CN113674857B - Television-assisted disease diagnosis device and system - Google Patents

Abstract

The present invention belongs to the technical field of smart TVs, and discloses a TV-assisted disease diagnosis device and system. The device implements the following steps: obtaining user health information; sending a voice input command to the user according to the user health information, so that the user can feedback a number of descriptive voices; querying the first target information of the user's disease according to the descriptive voice; sending a gesture self-diagnosis command to the user, so that the user can feedback gesture information; querying the second target information of the user's disease according to the gesture information and the first target information; generating an analysis report according to the second target information, and displaying the analysis report to the user. In the above manner, by determining the second target information of the user's disease according to the voice information and gesture information fed back by the user, and finally generating an analysis report according to the second target information, and displaying it to the user, the user can understand his or her own symptom information and the diagnosis and treatment information related to the symptom, and realize the diagnosis of the disease assisted by TV, making the diagnosis and treatment of the disease more convenient and quick.

Description

Television-assisted disease diagnosis device and system

Technical Field

The present invention relates to the technical field of smart televisions, and in particular to a television-assisted disease diagnosis device and system.

Background technique

Medical and health issues have always been major livelihood issues that concern the vital interests of the people.

In the past, when people felt unwell, they usually had two options: 1. Go to the hospital for face-to-face consultation. Due to the large number of patients, doctors could not explain the disease conditions one by one, and some professional medical terms could not be accurately understood, resulting in cognitive bias. 2. Some patients did not pay enough attention to their diseases, and often bought some medicine based on their symptoms and experience to deal with the problem. This would cause minor illnesses to develop into major illnesses, delaying the best treatment period.

The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art.

Summary of the invention

The main purpose of the present invention is to provide a television-assisted disease diagnosis device and system, aiming to solve the technical problem that the prior art is not convenient for diagnosing and treating diseases.

To achieve the above object, the present invention provides a television-assisted disease diagnosis device, characterized in that the television-assisted disease diagnosis device comprises: a memory, a processor, and a television-assisted disease diagnosis program stored in the memory and executable on the processor, wherein the television-assisted disease diagnosis program is configured to implement the following steps:

Obtain user health information;

Sending a voice input instruction to the user according to the user health information, so that the user can feedback several descriptive voices;

querying the first target information of the user's disease according to the description voice;

Sending a gesture self-diagnosis instruction to the user, so that the user can feedback gesture information;

querying second target information of the user's disease according to the gesture information and the first target information;

Generate an analysis report based on the second target information, and display the analysis report to the user.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

Recognize the first face information of the user through an AI camera;

Comparing the first facial information with the stored facial information to obtain a first comparison result;

When the first comparison result is that the first facial information is not stored in the stored facial information, a profile setting page is displayed to the user so that the user can provide personal information, and user health information is generated based on the personal information;

When the first comparison result is that the first facial information is recognized to be stored in the stored facial information, the user health information corresponding to the first facial information is queried.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

Obtaining a number of symptom description voices according to the description voices;

According to the symptom description voice query preset disease knowledge base, to obtain a number of query results;

Obtaining a first target disease according to the plurality of query results;

The preset disease knowledge base is queried according to the first target symptom to obtain first target information.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

Obtain body bone point information through AI camera;

Performing body position recognition according to the body skeleton point information and the gesture information to obtain symptom position recognition information;

The second target information of the user's disease is queried based on the symptom location identification information and the first target information.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

According to the symptom location identification information, a preset disease knowledge base is searched to obtain a second target disease;

Comparing the second target disease with the first target information to obtain overlapping target diseases;

The preset disease knowledge base is queried according to the overlapping target symptoms to obtain second target information.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

When the second target disease belongs to a preset disease, displaying a preset action video to the user so that the user can complete the preset action;

Acquire an action detection video of the user completing the preset action;

Comparing the motion detection video with a preset comparison video to obtain a motion comparison result;

Obtaining action completion information according to the action comparison result;

querying the preset disease knowledge base according to the action completion information to obtain a third target disease;

According to the third target symptom, the preset disease knowledge base is searched to obtain third target information;

The third target information is displayed to the user.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

When receiving an online diagnosis and treatment instruction, the analysis report is sent to a target terminal so that the target terminal displays it;

Acquire real-time image information and real-time voice information of the user through an AI camera in real time;

Sending the real-time image information and the real-time voice information to the target terminal, and receiving the doctor's image information and the doctor's voice information from the target terminal;

When the diagnosis and treatment information fed back by the target terminal is received, a drug purchase page is displayed to the user based on the diagnosis and treatment information, so that the user can purchase drugs based on the drug purchase page.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

When receiving a healthcare recommendation instruction, obtaining second facial information of the user;

Comparing the second facial information with the stored facial information to obtain a second comparison result;

Generate health care recommendation information according to the second comparison result and display it to the user.

Optionally, the television-assisted disease diagnosis program is configured to implement the following steps:

When the second comparison result is that the second facial information is recognized to be stored in the stored facial information, querying the user health information corresponding to the second facial information, and using the user health information corresponding to the second facial information as the user health care information;

querying a preset health care knowledge base according to the user health care information to obtain health care recommendation information;

The healthcare recommendation information is displayed to the user.

In addition, to achieve the above-mentioned purpose, the present invention also proposes a TV-assisted disease diagnosis system, which includes: an acquisition module, a voice module, a recognition module, a gesture module, a query module and an analysis module:

The acquisition module is used to obtain user health information;

A voice module, used for sending a voice input instruction to the user according to the user's medical record information, so that the user can feedback a number of descriptive voices;

A recognition module, used for querying first target information of a user's disease according to the description voice;

A gesture module, used for sending a gesture self-diagnosis instruction to the user, so that the user can feedback gesture information;

a query module, configured to query second target information of the user's disease according to the gesture information and the first target information;

An analysis module is used to generate an analysis report based on the second target information and display the analysis report to the user.

The present invention obtains user health information; sends a voice input instruction to the user according to the user health information, so that the user feeds back a number of descriptive voices; queries the first target information of the user's disease according to the descriptive voice; sends a gesture self-diagnosis instruction to the user, so that the user feeds back gesture information; queries the second target information of the user's disease according to the gesture information and the first target information; generates an analysis report according to the second target information, and displays the analysis report to the user. In this way, by obtaining the user's health information, and then querying the first target information of the user's disease according to the user's voice input, and then determining the second target information of the user's disease according to the gesture information and the first target information fed back by the user, and finally generating an analysis report according to the second target information, and displaying the analysis report to the user, the user can understand his or her own disease information and the diagnosis and treatment information related to the disease, so as to realize the diagnosis of the disease assisted by television, making the diagnosis and treatment of the disease more convenient and quick.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the structure of a television-assisted disease diagnosis device in a hardware operating environment according to an embodiment of the present invention;

FIG2 is a schematic diagram of a flow chart of a first embodiment of a television-assisted disease diagnosis device according to the present invention;

FIG3 is a schematic diagram of body skeleton points of an embodiment of a television-assisted disease diagnosis device of the present invention;

FIG4 is a schematic diagram of a flow chart of a second embodiment of a television-assisted disease diagnosis device according to the present invention;

FIG. 5 is a structural block diagram of the first embodiment of the television-assisted disease diagnosis system of the present invention.

The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

Refer to Figure 1, which is a schematic diagram of the structure of a television-assisted disease diagnosis device in a hardware operating environment according to an embodiment of the present invention.

As shown in FIG1 , the TV-assisted disease diagnosis device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

Those skilled in the art will appreciate that the structure shown in FIG. 1 does not constitute a limitation on the television-assisted disease diagnosis device, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

As shown in FIG. 1 , the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a television-assisted disease diagnosis program.

In the television-assisted disease diagnosis device shown in Figure 1, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the television-assisted disease diagnosis device of the present invention can be set in the television-assisted disease diagnosis device, and the television-assisted disease diagnosis device calls the television-assisted disease diagnosis program stored in the memory 1005 through the processor 1001.

An embodiment of the present invention provides a television-assisted disease diagnosis device. Referring to FIG. 2 , FIG. 2 is a flow chart of a first embodiment of a television-assisted disease diagnosis device of the present invention.

In this embodiment, the television-assisted disease diagnosis device includes: a memory, a processor, and a television-assisted disease diagnosis program stored in the memory and executable on the processor, wherein the television-assisted disease diagnosis program is configured to implement the following steps:

Step S10: Obtain user health information.

It should be noted that the user health information includes the user's personal information, such as name, age, gender, etc., and also includes the user's medical history information, such as the user's medical history, diagnosis records on the TV-assisted disease diagnosis device, doctor's advice, etc., and may also include other information related to the user's health, which is not limited in this embodiment.

Further, in order to obtain user health information, step S10 includes: identifying the first facial information of the user through an AI camera; comparing the first facial information with the stored facial information to obtain a first comparison result; when the first comparison result is that the first facial information is not stored in the stored facial information, displaying a profile setting page to the user so that the user can feedback personal information and generate user health information based on the personal information; when the first comparison result is that the first facial information is stored in the stored facial information, querying the user health information corresponding to the first facial information.

It should be understood that the first facial information refers to the facial image information used to identify the user's identity when obtaining the user's health information.

In a specific implementation, identifying the first facial information of the user through an AI camera means capturing the facial image information of the user through the AI camera as the first facial information.

It should be noted that the stored facial information refers to the facial information pre-stored for comparison with the first facial information. The stored facial information contains all the stored first facial information, and whenever there is new first facial information, the stored facial information will be updated and the newly obtained first facial information will be stored.

It should be understood that the first comparison result refers to the comparison of the first facial information with all facial information stored in the stored facial information, and the final comparison result is taken as the first comparison result.

In a specific implementation, when the first comparison result is that the first facial information is not recognized in the stored facial information, a data setting page is displayed to the user so that the user can provide feedback on personal information, and user health information is generated based on the personal information. This means that when the first comparison result is that the stored facial information does not contain a face identical to the first facial information, it is determined that the current user is using the device for the first time, and then a data display page is displayed to the user through the TV display screen. The current user can fill in personal information on the data setting page, and then after the user's personal information is obtained, the user health information is generated based on the personal information.

It should be noted that the information setting page contains several blank areas for users to fill in personal information, where the personal information may include personal information such as name, height, weight, gender, medical history, or other personal information related to the user, and this embodiment does not limit this.

It should be understood that when the first comparison result is that the first facial information is recognized to be stored in the stored facial information, querying the user health information corresponding to the first facial information means that when the first comparison result is that a face identical to the first facial information is stored in the stored facial information, it is determined that the current user has used it before, and the user health information corresponding to the first facial information is directly queried in the storage.

In a specific implementation, whenever user health information is generated, the user health information and the first facial information are stored in correspondence, so as to automatically query the user health information of the user corresponding to the first facial information based on the first facial information.

In this way, first-time users can quickly establish user health information, and non-first-time users can quickly query previously stored user health information. There is no need to regenerate user health information each time use, and previous diagnosis history can be queried at any time, making the TV-assisted disease diagnosis device more convenient and quick to use.

Step S20: Sending a voice input instruction to the user according to the user health information, so that the user can feedback a number of descriptive voices.

It should be noted that the voice input command refers to a command sent to the user, which is used to allow the user to feedback voice information describing the user's physical symptoms. After the user receives the voice input command, he or she can feedback the descriptive voice to the smart TV.

It should be understood that the descriptive voice refers to the voice information in which the user describes his or her own symptoms.

Step S30: Query the first target information of the user's disease according to the descriptive voice.

In a specific implementation, the first target information refers to the user's first target disease and information such as the recommended medical department, the cause of the disease and the basic treatment method corresponding to the first target disease. It may also include other information related to the first target disease, which is not limited in this embodiment.

It should be noted that querying the first target information of the user's disease according to the description voice means obtaining the symptom description voice according to the description voice, then obtaining the first target disease according to the symptom description voice, and then obtaining the first target information according to the first target disease.

Furthermore, in order to accurately obtain the first target information, step S30 includes: obtaining a number of symptom description voices based on the description voices; querying a preset disease knowledge base based on the symptom description voices to obtain a number of query results; obtaining the first target symptom based on the number of query results; querying the preset disease knowledge base based on the first target symptom to obtain the first target information.

It should be understood that the symptom description voice refers to the voice related to the user's diseased part or symptoms, and the symptom description voice is screened out from the description voice.

In a specific implementation, obtaining a number of symptom description voices according to the description voice means that after obtaining the description voice, the description voice can be screened to remove useless voices, and finally a number of symptom description voices are obtained.

It should be noted that the preset disease knowledge base stores all existing disease knowledge, which may include information such as diseases, symptoms, causes, conventional treatment methods, recommended treatment departments, and may also include other knowledge about the disease, which is not limited in this embodiment.

It should be understood that the query result refers to the result obtained by querying each symptom description voice in the preset disease knowledge base, so in the end, several query results corresponding to the symptom description voice can be obtained.

In a specific implementation, querying a preset disease knowledge base according to the symptom description voice to obtain a number of query results means that after obtaining the symptom description voice, the text information in the symptom description voice is identified, and then the preset disease knowledge base is queried according to the text information to obtain the query results.

It should be noted that obtaining the first target disease according to the plurality of query results means summarizing the plurality of query results, wherein the disease having the same or similar symptoms as the query results is taken as the first target disease.

It should be understood that the first target disease can be one or more, and this embodiment does not limit this.

In a specific implementation, querying the preset disease knowledge base according to the first target disease to obtain the first target information means that after obtaining the first target disease, querying the preset disease knowledge base according to the first target disease to obtain relevant information such as the recommended treatment department, common treatment methods, symptoms, possible causes, or other information related to the first target disease, and this embodiment does not limit this, and stores the above information and the first target disease as the first target information.

In this way, the user's possible first target disease can be obtained by querying the preset disease knowledge base and the user's description voice-assisted diagnosis, making the diagnosis of the disease more convenient and quick.

Step S40: sending a gesture self-diagnosis instruction to the user, so that the user can feedback gesture information.

It should be noted that the gesture self-diagnosis instruction is an instruction that prompts the user to feedback gesture information. The gesture self-diagnosis instruction can be displayed to the user through the display screen of the TV, or can be prompted to feedback the gesture information to the user in other forms. This embodiment is not limited to this.

It should be understood that gesture information refers to the user's gestures obtained through the camera, and gesture information refers to the information obtained after the user makes a specific gesture to the uncomfortable part of the body. The specific gesture can be pre-set by the user or administrator, and this embodiment does not limit this.

Step S50: querying second target information of the user's disease according to the gesture information and the first target information.

In a specific implementation, the second target information refers to the user's symptom information further determined after screening and querying the first target information and the gesture information obtained by the user through the gesture action, as the second target information.

It should be noted that the second target information of querying the user's disease based on the gesture information and the first target information means that after receiving the feedback gesture information, the second target information is obtained based on the gesture information, the first target information and the preset disease knowledge base.

Furthermore, in order to accurately obtain the second target information, step S50 includes: obtaining body skeleton point information through an AI camera; performing body position recognition based on the body skeleton point information and the gesture information to obtain symptom position recognition information; and querying the second target information of the user's disease based on the symptom position recognition information and the first target information.

It should be understood that the body skeleton point information refers to the user standing in front of the AI camera, determining the user's body position from the image information obtained by the AI camera, and then determining the location of the user's skeleton points based on the user's body position and storing them as body skeleton points. Body skeleton points may include information such as joint points or important bone location points, which is not limited in this embodiment. A schematic diagram of body skeleton points is shown in Figure 3, and the points in the figure are all body skeleton points.

In a specific implementation, body position recognition is performed based on the body skeleton point information and the gesture information to obtain symptom position recognition information. This means that after the body skeleton point information is determined, the image area where the user's body discomfort part is located is determined based on the gesture information, and then the user's body part corresponding to the image area where the user's body discomfort part is located is determined based on the body skeleton point information, and the user's body part corresponding to the image area where the user's body discomfort part is located is stored as the symptom position recognition information.

It should be noted that querying the second target information of the user's disease based on the symptom location identification information and the first target information means querying the preset disease knowledge base based on the symptom location identification information to obtain the second target symptom, then comparing the second target symptom with the first target information to obtain the overlapping target symptom, and finally obtaining the second target information based on the overlapping target symptom.

In this way, the body bone point information and gesture information can be used to determine where the user's symptoms are located in the body, thereby determining the user's disease.

Furthermore, in order to accurately determine the second target information, the step of querying the second target information of the user's disease according to the symptom location identification information and the first target information includes: querying a preset disease knowledge base according to the symptom location identification information to obtain a second target symptom; comparing the second target symptom with the first target information to obtain an overlapping target symptom; and querying the preset disease knowledge base according to the overlapping target symptom to obtain the second target information.

It should be understood that querying the preset disease knowledge base according to the symptom location identification information to obtain the second target disease means querying the preset disease knowledge base according to the symptom location identification information to obtain the disease at the same location as the symptom location as the second target disease. The number of second target diseases can be any number, and this embodiment does not limit this.

In a specific implementation, comparing the second target symptom with the first target information to obtain overlapping target symptoms means comparing the second target symptom with the first target symptom in the first target information to obtain symptoms that both the second target symptom and the first target symptom have as overlapping target symptoms.

It should be noted that querying the preset disease knowledge base according to the overlapping target symptoms to obtain the second target information means that after determining the overlapping target symptoms, querying the preset disease knowledge base for relevant knowledge corresponding to the overlapping target symptoms, and storing the query results as the second target information.

In this way, it is possible to further determine and narrow down the types of diseases that the user may have and related information based on the user's gesture information, making TV-assisted disease diagnosis more accurate.

Step S60: Generate an analysis report based on the second target information, and display the analysis report to the user.

It should be understood that the analysis report refers to a report generated based on the second target information for display to the user. The form and format of the analysis report can be in any form, and this embodiment does not limit this.

In a specific implementation, generating an analysis report according to the second target information and displaying the analysis report to the user means that after the second target information is generated, an analysis report is generated according to the second target information, and then the analysis report is displayed to the user through the display screen of the TV.

It should be noted that after the analysis report is generated, it will be stored in the user's corresponding health information to continuously update the user's health information.

Furthermore, in order to further accurately identify the user's symptoms, after step S60, the following steps are further included:

When the second target symptom belongs to a preset symptom, a preset action video is displayed to the user so that the user can complete the preset action; an action detection video of the user completing the preset action is obtained; the action detection video is compared with a preset comparison video to obtain an action comparison result; action completion information is obtained according to the action comparison result; the preset disease knowledge base is queried according to the action completion information to obtain a third target symptom; the preset disease knowledge base is queried according to the third target symptom to obtain third target information; and the third target information is displayed to the user.

It should be noted that the preset disease refers to the disease type preset by the user or administrator, which may be a nervous system disease or a motor system disease, and this embodiment does not limit this.

It should be understood that when the second target disease belongs to the preset disease, displaying the preset action video to the user so that the user can complete the preset action means that when the second target disease belongs to the preset disease, the preset action video is displayed to the user through the display screen of the TV, and then the user can complete the preset action according to the actions in the preset action video.

In a specific implementation, the preset action video refers to a pre-stored video, which will display prompts for the user to imitate the preset action.

It should be noted that the preset action refers to a pre-stored action, which is preset and stored by a user or administrator. It can be any action and this embodiment does not limit this.

It should be understood that obtaining the action detection video of the user completing the preset action means that when the user completes the preset action, the video screen information of the user completing the preset action is obtained through the AI camera and stored as the action detection video.

In a specific implementation, comparing the action detection video with a preset comparison video to obtain an action comparison result means comparing the action detection video with a preset comparison video, and then determining the parts with action differences according to the user's skeletal point information, and finally summarizing and storing the parts with action differences as the action comparison result.

It should be noted that the preset comparison video refers to a pre-stored image video completed with the preset action standard.

It should be understood that obtaining the action completion information based on the action comparison result means obtaining the action completion information based on all parts with action differences and the degree of action differences.

In a specific implementation, querying the preset disease knowledge base according to the action completion information to obtain the third target symptom means querying the possible existing symptom corresponding to each part with action difference in the preset disease knowledge base according to the part with action difference in the action completion information, and then summarizing the possible existing symptom corresponding to each part with action difference as the third target symptom for storage.

It should be noted that querying the preset disease knowledge base according to the third target disease to obtain the third target information means that after the third target disease is determined, the preset disease knowledge base is queried according to the third target disease to query the disease, symptoms, causes, conventional treatment methods, recommended treatment departments and other information corresponding to the third target disease, and other knowledge related to the third target disease may also be included, which is not limited in this embodiment.

It should be understood that after the third target information is determined, the third target information is stored in the user health information corresponding to the user to update the user health information.

In this way, the user's motor or nervous system diseases can be judged by the degree of completion of the user's actions, which can further narrow and accurately identify the user's symptoms and improve the accuracy of TV-assisted disease diagnosis.

Furthermore, in order to assist users in online diagnosis and purchase of medicines, after step S60, it also includes: when an online diagnosis and treatment instruction is received, sending the analysis report to the target terminal so that the target terminal displays it; acquiring real-time image information and real-time voice information of the user through an AI camera in real time; sending the real-time image information and the real-time voice information to the target terminal, and receiving doctor image information and doctor voice information from the target terminal; when receiving diagnosis and treatment information fed back by the target terminal, displaying a medicine purchase page to the user according to the diagnosis and treatment information, so that the user can purchase medicine according to the medicine purchase page.

It should be noted that the online diagnosis and treatment instructions are instructions input by the user, which can be key information entered by the remote control, voice information, or other forms of instructions that can achieve this function.

It should be understood that the target terminal refers to the terminal corresponding to the doctor who is automatically matched and can provide online diagnosis and treatment, which can be an electronic device such as a mobile phone, laptop computer or tablet computer.

In a specific implementation, when an online diagnosis and treatment instruction is received, the analysis report is sent to the target terminal so that the target terminal displays it. This means that after receiving the online diagnosis and treatment instruction, an online diagnosis and treatment request is sent to the terminals of all doctors who can provide online diagnosis and treatment. After a successful match with a doctor, the terminal of the successfully matched doctor is used as the target terminal, and the analysis report is sent to the target terminal so that the target terminal displays the analysis report to the doctor.

It should be noted that the real-time image information and real-time voice information of the user are obtained in real time through the AI camera; the real-time image information and the real-time voice information are sent to the target terminal, and the doctor's image information and the doctor's voice information from the target terminal are received. This means that the TV collects the user's real-time image information and real-time voice information in real time and sends them to the target terminal, so that the target terminal displays the user's real-time image information and real-time voice information, and then the target terminal also collects the doctor's voice information and the doctor's image information in real time, and feeds them back to the TV, so that the TV displays them, and in this way, the real-time video and voice communication between the user and the doctor is completed.

It should be understood that diagnosis and treatment information refers to the diagnosis information, treatment methods and other information related to the user's condition entered by the doctor on the target terminal.

In a specific implementation, when the diagnosis and treatment information fed back by the target terminal is received, a drug purchase page is displayed to the user based on the diagnosis and treatment information, so that the user can purchase drugs based on the drug purchase page. This means that when the diagnosis and treatment information fed back by the target terminal is received, the purchase page of the relevant drugs is automatically searched and queried based on the information related to the therapeutic drugs in the diagnosis and treatment information, and is displayed to the user through a TV display screen, so that the user can purchase the drugs on the purchase page.

It should be noted that after the drug purchase page is displayed, the diagnosis and treatment information will be stored in the user's corresponding user health information to complete the update of the user's health information.

In this way, users can communicate with doctors online in real time to complete the diagnosis of the disease, and then provide a quick way to purchase medicines, so that users can complete the diagnosis of the disease without leaving home, which improves the convenience and professionalism of TV-assisted disease diagnosis.

This embodiment obtains user health information; sends a voice input instruction to the user according to the user health information, so that the user feeds back several descriptive voices; queries the first target information of the user's disease according to the descriptive voice; sends a gesture self-diagnosis instruction to the user, so that the user feeds back gesture information; queries the second target information of the user's disease according to the gesture information and the first target information; generates an analysis report according to the second target information, and displays the analysis report to the user. In this way, by obtaining the user health information, and then querying the first target information of the user's disease according to the user's voice input, and then determining the second target information of the user's disease according to the gesture information and the first target information fed back by the user, and finally generating an analysis report according to the second target information, and displaying the analysis report to the user, the user can understand his own disease information and the diagnosis and treatment information related to the disease, so as to realize the diagnosis of the disease assisted by television, making the diagnosis and treatment of the disease more convenient and quick.

Referring to Fig. 4, Fig. 4 is a flowchart of a second embodiment of a television-assisted disease diagnosis device according to the present invention.

Based on the first embodiment, the television-assisted disease diagnosis device of this embodiment further includes, after step S60:

Step S601: When a healthcare recommendation instruction is received, second facial information of the user is obtained.

It should be noted that the health care recommendation instruction is a trigger instruction for a user to obtain the second facial information of the user, and can be an instruction form input by the user in any form, and this embodiment does not impose any limitation on this.

It should be understood that when a healthcare recommendation instruction is received, obtaining the second facial information of the user means that after the healthcare recommendation instruction is received, the second facial information of the user at the current moment is obtained through the AI camera.

In a specific implementation, the second facial information refers to the facial image information of the user collected when the healthcare recommendation instruction is received.

It should be noted that comparing the second facial information with the stored facial information to obtain the second comparison result means comparing the second facial information with the stored facial information to query whether the user corresponding to the second facial information has stored user health information.

Step S602: Compare the second facial information with the stored facial information to obtain a second comparison result.

It should be understood that comparing the second facial information with the stored facial information to obtain a second comparison result means comparing the second facial information with the stored facial information to determine the second comparison result, and the second comparison result is divided into recognizing that the second facial information is stored in the stored facial information and not recognizing that the second facial information is stored in the stored facial information.

Step S603: Generate health care recommendation information according to the second comparison result, and display it to the user.

In a specific implementation, the health care recommendation information refers to the relevant information about the user's physical health that is queried based on the user's health care information by querying the preset health care knowledge base, for example: the user's daily diet recommendation, recommended daily life, and recommended daily exercise.

Further, in order to accurately recommend health care recommendation information, step S603 includes: when the second comparison result is to identify that the second facial information is stored in the stored facial information, query the user health information corresponding to the second facial information, and use the user health information corresponding to the second facial information as the user health care information; query a preset health care knowledge base according to the user health care information to obtain health care recommendation information; and display the health care recommendation information to the user.

It should be noted that, when the second comparison result is that the second facial information is recognized to be stored in the stored facial information, the user health information corresponding to the second facial information is queried, and the user health information corresponding to the second facial information is used as the user health information. This means that when the comparison result is that the user corresponding to the second facial information has user health information stored, the user health information corresponding to the second facial information is queried, and the user health information corresponding to the second facial information is stored as the user health information.

It should be understood that the preset health care knowledge base is a pre-stored knowledge base consisting of information such as daily life precautions and life conditioning tips corresponding to different diseases or sub-health problems. It can be set in advance by the user or administrator and adjusted at any time. This embodiment does not limit this.

In a specific implementation, querying a preset health care knowledge base according to the user health care information to obtain health care recommendation information means querying the preset health care knowledge base according to the user health care information for the health care information of the corresponding user's disease or body discomfort part, and using the health care information of the corresponding user's disease or body discomfort part in the preset health care knowledge base as the health care recommendation information.

In this way, when the user has stored user health information, the preset health care knowledge base can be queried to obtain health care recommendation information and display it to the user, thus realizing personalized and personal life health care tips and improving the user experience.

In this embodiment, when receiving a health care recommendation instruction, the second face information of the user is obtained; the second face information is compared with the stored face information to obtain a second comparison result; and health care recommendation information is generated according to the second comparison result and displayed to the user. In this way, the health care recommendation information of the user is queried according to the user's personal information in daily life, and then displayed to the user, so as to realize personalized management of the user's health and improve the user's experience.

In addition, an embodiment of the present invention further provides a memory having a television-assisted disease diagnosis program stored thereon, and when the television-assisted disease diagnosis program is executed by a processor, the steps implemented by the television-assisted disease diagnosis device as described above are implemented.

Since the present memory adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

5, FIG5 is a structural block diagram of a first embodiment of a television-assisted disease diagnosis system according to the present invention.

As shown in FIG5 , the TV-assisted disease diagnosis system proposed in the embodiment of the present invention includes: an acquisition module 10, a voice module 20, a recognition module 30, a gesture module 40, a query module 50 and an analysis module 60:

The acquisition module 10 is used to acquire user health information.

The voice module 20 is used to send a voice input instruction to the user according to the user's medical record information, so that the user can feedback a number of descriptive voices.

The recognition module 30 is used to query the first target information of the user's disease according to the description voice.

The gesture module 40 is used to send a gesture self-diagnosis instruction to the user so that the user can feedback gesture information.

The query module 50 is used to query the second target information of the user's disease based on the gesture information and the first target information.

The analysis module 60 is used to generate an analysis report based on the second target information and display the analysis report to the user.

It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

This embodiment obtains user health information; sends a voice input instruction to the user according to the user health information, so that the user feeds back several descriptive voices; queries the first target information of the user's disease according to the descriptive voice; sends a gesture self-diagnosis instruction to the user, so that the user feeds back gesture information; queries the second target information of the user's disease according to the gesture information and the first target information; generates an analysis report according to the second target information, and displays the analysis report to the user. In this way, by obtaining the user health information, and then querying the first target information of the user's disease according to the user's voice input, and then determining the second target information of the user's disease according to the gesture information and the first target information fed back by the user, and finally generating an analysis report according to the second target information, and displaying the analysis report to the user, the user can understand his own disease information and the diagnosis and treatment information related to the disease, so as to realize the diagnosis of the disease assisted by television, making the diagnosis and treatment of the disease more convenient and quick.

In this embodiment, the acquisition module 10 is further used to identify the first facial information of the user through the AI camera; compare the first facial information with the stored facial information to obtain a first comparison result; when the first comparison result is that the first facial information is not stored in the stored facial information, display a profile setting page to the user so that the user can feedback personal information and generate user health information based on the personal information; when the first comparison result is that the first facial information is stored in the stored facial information, query the user health information corresponding to the first facial information.

In this embodiment, the speech module 20 is further used to obtain a number of symptom description speech according to the description speech; query a preset disease knowledge base according to the symptom description speech to obtain a number of query results; obtain a first target symptom according to the number of query results; query the preset disease knowledge base according to the first target symptom to obtain first target information.

In this embodiment, the query module 50 is also used to obtain body bone point information through an AI camera; perform body position recognition based on the body bone point information and the gesture information to obtain symptom position recognition information; and query second target information of the user's disease based on the symptom position recognition information and the first target information.

In this embodiment, the query module 50 is further used to query a preset disease knowledge base according to the symptom location identification information to obtain a second target symptom; compare the second target symptom with the first target information to obtain an overlapping target symptom; and query the preset disease knowledge base according to the overlapping target symptom to obtain the second target information.

In this embodiment, the analysis module 60 is also used to display a preset action video to the user when the second target disease belongs to a preset disease, so that the user can complete the preset action; obtain an action detection video of the user completing the preset action; compare the action detection video with a preset comparison video to obtain an action comparison result; obtain action completion information based on the action comparison result; query the preset disease knowledge base based on the action completion information to obtain a third target disease; query the preset disease knowledge base based on the third target disease to obtain third target information; and display the third target information to the user.

In this embodiment, the analysis module 60 is also used to send the analysis report to the target terminal when receiving an online diagnosis and treatment instruction, so that the target terminal can display it; obtain the real-time image information and real-time voice information of the user through the AI camera in real time; send the real-time image information and the real-time voice information to the target terminal, and receive the doctor's image information and the doctor's voice information from the target terminal; when receiving the diagnosis and treatment information fed back by the target terminal, display the drug purchase page to the user according to the diagnosis and treatment information, so that the user can purchase the drug according to the drug purchase page.

In this embodiment, the analysis module 60 is further used to obtain the second facial information of the user when receiving a healthcare recommendation instruction; compare the second facial information with the stored facial information to obtain a second comparison result; generate healthcare recommendation information based on the second comparison result, and display it to the user.

In this embodiment, the analysis module 60 is also used to query the user health information corresponding to the second facial information when the second comparison result is to identify that the second facial information is stored in the stored facial information, and use the user health information corresponding to the second facial information as the user health information; query a preset health knowledge base according to the user health information to obtain health recommendation information; and display the health recommendation information to the user.

Since this system adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, those skilled in the art may select part or all of the workflows to achieve the purpose of the present embodiment according to actual needs, and no limitation is imposed here.

In addition, for technical details not described in detail in this embodiment, please refer to the television-assisted disease diagnosis device provided in any embodiment of the present invention, and will not be repeated here.

In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of more restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM)/RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims (9)

1. A television-assisted disease diagnosis device, characterized in that the television-assisted disease diagnosis device comprises: a memory, a processor, and a television-assisted disease diagnosis program stored in the memory and executable on the processor, wherein the television-assisted disease diagnosis program is configured to implement the following steps: Obtain user health information; Sending a voice input instruction to the user according to the user health information, so that the user can feedback a number of descriptive voices; Obtaining a number of symptom description voices according to the description voices; According to the symptom description voice query preset disease knowledge base, to obtain a number of query results; Obtaining a first target disease according to the plurality of query results; According to the first target disease, the preset disease knowledge base is searched to obtain first target information, wherein the first target information includes at least one of a recommended department for diagnosis, common treatment methods, symptoms, and possible causes of the first target disease; Sending a gesture self-diagnosis instruction to the user, so that the user can feedback gesture information; querying second target information of the user's disease according to the gesture information and the first target information; Generate an analysis report based on the second target information, and display the analysis report to the user. 2. The television-assisted disease diagnosis device according to claim 1, wherein the television-assisted disease diagnosis program is configured to implement the following steps: Recognize the first face information of the user through an AI camera; Comparing the first facial information with the stored facial information to obtain a first comparison result; When the first comparison result is that the first facial information is not stored in the stored facial information, a profile setting page is displayed to the user so that the user can provide personal information, and user health information is generated according to the personal information; When the first comparison result is that the first facial information is recognized to be stored in the stored facial information, the user health information corresponding to the first facial information is queried. 3. The TV-assisted disease diagnosis device according to claim 1, wherein the TV-assisted disease diagnosis program is configured to implement the following steps: Obtain body bone point information through AI camera; Perform body position recognition based on the body skeleton point information and the gesture information to obtain symptom position recognition information; The second target information of the user's disease is queried according to the symptom location identification information and the first target information. 4. The TV-assisted disease diagnosis device according to claim 3, wherein the TV-assisted disease diagnosis program is configured to implement the following steps: According to the symptom location identification information, a preset disease knowledge base is searched to obtain a second target disease; Comparing the second target disease with the first target information to obtain overlapping target diseases; The preset disease knowledge base is queried according to the overlapping target symptoms to obtain second target information. 5. The TV-assisted disease diagnosis device according to claim 4, wherein the TV-assisted disease diagnosis program is configured to implement the following steps: When the second target disease belongs to a preset disease, displaying a preset action video to the user so that the user can complete the preset action; Acquire an action detection video of the user completing the preset action; Comparing the motion detection video with a preset comparison video to obtain a motion comparison result; Obtaining action completion information according to the action comparison result; querying the preset disease knowledge base according to the action completion information to obtain a third target disease; According to the third target symptom, the preset disease knowledge base is searched to obtain third target information; The third target information is displayed to the user. 6. The TV-assisted disease diagnosis device according to claim 1, wherein the TV-assisted disease diagnosis program is configured to implement the following steps: When receiving an online diagnosis and treatment instruction, sending the analysis report to a target terminal so that the target terminal can display it; Acquire real-time image information and real-time voice information of the user through an AI camera in real time; Sending the real-time image information and the real-time voice information to the target terminal, and receiving the doctor's image information and the doctor's voice information from the target terminal; When the diagnosis and treatment information fed back by the target terminal is received, a drug purchase page is displayed to the user according to the diagnosis and treatment information, so that the user can purchase drugs according to the drug purchase page. 7. The television-assisted disease diagnosis device according to any one of claims 1 to 6, characterized in that the television-assisted disease diagnosis program is configured to implement the following steps: When receiving a health care recommendation instruction, obtaining second facial information of the user; Comparing the second facial information with the stored facial information to obtain a second comparison result; Generate health care recommendation information according to the second comparison result and display it to the user. 8. The TV-assisted disease diagnosis apparatus according to claim 7, wherein the TV-assisted disease diagnosis program is configured to implement the following steps: When the second comparison result is that the second facial information is recognized to be stored in the stored facial information, querying the user health information corresponding to the second facial information, and using the user health information corresponding to the second facial information as the user health care information; querying a preset health care knowledge base according to the user health care information to obtain health care recommendation information; The healthcare recommendation information is displayed to the user. 9. A TV-assisted disease diagnosis system, characterized in that the TV-assisted disease diagnosis system comprises: an acquisition module, a voice module, a recognition module, a gesture module, a query module and an analysis module: The acquisition module is used to obtain user health information; A voice module, used for sending a voice input instruction to the user according to the user's medical record information, so that the user can feedback a number of descriptive voices; A recognition module is used to obtain a number of symptom description voices according to the description voices; query a preset disease knowledge base according to the symptom description voices to obtain a number of query results; obtain a first target symptom according to the number of query results; query the preset disease knowledge base according to the first target symptom to obtain first target information, wherein the first target information includes at least one of a recommended diagnosis department, common treatment methods, symptoms, and possible causes of the first target symptom; A gesture module, used for sending a gesture self-diagnosis instruction to the user, so that the user can feedback gesture information; A query module, used for querying second target information of the user's disease according to the gesture information and the first target information; An analysis module is used to generate an analysis report based on the second target information and present the analysis report to the user.