and analysis method, system and computer storage medium |
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