Dining interaction method based on intelligent sofa, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a dining interaction method based on an intelligent sofa, electronic equipment and a storage medium, and the method is applied to the intelligent sofa of a dining interaction system. The method comprises the following steps: when it is detected that a target user exists on the intelligent sofa and the target user wears physiological parameter monitoring equipment, sending the physiological parameter monitoring equipment to the intelligent sofa; monitoring a current value of a physiological parameter of the target user through the physiological parameter monitoring device, and collecting an image including a target dining behavior of the target user through the camera device; according to the current value of the physiological parameter and the image, whether the target dining behavior is a behavior enabling the value of the physiological parameter to exceed a corresponding target threshold value is judged, and a judgment result is obtained; when the judgment result indicates that the target dining behavior is the behavior enabling the value of the physiological parameter to exceed the corresponding target threshold value, prompt information is output, and dining safety and health are improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a dining interaction method, electronic device and storage medium based on a smart sofa. Background Art

[0002] In order to improve the dining experience of the elderly, some restaurants use smart sofas with height adjustment, temperature adjustment and massage functions as dining tables. However, in practice, it is found that the smart sofas used with dining tables cannot provide healthy dining tips to users based on the dishes on the table. For example, users with excessive blood sugar should not eat starchy potatoes, sweet potatoes, etc., or pumpkins and beets with high sugar content; users with high body fat rates should not eat foods with high fat content, etc. If the above dishes are on the table and the smart sofas in the restaurant cannot provide healthy dining tips to the user, it will have a bad impact on the user's health.

[0003] How to improve the safety and health of meals during the dining process is an urgent problem to be solved. Summary of the invention

[0004] The embodiments of the present application provide a dining interaction method, electronic device and storage medium based on a smart sofa, which can continuously monitor changes in the user's physiological parameters in combination with dining behavior, thereby improving the safety and health of dining.

[0005] In a first aspect, an embodiment of the present application provides a dining interaction method based on a smart sofa, which is applied to a smart sofa in a dining interaction system. The system further includes a camera and a physiological parameter monitoring device. A communication connection is established between the smart sofa and the camera and the physiological parameter monitoring device. The method includes:

[0006] When it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, the current value of the physiological parameter of the target user is monitored by the physiological parameter monitoring device, and an image including the target dining behavior of the target user is captured by the camera device;

[0007] According to the current value of the physiological parameter and the image, determining whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value, and obtaining a determination result, wherein the target threshold value is associated with a standard value corresponding to the physiological parameter;

[0008] When the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold, a prompt message is output, where the prompt message is used to prompt the target user to terminate the target dining behavior.

[0009] In some embodiments, judging whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value based on the current value of the physiological parameter and the image, and obtaining a judgment result includes:

[0010] Obtaining a difference between a standard value corresponding to the physiological parameter and a current value of the physiological parameter;

[0011] When the difference is greater than zero, quantifying the influence value of the physiological parameter of the target dining behavior according to the image;

[0012] In the case where the influence value is greater than or equal to the difference value, a first judgment result is obtained, wherein the first judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value;

[0013] When the influence value is smaller than the difference value, a second judgment result is obtained, and the second judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

[0014] In some embodiments, quantifying the impact of the target dining behavior on the physiological parameter according to the image includes:

[0015] performing image recognition processing on the image, and when it is recognized that the target dining behavior is a food picking behavior or a food ordering behavior, recognizing from the image at least one size of food corresponding to the food picking behavior or the food ordering behavior;

[0016] Determining the content of the target component that affects the physiological parameter in the at least one food according to the size of the at least one food and the unit components of each food;

[0017] The influence value of the target dining behavior on the physiological parameter is determined according to the content of the target component and the mapping relationship between the preset component content and the influence value of the physiological parameter.

[0018] In some embodiments, the target threshold is a standard value corresponding to the physiological parameter.

[0019] In some embodiments, after obtaining the difference between the standard value corresponding to the physiological parameter and the current value of the physiological parameter, the method further includes:

[0020] When the difference is less than or equal to zero, identifying at least one food corresponding to the target dining behavior according to the image;

[0021] The judgment result is obtained according to whether the at least one food includes a target food, wherein the target food is a food whose influence value on the physiological parameter is greater than a preset influence threshold;

[0022] In a case where the at least one food includes the target food, a third judgment result is obtained, wherein the third judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value;

[0023] In the case that the target food is not included in the at least one food, a fourth judgment result is obtained, and the fourth judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

[0024] In some embodiments, before obtaining the judgment result based on whether the at least one food includes the target food, the method further includes:

[0025] Acquire at least one value range that is allowed when the value of the physiological parameter is greater than or equal to the standard value;

[0026] The target threshold is determined according to the target value interval described by the difference, and the target threshold is the upper limit value of the target value interval.

[0027] In some embodiments, the output prompt information includes:

[0028] Determining a target reminder level corresponding to the target threshold value according to the size of the target threshold value and a mapping relationship between a preset threshold range and a reminder level;

[0029] Outputting prompt information corresponding to the target reminder level.

[0030] The second aspect of the present application provides a dining interactive device based on a smart sofa, which is applied to a smart sofa in a dining interactive system. The system further includes a camera and a physiological parameter monitoring device. A communication connection is established between the smart sofa and the camera and the physiological parameter monitoring device, including:

[0031] Acquisition module: when it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, the current value of the physiological parameter of the target user is monitored by the physiological parameter monitoring device, and the image including the target dining behavior of the target user is captured by the camera device;

[0032] Processing module: judging whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value according to the current value of the physiological parameter and the image, and obtaining a judgment result, wherein the target threshold value is associated with a standard value corresponding to the physiological parameter;

[0033] Display module: when the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value, output prompt information, wherein the prompt information is used to prompt the target user to terminate the target dining behavior.

[0034] A third aspect of the present application provides an electronic device, including:

[0035] processor;

[0036] a memory for storing instructions executable by the processor;

[0037] Wherein, the processor is configured to execute the instructions to implement the dining interaction method as described in any one of the embodiments of the first aspect of the present application.

[0038] The fourth aspect embodiment of the present application provides a storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device can execute the dining interaction method as described in any one of the embodiments of the first aspect of the present application.

[0039] The technical solution provided by the embodiment of the present application includes at least the following beneficial effects:

[0040] The target user's dining behavior and physiological parameters are obtained by combining them through camera equipment and physiological parameter detection equipment. When it is determined that the target dining behavior is a behavior that makes the value of the physiological parameter exceed the corresponding target threshold, prompt information is output. By prompting the user to adjust his or her dining behavior in time, it helps to reduce health problems caused by unhealthy dining behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a diagram showing an example of the system structure of a dining interaction method based on a smart sofa proposed in an embodiment of the present application;

[0042] Figure 2 A schematic diagram of a dining interaction method based on a smart sofa proposed in an embodiment of the present application;

[0043] Figure 3 A flowchart of another dining interaction method based on a smart sofa proposed in an embodiment of the present application;

[0044] Figure 4A flowchart of another dining interaction method based on a smart sofa proposed in an embodiment of the present application;

[0045] Figure 5 A schematic diagram of a dining interaction method based on a smart sofa in an embodiment of the present application;

[0046] Figure 6 A schematic diagram of the structure of a smart sofa proposed in an embodiment of the present application;

[0047] Figure 7 This is a schematic diagram of the structure of another smart sofa proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0049] In order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. For example, the first instruction and the second instruction are to distinguish different user instructions, and their order is not limited. Those skilled in the art can understand that the words "first" and "second" do not limit the quantity and execution order, and the words "first" and "second" do not necessarily limit them to be different.

[0050] It should be noted that, in the embodiments of the present application, words such as "exemplarily" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present related concepts in a specific way.

[0051] In addition, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c, where a, b, c can be single or multiple.

[0052] It should be noted that in the embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0053] In today's society, with the continuous advancement of science and technology and people's pursuit of quality of life, smart home furniture is gradually becoming an indispensable part of our lives. Especially in the field of furniture, smart sofas, as an important part of smart homes, are attracting more and more attention for their research and development and innovation. Among them, smart sofas are not just a piece of furniture. By integrating advanced sensor technology, Internet of Things technology, big data analysis and artificial intelligence algorithms, they can bring users a more comfortable, convenient and personalized experience.

[0054] The core functions of the smart sofa mentioned in the related technology include height adjustment, temperature adjustment, massage function, etc. These functions can be adjusted according to the different needs and physical conditions of users. For example, through the built-in sensor, the smart sofa can detect the user's weight and sitting posture, and automatically adjust the sofa's tilt angle and hardness to suit the user's comfort. In addition, the smart sofa can also provide users with a suitable sitting and lying environment through the temperature adjustment function, especially in the cold winter, this function is particularly important.

[0055] However, existing smart sofa products often lack real-time monitoring and interactive functions with the user's health status. Especially for the special group of elderly people, their health status needs more attention and care. For example, elderly people with excessive blood sugar need to pay special attention to their diet and avoid high-starch and high-sugar foods; elderly people with high body fat percentage should not eat foods with high fat content, etc. However, existing smart sofas cannot provide healthy dining tips to the elderly based on the dishes on the table, which is undoubtedly a problem that needs to be solved urgently.

[0056] Based on this, the embodiment of the present application proposes a dining interaction method based on a smart sofa, an electronic device and a storage medium, which is applied to a smart sofa in a dining interaction system. The system also includes a camera device and a physiological parameter monitoring device. The physiological parameter monitoring device is used to monitor at least one of blood sugar, body fat rate and body mass index BMI. A communication connection is established between the smart sofa and the camera device and the physiological parameter monitoring device. When it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, the current value of the physiological parameter of the target user is monitored by the physiological parameter monitoring device, and an image including the target dining behavior of the target user is captured by the camera device.

[0057] Based on the current value of the physiological parameter and the image, determine whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold, and obtain a judgment result, wherein the target threshold is associated with the standard value corresponding to the physiological parameter; when the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold, output a prompt message, wherein the prompt message is used to prompt the target user to terminate the target dining behavior.

[0058] The embodiment of the present application integrates a physiological parameter monitoring bracelet, a smart sofa and a camera device to monitor the user's physiological health parameters in real time, and promptly reminds the user to avoid eating foods that may cause blood sugar to further increase when it is detected that the physiological health parameters exceed the standard, thereby effectively helping to control the physiological parameters to maintain normal, thereby improving the safety and health of dining.

[0059] For example, in the embodiment of the present application, the proposed dining interaction method based on the smart sofa involves a dining interaction system integrating multiple smart devices, such as Figure 1 As shown, the dining interactive system includes: a smart sofa 101, a camera device 102, and a physiological parameter monitoring device 103. The following are the working principles and functions of each component of the system:

[0060] Smart Sofa 101: Smart sofa is a seat for users to dine, which integrates the function of interacting with users. Smart sofa can provide dining feedback to users by receiving image information sent by camera equipment and physiological parameter information of physiological parameter detection equipment and processing the above information.

[0061] After the system analyzes the data collected by the camera and physiological parameter monitoring equipment, the smart sofa can take actions according to the system's instructions. For example, if the system determines that the user's diet may cause blood sugar to rise, the smart sofa can warn the user through the built-in display or sound system, or automatically adjust the shape of the sofa to remind the user to pay attention.

[0062] Camera device 102, when the user sits on the smart sofa to eat, the camera device will automatically start, capture the user's dining behavior in real time to determine whether the user's dining behavior will cause health problems, and the camera device is responsible for capturing and recording the user's behavior during the meal. This includes the food selected by the user, the action of picking up the food, and the amount of food, etc. The camera device can be a camera installed on the smart sofa, or it can be installed directly above the smart sofa, or a camera device at other locations around the smart sofa in the restaurant. As long as the target user's dining behavior is within the range that the camera can identify, the specific location is not limited.

[0063] It should be understood that the photo-taking behavior of the camera device is completed with the user's permission.

[0064] Physiological parameter monitoring device 103: After the user sits on the smart sofa, he / she wears the physiological parameter monitoring device before preparing to eat. The physiological parameter detection device is connected to the smart sofa by wire, and the device continuously monitors the user's physiological state. The monitored data will be sent to the system in real time so as to be combined with the user's dining behavior data for comprehensive analysis.

[0065] For example, physiological parameter monitoring devices are used to monitor the user's physiological parameters in real time, such as blood sugar, body fat percentage, body mass index (BMI), etc. These devices can be wearable, such as smart bracelets, smart watches or other non-invasive health monitoring devices.

[0066] Figure 1 The dotted line in the figure indicates that a communication connection can be established between the two. For example, the smart sofa can establish a communication connection with the camera device to receive images containing user behavior information sent by the camera device; it can also establish a communication connection with the physiological monitoring device; the three devices work together to form the dining interactive system based on the smart sofa proposed in this application.

[0067] In summary, the embodiment of the present application collects the user's dining behavior and physiological state data through a camera device and a physiological parameter monitoring device, and then the system analyzes it to determine whether the user's behavior is healthy. If the system detects that the user's dining behavior may cause the physiological parameters to exceed the health threshold, the smart sofa will take corresponding measures, such as issuing a prompt message, to guide the user to change unhealthy eating habits. Such a system can help users better manage their diet and health, especially for people who need to pay special attention to diet control, such as diabetics or obese patients.

[0068] After understanding the construction of the dining interaction system, the next step is to execute the dining interaction method based on the smart sofa proposed in the embodiment of the present application under this system. The steps of the method are explained in detail below.

[0069] Exemplarily, the method steps of the embodiment of the present application are as follows:

[0070] Step 201: monitoring the current value of the physiological parameter of the target user through the physiological parameter monitoring device, and capturing an image including the target dining behavior of the target user through the camera device;

[0071] When the system detects that a user is sitting on the smart sofa and the user is wearing a physiological parameter monitoring device, the system will start two main data collection processes:

[0072] Through the physiological parameter monitoring device, the system begins to continuously monitor the user's physiological indicators. The physiological parameters may include key vital signs such as heart rate, blood pressure, and blood sugar level. These data can help the system assess the user's current physical condition and their likelihood of responding to the current diet.

[0073] At the same time, the camera device will be activated to record the user's dining behavior and take images of the user's current dining behavior. Among them, dining behavior includes the user's behavior of picking up food or ordering food. These visual information are very important for understanding the user's eating habits.

[0074] The collected data is then sent to a processing unit where it is analyzed by specially designed algorithms. Based on these analysis results, the system can respond accordingly.

[0075] Step 202: judging whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value based on the current value of the physiological parameter and the image, and obtaining a judgment result;

[0076] Wherein, the target threshold is associated with a standard value corresponding to the physiological parameter;

[0077] Exemplarily, if the physiological parameter is blood sugar, the standard value of the physiological parameter refers to the normal blood sugar range defined medically.

[0078] For example, the standard value of fasting blood sugar is usually 70-99 mg / dL, and the normal blood sugar value after a meal is between 140-180 mg / dL.

[0079] Target Threshold: This is a set limit above the normal blood sugar range. If the user's blood sugar exceeds this value, action may be needed to prevent health risks, and the standard range is included in the target threshold range.

[0080] For example, the system may set a target threshold value higher than the normal range, such as 180 mg / dL as the limit value of the target threshold range. When the user's blood sugar reaches or exceeds this value, it indicates that there may be a health risk and emergency measures need to be taken, such as sending an alarm through the smart sofa to remind the user to stop eating immediately.

[0081] The detailed judgment process in step 202 is as follows: Figure 3 or Figure 4 The detailed steps are as follows:

[0082] Step 301: Obtaining a difference between a standard value corresponding to the physiological parameter and a current value of the physiological parameter;

[0083] When the difference is greater than zero, executing step 302, quantifying the influence value of the physiological parameter of the target dining behavior according to the image;

[0084] The impact value refers to the impact of the user's dining behavior on the value of the physiological parameter. Next, the relationship between the impact value and the difference value is determined.

[0085] For example, the user's dining behavior is to pick up food with a high sugar content. The food with a high sugar content has a greater impact on the user's blood sugar, so the impact value will become larger. Then, the relationship between the impact value and the difference value is determined, that is, the impact value is compared with the difference value required for the user's current blood sugar to rise to the standard value.

[0086] The first case is Figure 3 As shown, when the influence value is greater than or equal to the difference value, a first judgment result is obtained, and the first judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value;

[0087] In this case, the target threshold is the standard value. The target threshold is a dangerous upper limit of blood sugar that is greater than the standard value. The standard value refers to the limit of the food with high sugar content when the user is healthy. When the food is less than the target threshold, for the sake of the user's health, when the sugar content of the food is too high and exceeds this standard value, a prompt message will be given to the user.

[0088] When the influence value is smaller than the difference value, a second judgment result is obtained, and the second judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

[0089] For example, taking blood sugar as an example, that is, when the blood sugar level of the user still does not exceed the standard value under the influence of the food eaten, then the judgment may not require a prompt, or the user may be given a signal that the current blood sugar level is normal, so as to reassure users who are worried that eating foods with high sugar content will cause high blood sugar level.

[0090] Then, taking blood sugar as an example, the difference between the standard value corresponding to the blood sugar and the current value of the blood sugar of the user is obtained; assuming that the standard value is 140 mg / dL, the current value of the blood sugar is 80 mg / dL, and the difference between the two is 60, then according to the case where the impact value of image quantization is greater than or equal to the difference, a first judgment result is obtained, and the first judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value;

[0091] In this example, the target threshold is the standard value.

[0092] The second case is that when the difference is less than or equal to zero, at least one food corresponding to the target dining behavior is identified according to the image;

[0093] For example, Figure 4 The method flow chart described above is for the second case.

[0094] Before obtaining the judgment result according to whether the at least one food includes the target food, obtaining at least one value range that is allowed when the value of the physiological parameter is greater than or equal to the standard value;

[0095] Because the user's physiological parameters in the second case are higher than the standard value, food cannot be used to set the target, so as to avoid a large change in the physiological parameters, which may affect the user's life and health. The target food is food that has a greater impact on physiological parameters, such as food that has a greater impact on blood sugar, cakes, desserts, etc.

[0096] The target threshold is determined according to the target value interval described by the difference, and the target threshold is the upper limit value of the target value interval.

[0097] Step 401: identifying at least one food corresponding to the target dining behavior according to the image; then obtaining the judgment result according to whether the at least one food includes a target food, wherein the target food is a food whose influence value on the physiological parameter is greater than a preset influence threshold;

[0098] In a case where the at least one food includes the target food, a third judgment result is obtained, wherein the third judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value;

[0099] The target threshold is a threshold higher than the standard value.

[0100] In the case that the target food is not included in the at least one food, a fourth judgment result is obtained, and the fourth judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

[0101] It should be understood that the method proposed in the embodiment of the present application needs to obtain the user's explicit consent before implementing any data collection and analysis.

[0102] Step 203: When the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold, output prompt information.

[0103] Output prompt information, determine the target reminder level corresponding to the target threshold according to the size of the target threshold and the mapping relationship between the preset threshold range and the reminder level; output prompt information corresponding to the target reminder level.

[0104] Exemplarily, in the first case, when the difference between the standard value corresponding to the physiological parameter and the current value of the physiological parameter is greater than zero, a first judgment result and a second judgment result are output. In the case of the first judgment result, it is necessary to remind the user that the blood sugar may rise, and recommend foods with lower sugar content to the user; in the case of the second judgment result, the user's dining behavior may not cause the user's blood sugar to be higher than the target threshold, so there is no need to terminate the reminder to the user to use the food, and the user can also be provided with a reminder of the blood sugar content.

[0105] In the case of the first judgment result, the prompt mode may be the first level;

[0106] In the case of the second judgment result, the user's blood pressure value range is within the normal range, and there is no need to remind the user of the dining behavior. The nutritional components of the food selected by the user can be listed in a targeted manner, and the corresponding possible impacts can be generated;

[0107] In the second case, when the difference between the standard value corresponding to the physiological parameter and the current value of the physiological parameter is greater than zero;

[0108] If the user's current blood sugar is just consistent with the normal standard value or higher than the standard value, then the user needs to be reminded in time when choosing the type of dish, that is, the value of the physiological parameter is greater than or equal to the standard value to obtain at least one allowable value interval, and then the target threshold is determined according to the target value interval described by the difference, and the target threshold is the upper limit of the target value interval. If it exceeds this target threshold, then the third judgment result is obtained, and if the user's current blood pressure value is less than the target threshold, then the fourth judgment result is obtained.

[0109] In the case of the third judgment result, the prompt method may be the third level;

[0110] In the case of the fourth judgment result, the prompt method may be the second level;

[0111] Exemplarily, different prompt levels have different prompt methods. Taking blood sugar as an example, the first level of blood sugar reminder is the lowest, the second level of blood sugar reminder is higher than the second level, and so on. The third level of blood sugar reminder is the highest.

[0112] For example, the level setting criteria are as follows:

[0113] Level 1: Blood sugar is significantly higher than the standard value, which requires attention and some measures to be taken;

[0114] Level 2: Blood sugar is significantly higher than the standard value but does not reach the target threshold. Sugary foods need to be avoided immediately to avoid health risks.

[0115] Level 3: Blood sugar is higher than the preset target threshold, there is a serious health risk, and emergency measures need to be taken immediately.

[0116] Exemplarily, different levels correspond to different reminder methods;

[0117] The first level of reminders are:

[0118] Display prompt: A more obvious text prompt is displayed on the built-in display of the smart sofa: "Your blood sugar is higher than the standard value, please adjust your diet."

[0119] Voice prompts: A more obvious voice prompt is issued through the built-in speaker: "Please note that your blood sugar is higher than the standard value, please reduce the intake of high-sugar foods and increase the proportion of vegetables."

[0120] Vibration prompt: The sofa vibrates twice in a row to attract more attention of the user.

[0121] Mobile notification: Send a medium-priority notification to the user's smartphone with the following message: "Your blood sugar is higher than the standard value, please adjust your diet."

[0122] The second level of reminders are:

[0123] Display prompt: A warning text prompt is displayed on the built-in display of the smart sofa: "Your blood sugar is higher than the standard value, please reduce sugar intake!"

[0124] Vibration reminder: The sofa vibrates continuously for a few seconds to remind the user.

[0125] Mobile notification: Send a high-priority notification to the user's smartphone with the following content: "Warning! Your blood sugar is higher than the standard value, please reduce sugar intake."

[0126] Lighting cues: The lights around the sofa flicker to further attract the user's attention.

[0127] The third level of reminders is:

[0128] Display prompt: An emergency warning text prompt is displayed on the built-in display of the smart sofa: "Your blood sugar is very high and there is a health risk. Please take emergency measures immediately!"

[0129] Voice prompts: Emergency voice prompts are issued through the built-in speaker: "Emergency warning! Your blood sugar is very high, please contact your doctor or seek medical help immediately."

[0130] Vibration prompt: The sofa vibrates strongly and continuously until the user responds.

[0131] Mobile Notification: Send a top-priority notification to the user’s smartphone that reads: “Urgent Warning! Your blood sugar is very high. Please take emergency measures immediately.”

[0132] Light prompt: The lights around the sofa flash quickly and may be accompanied by an alarm sound.

[0133] Emergency Contact: The system automatically dials the preset emergency contact number to inform the user of the current condition and request help.

[0134] If the third level prompt message continues to be unprocessed, the smart sofa automatically starts the emergency response program to notify the emergency contact or medical service provider.

[0135] Through this hierarchical reminder mechanism, the smart sofa system can provide different levels of reminders according to the user's blood sugar level, thereby helping the user to take appropriate measures in a timely manner. This multi-level reminder method can not only effectively attract the user's attention, but also provide emergency support when necessary to ensure the user's health and safety.

[0136] For example, after outputting the prompt information, user feedback is collected:

[0137] After the system outputs the prompt information, the target user can be asked whether to accept the prompt through the interactive interface on the smart sofa (such as a touch screen, voice assistant, etc.), and the user can be requested to provide feedback.

[0138] Users can choose to confirm or ignore the prompt, and can also choose to provide more detailed feedback, such as their opinion on the prompt content or suggestions for improvement.

[0139] In addition, the embodiment of the present application can continuously monitor the actual behavior changes of the user through the camera device. If the user follows the prompt and changes the dining behavior, this positive feedback is recorded; if the user does not take action or continues the original behavior, it is marked as a situation that requires further intervention.

[0140] For example, based on the direct feedback provided by the user and the observed behavioral changes, the system can adjust the way or frequency of its prompts. For example, if a certain type of prompt is found to be particularly effective, then this type of prompt can be used preferentially in similar situations in the future.

[0141] For example, for users who repeatedly do not respond to prompts, the system may need to consider adopting more personalized communication methods or introducing external factors (such as support from family members) to strengthen the effect. The feedback mechanism can not only provide immediate guidance, but also adjust according to the user's response, thereby better helping users maintain healthy dining habits.

[0142] In some embodiments, in the process of detecting the user's physiological parameters according to the user's dining behavior, step 302 mentions quantifying the influence value of the physiological parameters of the target dining behavior according to the image;

[0143] So how to quantify the impact of the dining behavior on the user's physiological parameters? It is necessary to quantify the impact of the target dining behavior on the physiological parameters based on the user behavior detected by the camera device, that is, the image of the user dining taken by the camera device. The quantification method is as follows: Figure 5 Said:

[0144] Step 501: Identify the size of at least one food corresponding to the food picking behavior or the food ordering behavior from the image;

[0145] After the camera acquires an image of the user's dining behavior, the smart sofa performs image recognition processing on the image, and when it is recognized that the target dining behavior is a food picking behavior or a food ordering behavior, recognizes from the image the size of at least one food corresponding to the food picking behavior or the food ordering behavior;

[0146] When the smart sofa recognizes an image, it stores the correspondence between the food image and the name of the real object in advance, determines the food that the user has picked up or ordered, and then identifies the size of the food. In order to accurately measure the size of the food, a reference object with a known size is required, such as the diameter of a plate, the length and width of a table, or other items of standard size. The actual size of the food can be calculated based on the size of the reference object.

[0147] Exemplarily, the dimensions of a food typically include the length, width, and height (volume) of the food, and possibly its mass (weight).

[0148] For example, the size of the cake in the plate is identified by using the YOLOv5 model to detect the image and identify the reference objects: plate, fork and cake. YOLOv5 is an advanced target detection model for real-time recognition and location of objects in images or videos.

[0149] First, get the bounding box of the cake. Assume that the coordinates of the bounding box are (x, y, w, h), where (x, y) is the coordinate of the upper left corner, w is the width, and h is the height.

[0150] Assume the diameter of the dish is known, for example 20 cm. Use a perspective transform to transform the dish area in the image into a top-down view.

[0151] The actual length and width of the cake are calculated by the diameter of the plate and the aspect ratio of the bounding box. For example, if the width of the bounding box is 40% of the diameter of the plate, the actual width of the cake is 20 cm x 40% = 8 cm.

[0152] Similarly, the actual height of the cake is calculated by the height of the bounding box and the diameter of the plate. Assuming that the height of the bounding box accounts for 10% of the diameter of the plate, the actual height of the cake is 20 cm × 10% = 2 cm.

[0153] Volume: Assuming the cake is roughly rectangular in shape, the volume is length × width × height. For example, 8 cm × 8 cm × 2 cm = 128 cubic centimeters.

[0154] Step 502: Determine the content of the target component affecting the physiological parameter in the at least one food;

[0155] Determining the content of the target component that affects the physiological parameter in the at least one food according to the size of the at least one food and the unit components of each food;

[0156] For example, taking blood sugar as an example, the sugar content per unit volume of each food sold in the restaurant is pre-stored, and the total sugar content of the food selected by the user is obtained by multiplying the volume identified by the image recognition algorithm by the unit sugar content.

[0157] Step 503: Determine the impact value of the target dining behavior on the physiological parameter.

[0158] The influence value of the target dining behavior on the physiological parameter is determined according to the content of the target component and the mapping relationship between the preset component content and the influence value of the physiological parameter.

[0159] Exemplarily, through image recognition technology, it is recognized that the size of this chocolate cake is 5 cm×5 cm×2 cm.

[0160] Preset ingredient content to get the main nutritional components of this cake:

[0161] Total weight: 100 grams; sugar content: 30 grams; total carbohydrates: 60 grams; other ingredients (such as fat, protein, etc.) are negligible.

[0162] For example, there is a preset mapping relationship table between the component content and the blood sugar impact value. For example:

[0163] For every 10 grams of sugar consumed, blood sugar rises by about 10 mg / dL; for every 10 grams of carbohydrates consumed, blood sugar rises by about 8 mg / dL.

[0164] According to the mapping, every 10 grams of sugar causes blood sugar to rise by 10 mg / dL.

[0165] Therefore, 30 grams of sugar causes a rise in blood sugar: (30 / 10) x 10 mg / dL = 30 mg / dL.

[0166] Carbohydrate impact: The total amount of carbohydrates in the cake is 60 grams. According to the mapping relationship, every 10 grams of carbohydrates causes blood sugar to rise by 8 mg / dL. Therefore, 60 grams of carbohydrates causes blood sugar to rise by: (60 / 10) × 8 mg / dL = 48 mg / dL;

[0167] The total impact value is then calculated as follows:

[0168] Total blood sugar rise = sugar effect + carbohydrate effect = 30 mg / dL + 48 mg / dL = 78 mg / dL.

[0169] In summary, it can be concluded that after the user consumes this piece of chocolate cake, his blood sugar level is expected to rise by 78 mg / dL, which means the impact value is 78 mg / dL.

[0170] It should be understood that although Figure 2-5The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-5 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0171] In one embodiment, Figure 6 As shown, a schematic block diagram of the structure of a smart sofa is provided, which includes the following three modules: an acquisition module 601, a processing module 602, and a display module 603, wherein:

[0172] Acquisition module 601: when it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, current values ​​of the physiological parameters of the target user are monitored by the physiological parameter monitoring device, and images including the target dining behavior of the target user are captured by the camera device;

[0173] Processing module 602: judging whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value according to the current value of the physiological parameter and the image, and obtaining a judgment result, wherein the target threshold value is associated with a standard value corresponding to the physiological parameter;

[0174] Display module 603: when the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value, output prompt information, wherein the prompt information is used to prompt the target user to terminate the target dining behavior.

[0175] For the specific definition of the smart sofa, please refer to the definition of the dining interaction method based on the smart sofa above, which will not be repeated here. Each module in the above-mentioned smart sofa can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the terminal device in the form of hardware, or can be stored in the memory in the terminal device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0176] Another embodiment provides a computer-readable storage medium, which is used to store a computer program. The computer program includes instructions for implementing the method described in the embodiment of the present application. By installing the computer program on a computer, the computer can execute the corresponding method to perform dining interaction.

[0177] Another embodiment proposes that this embodiment provides a computer program product, which includes computer program codes. When these computer program codes are run on a computer, they enable the computer to implement the method proposed in the embodiment of the present application. In this way, users can complete the dining interaction function by using this computer program product.

[0178] For example, Figure 7 This is a schematic block diagram of the structure of another smart sofa provided in an embodiment of the present application, which includes the following four parts: processor 701, memory 702, communication interface 703, and bus 704. This system provides users with real-time health feedback and suggestions through the collaborative work of these components, helping them better manage their diet and health.

[0179] Processor 701 is the control center of the entire system and is responsible for performing various computing tasks and logical operations. It processes data collected from camera equipment and physiological parameter monitoring equipment (such as blood glucose meters) for analysis and calculation. For example, the processor can identify the type and amount of food consumed by the user, and combine the user's blood glucose data to evaluate the impact of diet on blood glucose. Based on the analysis results, the processor will make decisions, such as whether to issue a warning, adjust the sofa shape, etc. In addition, the processor is also responsible for executing instructions from the user or the system, controlling the work of other hardware components, and running various algorithms such as image recognition, data analysis, and health advice generation.

[0180] The memory 702 is used to store data and program code to ensure the normal operation of the system. It saves the raw data collected from the sensors, the processed data, and the historical records, which are essential for long-term tracking of the user's health status. The memory also stores the code of the operating system, applications, and various algorithms, enabling the system to perform complex tasks efficiently. In addition, the memory provides temporary storage space for temporarily storing intermediate results during data processing, and saving the user's personalized settings and system configuration information to ensure consistency and personalization of the user experience.

[0181] The communication interface 703 is responsible for exchanging data with other devices or systems to achieve data transmission and remote control. It transmits data with external devices (such as smartphones, servers, and other smart home devices) and receives remote control instructions from users, such as instructions sent through mobile phone applications. The communication interface is also connected to the Internet or other local area network to obtain updates, upload data, or receive cloud services. In addition, it also synchronizes data with other health monitoring devices to ensure data consistency and integrity, thereby providing a more comprehensive health management solution.

[0182] The bus 704 is a communication channel connecting various components and is responsible for transmitting data and signals between different components. It not only transmits data between the processor, memory, communication interface, and other possible components, but also transmits control signals and status information to ensure coordinated work between various components. In some cases, the bus may also participate in power management and distribution to ensure that each component obtains appropriate power supply so that the entire system can operate stably.

[0183] In summary, the overall workflow is as follows: First, the camera device captures the user's dining behavior image, and the physiological parameter monitoring device monitors the user's blood sugar level in real time. Then, the collected data is transmitted to the processor 701 through the communication interface 703. The processor processes the data and analyzes the user's eating habits and current blood sugar level. If it is detected that the user's blood sugar level is higher than the standard value but does not reach the high-risk threshold, the processor will further analyze the impact of the dining behavior and generate corresponding feedback information, such as warnings, suggestions, etc. Next, feedback information is sent to the user through the built-in display or speaker, and the data and feedback information are sent to the user's smartphone or other device through the communication interface 703. If necessary, the processor can also control the physical adjustment of the sofa, such as changing the seat angle. Finally, all relevant data and feedback information will be stored in the memory 702 for subsequent analysis and reference.

[0184] Through this structure and workflow, Figure 7 The structural example of the smart sofa shown can realize the dining interactive function of the smart sofa, helping users to better manage their diet and health, thereby improving the quality of life.

[0185] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0186] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor executes the instructions in the memory, and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0187] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present application.

[0188] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0189] In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0190] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0191] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0192] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0193] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the embodiment of the present application, which should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

Claims

1. A dining interactive method based on a smart sofa, characterized in that: A smart sofa applied to a dining interactive system, the system further comprising a camera device and a physiological parameter monitoring device, a communication connection being established between the smart sofa and the camera device and the physiological parameter monitoring device, the method comprising: When it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, the current value of the physiological parameter of the target user is monitored by the physiological parameter monitoring device, and an image including the target dining behavior of the target user is captured by the camera device; According to the current value of the physiological parameter and the image, determining whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold, and obtaining a determination result, wherein the target threshold is associated with a standard value corresponding to the physiological parameter; When the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold, a prompt message is output, where the prompt message is used to prompt the target user to terminate the target dining behavior.

2. The method according to claim 1, characterized in that The step of determining, based on the current value of the physiological parameter and the image, whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value, and obtaining a determination result includes: Obtaining a difference between a standard value corresponding to the physiological parameter and a current value of the physiological parameter; When the difference is greater than zero, quantifying the influence value of the physiological parameter of the target dining behavior according to the image; In the case where the influence value is greater than or equal to the difference value, a first judgment result is obtained, wherein the first judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value; When the influence value is smaller than the difference value, a second judgment result is obtained, and the second judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

3. The method according to claim 2, characterized in that The step of quantifying the impact of the target dining behavior on the physiological parameter according to the image includes: performing image recognition processing on the image, and when it is recognized that the target dining behavior is a food picking behavior or a food ordering behavior, recognizing from the image at least one size of food corresponding to the food picking behavior or the food ordering behavior; Determining the content of the target component that affects the physiological parameter in the at least one food according to the size of the at least one food and the unit components of each food; The influence value of the target dining behavior on the physiological parameter is determined according to the content of the target component and the mapping relationship between the preset component content and the influence value of the physiological parameter.

4. The method according to claim 2 or 3, characterized in that: The target threshold is a standard value corresponding to the physiological parameter.

5. The method according to claim 2, characterized in that: After obtaining the difference between the standard value corresponding to the physiological parameter and the current value of the physiological parameter, the method further includes: When the difference is less than or equal to zero, identifying at least one food corresponding to the target dining behavior according to the image; The judgment result is obtained according to whether the at least one food includes a target food, wherein the target food is a food whose influence value on the physiological parameter is greater than a preset influence threshold; In a case where the at least one food includes the target food, a third judgment result is obtained, wherein the third judgment result is used to indicate that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value; In the case that the target food is not included in the at least one food, a fourth judgment result is obtained, and the fourth judgment result is used to indicate that the target dining behavior is not a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value.

6. The method according to claim 5, characterized in that Before obtaining the judgment result according to whether the at least one food includes the target food, the method further includes: Acquire at least one value range that is allowed when the value of the physiological parameter is greater than or equal to the standard value; The target threshold is determined according to the target value interval described by the difference, and the target threshold is the upper limit value of the target value interval.

7. The method according to claim 1, characterized in that The output prompt information includes: Determining a target reminder level corresponding to the target threshold value according to the size of the target threshold value and a mapping relationship between a preset threshold range and a reminder level; Outputting prompt information corresponding to the target reminder level.

8. A dining interactive device based on a smart sofa, characterized in that: A smart sofa applied to a dining interactive system, the system further comprising a camera device and a physiological parameter monitoring device, a communication connection being established between the smart sofa and the camera device and the physiological parameter monitoring device, including: Acquisition module: when it is detected that there is a target user on the smart sofa and the target user is wearing the physiological parameter monitoring device, the current value of the physiological parameter of the target user is monitored by the physiological parameter monitoring device, and the image including the target dining behavior of the target user is captured by the camera device; Processing module: judging whether the target dining behavior is a behavior that causes the value of the physiological parameter to exceed a corresponding target threshold value according to the current value of the physiological parameter and the image, and obtaining a judgment result, wherein the target threshold value is associated with a standard value corresponding to the physiological parameter; Display module: when the judgment result indicates that the target dining behavior is a behavior that causes the value of the physiological parameter to exceed the corresponding target threshold value, output prompt information, wherein the prompt information is used to prompt the target user to terminate the target dining behavior.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; Wherein, the processor is configured to execute the instructions to implement the dining interaction method as described in any one of claims 1-7.

10. A storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the dining interaction method as described in any one of claims 1 to 7.

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