Remote screening method and device for depressive symptoms, electronic equipment and storage medium

Abstract

The invention discloses a remote screening method and device for depressive symptoms, electronic equipment and a storage medium, the method and device are applied to the electronic equipment, and specifically, the method comprises the steps of receiving multi-modal data of a user in response to an information input request of the user; processing the multi-modal data by using a depressive symptom screening model to obtain depressive symptom grading information; the depression symptom grading information is fed back to the user. Therefore, the scheme does not need field evaluation and subjective judgment of doctors in the process of obtaining and feeding back the depressive symptom grading information, so that the evaluation basis is more objective and scientific, and the accuracy and objectivity of the evaluation result of the depressive symptom are improved.

Description

Technical Field

[0001] This application relates to the technical field of medical devices, and more particularly, to a remote screening method, device, electronic device, and storage medium for depressive symptoms. Background Art

[0002] In the traditional diagnosis process of mental diseases, doctors and psychological experts often rely on standardized scale assessments to identify and evaluate the psychological conditions of patients. However, this method has certain limitations because it largely depends on the self-report of patients, which may be affected by the patient's personal subjective will, such as social expectations, self-awareness, or misunderstandings of symptoms, etc., thus may lead to deviations or inaccuracies in the diagnosis results. In addition, scale assessments may not be able to comprehensively capture the patient's daily behavior patterns and mood fluctuations, which are important considerations in mental health assessments.

[0003] In the traditional assessment of depression treatment, the personal subjective feelings of psychological counselors and patients often play a core role. However, this subjective assessment method is easily interfered by various external factors, such as differences in the personal experience of psychological counselors, the patient's current mood fluctuations, etc., and these factors will weaken the accuracy and reliability of the assessment results. Summary of the Invention

[0004] In view of this, this application provides a remote screening method, device, electronic device, and storage medium for depressive symptoms, which are used to improve the accuracy and reliability of the assessment results of patients' depressive symptoms.

[0005] In order to achieve the above object, the following solutions are proposed:

[0006] A remote screening method for depressive symptoms, which is applied to an electronic device. The remote screening device includes the steps of:

[0007] Respond to the user's information input request and receive the user's multimodal data;

[0008] Use a depressive symptom screening model to process the multimodal data to obtain depressive symptom grading information;

[0009] Feedback the depressive symptom grading information to the user.

[0010] Optionally, the multimodal data includes video image data, audio data, and / or text data.

[0011] Optionally, the step of using a depressive symptom screening model to process the multimodal data to obtain depressive symptom grading information includes the steps of:

[0012] Preprocess the multimodal data to obtain data features;

[0013] Process the data features using the depression symptom screening model to obtain the depression symptom grading information.

[0014] Optionally, the feedback of the depression symptom grading information to the user includes the steps of:

[0015] Feedback the depression symptom grading information to the user in a visual manner, and is also used to feedback the multimodal data to the user.

[0016] A remote screening device for depression symptoms, which is applied to an electronic device. The remote screening device includes:

[0017] A data acquisition module, configured to receive the multimodal data of the user in response to the information input request of the user;

[0018] A data analysis module, configured to process the multimodal data using a depression symptom screening model to obtain depression symptom grading information;

[0019] An information feedback module, configured to feedback the depression symptom grading information to the user.

[0020] Optionally, the multimodal data includes video image data, audio data, and / or text data.

[0021] Optionally, the data analysis module includes:

[0022] A first processing unit, configured to preprocess the multimodal data to obtain data features;

[0023] A second processing unit, configured to process the data features using the depression symptom screening model to obtain the depression symptom grading information.

[0024] Optionally, the information feedback module is configured to feedback the depression symptom grading information to the user in a visual manner, and is also used to feedback the multimodal data to the user.

[0025] An electronic device, the electronic device includes at least one processor and a memory connected to the processor, wherein:

[0026] The memory is used to store computer programs or instructions;

[0027] The processor is used to execute the computer programs or instructions so that the electronic device implements the remote screening method as described above.

[0028] A computer-readable storage medium is applied to an electronic device. The storage medium carries one or more computer programs, and the one or more computer programs can be executed by the electronic device, so that the electronic device implements the remote screening method of the medical exercise prescription as described above.

[0029] As can be seen from the above technical solutions, the present application discloses a remote screening method, device, electronic device and storage medium for depressive symptoms. The method and device are applied to an electronic device. Specifically, in response to a user's information input request, multimodal data of the user is received; the multimodal data is processed by a depressive symptom screening model to obtain depressive symptom grading information; and the depressive symptom grading information is fed back to the user. It can be seen that in the process of obtaining and feeding back the depressive symptom grading information, this solution does not require on-site evaluation and subjective judgment of doctors. Therefore, the evaluation basis is more objective and scientific, thereby improving the accuracy and objectivity of the evaluation results of depressive symptoms. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0031] Figure 1 It is a flowchart of a remote screening method for depressive symptoms according to an embodiment of the present application;

[0032] Figure 2 It is a schematic diagram of data collection according to an embodiment of the present application;

[0033] Figure 3 It is a block diagram of a remote screening device for depressive symptoms according to an embodiment of the present application;

[0034] Figure 4 It is a functional schematic diagram of a data analysis module according to an embodiment of the present application;

[0035] Figure 5 It is a system overall architecture diagram of a generation device for a medical exercise prescription according to an embodiment of the present application;

[0036] Figure 6 It is a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0038] Figure 1 It is a flowchart of a remote screening method for depressive symptoms in an embodiment of the present application.

[0039] As Figure 1 shown, the remote screening method provided in this embodiment is applied to an electronic device for generating depressive symptom grading information. The electronic device can be understood as a computer, server or cloud platform with data computing and information processing capabilities. The method includes the following steps:

[0040] S1. Obtain multi-modal data of the user.

[0041] When the user sends an information input request based on the client of the system or a mobile device connected to the system, receive the multi-modal data input by the user. The multi-modal data includes but is not limited to video image data, audio data, and text data.

[0042] The multi-modal data includes but is not limited to some or all of body data, exercise habit data, and health status data. Body data includes height, weight, body fat percentage, heart rate, etc., exercise habit data includes exercise frequency, exercise duration, exercise type, etc., and health status data includes medical history, allergy history, etc.

[0043] In specific implementation, the user can input the above data by filling out a questionnaire through the client or mobile device. Or obtain the above multi-modal data through sensors or wearable devices configured on the user's body, or realize the acquisition of multi-modal data through the information collection program of the mobile device carried by the user, as Figure 2 shown.

[0044] S2. Process the multi-modal data using a depressive symptom screening model.

[0045] Specifically, after obtaining the above multi-modal data, use the depressive symptom screening model to model and analyze the multi-modal data, so as to obtain the depressive symptom grading information of the user. The specific process is as follows:

[0046] First, preprocess the multi-modal data to obtain data features.

[0047] Then, input the data features into the above-mentioned depression symptom screening model, so that the model outputs the depression symptom grading information based on the data features.

[0048] The depression symptom screening model here refers to a model trained based on a pre-constructed medical information data set.

[0049] S3. Feed back the depression symptom grading information to the user.

[0050] After obtaining the depression symptom grading information, feedback this information to the user in a visual way. When feedbacking the grading information, the above-mentioned multimodal data can also be fed back to the user so that the user can understand more information.

[0051] It can be seen from the above that the present application provides a remote screening method for depression symptoms. This method is applied to an electronic device. Specifically, in response to a user's information input request, it receives the user's multimodal data; uses a depression symptom screening model to process the multimodal data to obtain depression symptom grading information; and feeds back the depression symptom grading information to the user. It can be seen that in the process of obtaining and feeding back the depression symptom grading information, this solution does not require on-site evaluation and the subjective judgment of a doctor. Therefore, the evaluation basis is more objective and scientific, thereby improving the accuracy and objectivity of the evaluation results of depression symptoms.

[0052] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0053] Although the operations are depicted in a particular order, this should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous.

[0054] It should be understood that the various steps recited in the method embodiments of the present disclosure may be executed in a different order and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.

[0055] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include, but are not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the C language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.

[0056] Figure 3 It is a block diagram of a remote screening device for depressive symptoms according to an embodiment of the present application.

[0057] As Figure 3 shown, the remote screening device provided in this embodiment is applied to an electronic device for generating depressive symptom grading information. The electronic device may be understood as a computer, a server, or a cloud platform with data computing capabilities and information processing capabilities. The remote screening device includes a data acquisition module 10, a data analysis module 20, and an information feedback module 30.

[0058] The data acquisition module is used to obtain multi-modal data of the user.

[0059] When the user sends an information input request based on the client of the system or a mobile device connected to the system, the multi-modal data input by the user is received. The multi-modal data includes, but is not limited to, video image data, audio data, and text data.

[0060] The multi-modal data includes, but is not limited to, some or all of body data, exercise habit data, and health status data. Body data includes height, weight, body fat percentage, heart rate, etc. Exercise habit data includes exercise frequency, exercise duration, exercise type, etc. Health status data includes medical history, allergy history, etc.

[0061] In specific implementation, the user can input the questionnaire through the client or mobile device filling method to achieve the input of the above data. Or obtain the above multi-modal data through sensors or wearable devices configured on the user's body, or achieve the acquisition of multi-modal data through the information collection program of the mobile device carried by the user, such as Figure 2 as shown

[0062] The data analysis module is used to process the multi-modal data by using the depression symptom screening model.

[0063] Specifically, after obtaining the above multi-modal data, use the depression symptom screening model to model and analyze the multi-modal data, so as to obtain the depression symptom grading information of the user. The specific functions of this module are as Figure 4 shown. This module includes a first processing unit and a second processing unit.

[0064] The first processing unit is used to preprocess the multi-modal data to obtain data features.

[0065] The second processing unit is used to input the data features into the above depression symptom screening model, so that the model outputs the depression symptom grading information based on the data features.

[0066] The depression symptom screening model here refers to a model trained based on a pre-constructed medical information data set.

[0067] The information feedback module is used to feedback the depression symptom grading information to the user.

[0068] After obtaining the depression symptom grading information, feedback the information to the user in a visual way. When feedbacking the grading information, the above multi-modal data can also be feedbacked to the user so that the user can understand more information.

[0069] It can be seen from the above content that the present application provides a remote screening device for depression symptoms. This device is applied to an electronic device. Specifically, in response to the user's information input request, it receives the user's multi-modal data; uses the depression symptom screening model to process the multi-modal data to obtain the depression symptom grading information; and feedbacks the depression symptom grading information to the user. It can be seen that in the process of obtaining and feedbacking the depression symptom grading information, this solution does not require on-site evaluation and subjective judgment of doctors. Therefore, the evaluation basis is more objective and scientific, thus improving the accuracy and objectivity of the evaluation results of depression symptoms.

[0070] In addition, the overall architecture of this system is as Figure 5 shown.

[0071] The units involved in the embodiments of the present disclosure can be implemented in software or in hardware. Among them, the name of the unit does not constitute a limitation on the unit itself in some cases. For example, the first acquisition unit can also be described as "the unit for acquiring at least two Internet protocol addresses".

[0072] The functions described above in this article can be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), Application Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), and so on.

[0073] Figure 6 It is a block diagram of an electronic device according to an embodiment of the present application.

[0074] Reference is made below to Figure 6 , which shows a schematic structural diagram suitable for implementing the electronic device in the embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. This electronic device is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0075] The electronic device may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 1101, which can perform various appropriate actions and processes according to the program stored in the read-only memory ROM 1102 or the program loaded from the input device 1106 into the random access memory RAM 1103. In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other through the bus 1104. The input / output (I / O) interface 1105 is also connected to the bus 1104.

[0076] Typically, the following devices can be connected to the I / O interface: input devices including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 1107 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1108 including, for example, magnetic tapes, hard disks, etc.; and a communication device 1109. The communication device 1109 can allow the electronic device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows an electronic device having various devices, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices can be implemented or had.

[0077] This embodiment also provides an embodiment of a computer-readable storage medium.

[0078] The above computer-readable storage medium is applied to an electronic device and carries one or more computer programs. When the above one or more computer programs are executed by the electronic device, the electronic device responds to a user's information input request, receives the user's multimodal data; processes the multimodal data using a depression symptom screening model to obtain depression symptom grading information; and feeds back the depression symptom grading information to the user. It can be seen from this that in the process of obtaining and feeding back the depression symptom grading information, this solution does not require on-site evaluation and subjective judgment by a doctor, so the evaluation basis is more objective and scientific, thereby improving the accuracy and objectivity of the evaluation results of depression symptoms..

[0079] It should be noted that the above computer-readable medium of the present disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0080] In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

[0081] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same or similar parts among the various embodiments, reference may be made to each other.

[0082] Although the preferred embodiments of the embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0083] Finally, it should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such a process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or terminal device comprising the said element.

[0084] The above has introduced the technical solution provided by the present invention in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A remote screening method for depressive symptoms, applied to electronic equipment, characterized in that: The remote screening device comprises the steps of: Responding to a user's information input request, receiving the user's multimodal data; Processing the multimodal data using a depression symptom screening model to obtain depression symptom grading information; The depression symptom classification information is fed back to the user.

2. The remote screening method according to claim 1, characterized in that: The multimodal data includes video image data, audio data and / or text data.

3. The remote screening method according to claim 1, characterized in that: The method of processing the multimodal data using a depression symptom screening model to obtain depression symptom grading information comprises the steps of: Preprocessing the multimodal data to obtain data features; The data features are processed using the depression symptom screening model to obtain the depression symptom grading information.

4. The remote screening method according to claim 1, characterized in that: The step of feeding back the depressive symptom classification information to the user comprises the steps of: The depressive symptom grading information is fed back to the user in a visual manner, and is also used to feed back the multimodal data to the user.

5. A remote screening device for depression symptoms, applied to electronic equipment, characterized in that: The remote screening device comprises: The data collection module is configured to respond to the user's information input request and receive the user's multimodal data; A data analysis module is configured to process the multimodal data using a depression symptom screening model to obtain depression symptom grading information; The information feedback module is configured to feed back the depressive symptom classification information to the user.

6. The remote screening device according to claim 5, characterized in that: The multimodal data includes video image data, audio data and / or text data.

7. The remote screening device according to claim 5, characterized in that: The data analysis module includes: A first processing unit is configured to preprocess the multimodal data to obtain data features; The second processing unit is configured to process the data features using the depression symptom screening model to obtain the depression symptom grading information.

8. The remote screening device according to claim 5, characterized in that: The information feedback module is configured to provide feedback of the depressive symptom grading information to the user in a visual manner, and is also configured to provide feedback of the multimodal data to the user.

9. An electronic device, characterized in that: The electronic device comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs or instructions; The processor is used to execute the computer program or instruction so that the electronic device implements the remote screening method as described in any one of claims 1 to 4.

10. A computer-readable storage medium, applied to an electronic device, characterized in that: The storage medium carries one or more computer programs, and the one or more computer programs can be executed by the electronic device, so that the electronic device implements the remote screening method for medical exercise prescription as described in any one of claims 1 to 4.

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