Precise and intelligent undergraduate depression early warning system based on physical and medical deep fusion

Abstract

The invention discloses a precise and intelligent undergraduate depression early warning system based on physical and medical deep fusion. The system comprises the steps of database construction, physical and medical fusion detection, database importing, manual analysis and intelligent early warning. The step of constructing the database comprises data acquisition, data entry, data management and data updating; the data acquisition unit is used for acquiring various body information of people not suffering from depression and people suffering from depression during physical activities and recording the data; the physical and medical fusion detection comprises physical exercises and fitness activities, and data of medical detection comprises but is not limited to brain waves, pulse waves and electrocardiowaves; the step of importing the database comprises the steps of firstly creating a new file in the database, then inputting the detected target information into the new file and forming a chart, and then importing the existing information of the database to obtain a comparison chart of the target information and the database information; and a doctor can conveniently perform final judgment and early warning on the target according to a conclusion given by the model and in combination with medical experience.

Description

Technical Field

[0001] The present invention relates to the technical field of depression early warning, and specifically to a precise intelligent early warning system for college students' depression based on deep integration of physical and medical sciences. Background Art

[0002] The integration of sports and medicine is to optimize the allocation of health resources, improve the efficiency of health services, and ultimately promote the improvement of the health level of the whole people through the integration and mutual coordination of resources between sports and medical and health systems.

[0003] College students may face problems in their studies, life, health and entering society, which can easily lead to psychological stress.

[0004] Physical activities can relieve psychological stress and improve health levels. When engaging in physical activities, it is extremely necessary to monitor human-related data through medical instruments and accurately and intelligently predict the target's level of depression. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above-mentioned and / or existing problems in the existing precise intelligent early warning system for college students' depression based on deep integration of physical and medical science, the present invention is proposed.

[0007] Therefore, the purpose of the present invention is to provide a precise intelligent early warning system for college students' depression based on the deep integration of physical education and medicine. When in use, the target is first equipped with medical detection equipment, and then the target is allowed to engage in physical activities, such as running, brisk walking, cycling, etc., and various physical information of the target during the physical activities, such as the changes in brain waves, pulse waves and electrocardiogram waves, are recorded, and then imported into a constructed database, and combined with the physical information of people without depression and people with depression in the database during the same physical activities, a comparative model is constructed, and the target's mental state is comprehensively analyzed based on the model and combined with the doctor's on-site mental state of the target, and the target's on-site mental state is input into the model as an aid, and then the model derives the target's depression intensity or the possibility that the target may suffer from depression. The doctor makes the final judgment and early warning on the target based on the conclusion given by the model and combined with medical experience.

[0008] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0009] A precise intelligent early warning system for college students' depression based on the deep integration of physical and medical sciences, comprising the following components in parts by weight:

[0010] It includes database construction, physical and medical integration detection, database import, manual analysis and intelligent early warning; the database construction includes data collection, data entry, data management and data update;

[0011] The data collection is used to collect various physical information of people who do not suffer from depression and people who suffer from depression during physical activities and record these data;

[0012] The physical and medical integration test includes sports and fitness activities, and the medical test data includes but is not limited to brain waves, pulse waves and electrocardiogram waves;

[0013] The step of importing the database is to first create a new file in the database, then input the detected target information into the new file and form a chart, and then import the existing information in the database to obtain a comparison chart of the target information and the database information; for example, a comparison model of the target brain wave and the brain wave changes of depression patients in the database during running on a treadmill at the same speed for the same time;

[0014] The manual analysis is that the doctor imports the detected target's physical information into the database, forms a comparison model with the database information, and comprehensively analyzes the target's mental state in combination with the target's mental state observed on site;

[0015] The intelligent early warning is used to issue an early warning report to a doctor to remind the target of the intensity of depression or the possibility that the target may suffer from depression.

[0016] As a preferred solution of the accurate intelligent early warning system for college students' depression based on deep integration of physical and medical science described in the present invention, the data update is used to update the database in real time. Whenever a target comes for detection, the physical information of the target is obtained by using the integration of physical and medical science, and the information is entered into the database to complete and improve the database.

[0017] As a preferred solution of the accurate intelligent early warning system for college students' depression based on deep integration of physical and medical care described in the present invention, the pulse wave data in the data collection and physical and medical detection data also includes the target's pulse wave data in resting state, deep breathing state and standing state.

[0018] As a preferred solution of the precise intelligent early warning system for college students' depression based on deep integration of physical and medical care described in the present invention, the resting state is the data of the target sitting quietly for five minutes and breathing naturally; the deep breathing state is the data of the target inhaling for 5 seconds and exhaling for 5 seconds, repeated 10 times; the standing state is the data of the target standing for 2 minutes.

[0019] As a preferred solution of the accurate intelligent early warning system for college students' depression based on deep integration of physical and medical science described in the present invention, the comparison model is trained by academic models such as RNN (recurrent neural network) and LSTM (long short-term memory network) to complete data-based depression classification and analysis.

[0020] As a preferred solution of the precise intelligent early warning system for college students' depression based on the deep integration of physical and medical science described in the present invention, the data collection and physical and medical detection data also include blood oxygen level dependence (Blood Oxygen Level Dependent), that is, BOLD signal; by analyzing the BOLD signal, we can explore the connection patterns between different areas of the brain, understand how information is transmitted and processed in the brain, and how these processes are affected by diseases or drugs. In the field of early warning of depression, we can use the BOLD signals of non-depressed people and depressed people, that is, the difference in information transmission in the target's brain during exercise as a basis to judge whether the target suffers from depression.

[0021] Compared with the prior art, the present invention has the following beneficial effects: when in use, the target is first put on a medical detection device, and then the target is allowed to engage in physical activities, such as running, brisk walking, cycling, etc., and various physical information of the target during the physical activities, such as the changes in brain waves, pulse waves and electrocardiogram waves, are recorded, and then imported into a database that has been constructed, and combined with the physical information of people without depression and people with depression in the database during the same physical activities, a comparative model is constructed, and the target's mental condition is comprehensively analyzed based on the model and combined with the doctor's on-site mental state of the target, and the target's on-site mental state is input into the model as an aid, and then the model derives the target's depression intensity or the possibility that the target may suffer from depression, and the doctor makes a final judgment and warning on the target based on the conclusion given by the model and combined with medical experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below in combination with the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0023] Figure 1 This is a flow chart of a precise intelligent early warning system for college students' depression based on deep integration of physical and medical sciences according to the present invention;

[0024] Figure 2 This is a flowchart of the database construction of a precise intelligent early warning system for college students' depression based on the deep integration of physical and medical sciences according to the present invention;

[0025] Figure 3 This is a flow chart of data collection for a precise intelligent early warning system for college students' depression based on deep integration of physical and medical sciences according to the present invention. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0027] Secondly, the present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0028] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0029] The present invention provides a precise intelligent early warning system for college students' depression based on the deep integration of physical education and medicine. When in use, the target is first given medical detection equipment, and then the target is allowed to engage in physical activities, such as running, brisk walking, cycling, etc., and various physical information of the target during the physical activities, such as the changes in brain waves, pulse waves and electrocardiogram waves, are recorded, and then imported into a constructed database, and a comparison model is constructed in combination with the physical information of people without depression and people with depression in the database during the same physical activities. The target's mental state is comprehensively analyzed based on the model and in combination with the doctor's on-site mental state of the target, and the target's on-site mental state is input into the model as an aid. Then the model derives the target's depression intensity or the possibility that the target may suffer from depression. The doctor makes a final judgment and early warning on the target based on the conclusion given by the model and in combination with medical experience.

[0030] Figure 1-Figure 3 The figure shows the overall structure of an embodiment of a precise intelligent early warning system for college students' depression based on deep integration of physical and medical sciences. Figure 1-Figure 3 , this implementation method is a precise intelligent early warning system for college students' depression based on the deep integration of physical and medical care:

[0031] It includes database construction, physical and medical integration testing, database import, manual analysis and intelligent early warning; database construction includes data collection, data entry, data management and data update;

[0032] Data collection is used to collect various physical information of people without depression and people with depression during physical activities and record these data;

[0033] Physical and medical integration testing includes sports and fitness activities, and the data of medical testing includes but is not limited to brain waves, pulse waves and heart waves;

[0034] The steps of importing the database are to first create a new file in the database, then input the detected target information into the new file and form a chart, and then import the existing information in the database to obtain a comparison chart of the target information and the database information; for example, during the same period of running on a treadmill at the same speed for the same time, a comparison model of the changes in the target brain waves and the brain waves of patients with depression in the database;

[0035] Manual analysis is when the doctor imports the detected target's physical information into the database, forms a comparison model with the database information, and comprehensively analyzes the target's mental state by combining it with the target's mental state observed on site;

[0036] Intelligent early warning is used to send early warning reports to doctors to remind the target of the intensity of depression or the possibility that the target may suffer from depression;

[0037] Among them, data update is used to update the database in real time. Whenever a target comes for detection, the target's physical information will be obtained by using the integration of physical and medical methods, and this information will be entered into the database to improve and perfect the database; the pulse wave data in the data collection and physical and medical detection data also includes the target's resting state, deep breathing state and standing state pulse wave data; the resting state is the data of the target sitting quietly for five minutes and breathing naturally; the deep breathing state is the data of the target inhaling for 5 seconds and exhaling for 5 seconds, repeated 10 times; the standing state is the data of the target standing for 2 minutes; the comparison model is trained by academic models such as RNN (recurrent neural network) and LSTM (long short-term memory network) to complete data-based depression classification and analysis; the data collection and physical and medical detection data also include blood oxygen level dependence (Blood Oxygen Level By analyzing the BOLD signal, we can explore the connection patterns between different brain areas, understand how information is transmitted and processed in the brain, and how these processes are affected by diseases or drugs. In the field of early warning of depression, we can use the BOLD signal of non-depressed and depressed people, that is, the difference in information transmission in the target's brain during exercise, as a basis to judge whether the target suffers from depression.

[0038] Combination Figure 1-Figure 3, this implementation method is a precise intelligent early warning system for college students' depression based on the deep integration of physical education and medicine. The specific use process is as follows: when in use, first make the target wear medical detection equipment, and then let the target perform physical activities, such as running, brisk walking, cycling, etc., and record various physical information of the target during the physical activities, such as the changes in brain waves, pulse waves and electrocardiogram waves, and then import them into the constructed database, and combine the physical information of people without depression and people with depression in the database during the same physical activities to build a comparison model, and comprehensively analyze the target's mental state based on the model and combined with the doctor's on-site mental state of the target, and input the target's on-site mental state into the model as an aid, and then the model derives the target's depression intensity or the possibility that the target may suffer from depression. The doctor makes the final judgment and early warning on the target based on the conclusion given by the model and combined with medical experience.

[0039] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A precise intelligent early warning system for college students' depression based on the deep integration of physical and medical sciences, characterized by: It includes database construction, physical and medical integration detection, database import, manual analysis and intelligent early warning; the database construction includes data collection, data entry, data management and data update; The data collection is used to collect various physical information of people who do not suffer from depression and people who suffer from depression during physical activities and record these data; The physical and medical integration test includes sports and fitness activities, and the medical test data includes but is not limited to brain waves, pulse waves and electrocardiogram waves; The step of importing the database is to first create a new file in the database, then input the detected target information into the new file and form a chart, and then import the existing information in the database to obtain a comparison chart of the target information and the database information; for example, a comparison model of the target brain wave and the brain wave changes of depression patients in the database during running on a treadmill at the same speed for the same time; The manual analysis is that the doctor imports the detected target's physical information into the database, forms a comparison model with the database information, and comprehensively analyzes the target's mental state in combination with the target's mental state observed on site; The intelligent early warning is used to issue an early warning report to a doctor to remind the target of the intensity of depression or the possibility that the target may suffer from depression.

2. According to claim 1, a precise intelligent early warning system for college students' depression based on deep integration of physical and medical care is characterized by: The data update is used to update the database in real time. Whenever a target comes for detection, the target's physical information will be obtained using the method of physical and medical integration, and the information will be entered into the database to complete and improve the database.

3. According to claim 1, a precise intelligent early warning system for college students' depression based on deep integration of physical and medical care is characterized by: The pulse wave data in the data collection and physical medical detection data also includes the pulse wave data of the target in a resting state, a deep breathing state and a standing state.

4. According to claim 3, a precise intelligent early warning system for college students' depression based on deep integration of physical and medical care is characterized in that: The resting state refers to the data when the target sits quietly for five minutes and breathes naturally; the deep breathing state refers to the data when the target inhales for 5 seconds and exhales for 5 seconds, repeated 10 times; and the standing state refers to the data when the target stands for 2 minutes.

5. According to claim 1, a precise intelligent early warning system for college students' depression based on deep integration of physical and medical care is characterized by: The comparison model is trained by RNN (recurrent neural network) and LSTM (long short-term memory network) academic models to complete data-based depression classification and analysis.

6. According to claim 1, a precise intelligent early warning system for college students' depression based on deep integration of physical and medical care is characterized by: The data collection and physical medical examination data also include blood oxygen level dependence (Blood Oxygen Level Dependent), that is, BOLD signal; by analyzing the BOLD signal, we can explore the connection patterns between different areas of the brain, understand how information is transmitted and processed in the brain, and how these processes are affected by diseases or drugs. In the field of early warning of depression, we can use the BOLD signals of non-depressed people and depressed people, that is, the difference in information transmission in the target's brain during exercise, as a basis to judge whether the target suffers from depression.

Images