Interaction method and device of wearable equipment, wearable equipment and electronic equipment

Abstract

The invention discloses an interaction method and device of wearable equipment, the wearable equipment and electronic equipment, and belongs to the technical field of wearable equipment. The method comprises the following steps: determining personal information of a user in response to a first input of the user; acquiring physiological data, collected by the wearable device, of the user; and processing the personal information and the physiological data through a large language model to obtain feedback data corresponding to the user, and displaying the feedback data through the wearable device. According to the method, the feedback data displayed to the user is described by using the natural language, so that the user can more clearly and intuitively know the own health condition, the feedback data integrates the physiological data and personal information of the user, the personal condition of the user is better met, the user can obtain personalized health suggestions through the feedback data, and the user experience is improved. And the health condition is timely improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wearable devices, and particularly relates to an interaction method and device of a wearable device, the wearable device, and an electronic device. BACKGROUND

[0002] As an important tool for modern health monitoring, a health bracelet can collect monitoring data such as a user's heart rate, blood pressure, and exercise amount in real time. Such a device exhibits significant advantages in personal health management and medical assistance due to its portability and persistence.

[0003] However, the data collected by the health bracelet is usually presented in the form of simple numerical values or charts, which lacks an intuitive and easy-to-understand expression form. Moreover, the device can only provide data display functions and cannot provide professional health guidance suggestions according to data changes. This data output mode makes it difficult for users to obtain valuable health information from the monitoring data. SUMMARY

[0004] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides an interaction method and device of a wearable device, a wearable device, and an electronic device, which can make users more intuitively understand their own health conditions and provide personalized health suggestions to users through natural language descriptions.

[0005] In a first aspect, the present application provides an interaction method of a wearable device, which comprises:

[0006] determining personal information of a user in response to a first input of the user;

[0007] acquiring physiological data of the user collected by the wearable device;

[0008] processing the personal information and the physiological data through a large language model to obtain feedback data corresponding to the user, and displaying the feedback data through the wearable device.

[0009] According to the interaction method of the wearable device provided by the embodiments of the present application, the user's personal information and physiological data are combined for processing and analysis, feedback data can be generated and displayed to the user through the wearable device. The feedback data displayed to the user uses natural language description, which can make the user more clearly and intuitively understand their own health conditions. Moreover, the feedback data integrates the user's physiological data and personal information, which is more in line with the user's personal conditions. The user can obtain personalized health suggestions through the feedback data and improve their health conditions in a timely manner.

[0010] According to an embodiment of the present application, the feedback data comprises a data processing result of the physiological data and health guidance information inferred by the large language model based on the data processing result.

[0011] According to an embodiment of the present application, the health guidance information comprises an importance score, the importance score being used to represent the urgency of the health guidance information.

[0012] According to an embodiment of the present application, the health guidance information is determined according to the following steps:

[0013] Based on the personal information and the physiological data, a preset prompt word is determined;

[0014] The preset prompt word is input into the large language model to obtain the health guidance information inferred by the large language model based on the data processing result.

[0015] According to an embodiment of the present application, the physiological data comprises at least one of a physiological index change trend, a correlation between physiological indexes, a visual chart and a data summary.

[0016] According to an embodiment of the present application, the method further comprises:

[0017] In response to a second input of a user, interaction information of the user is obtained, and an interaction result of the interaction information is displayed through the wearable device;

[0018] The interaction result is obtained by processing the physiological data and the feedback data through the large language model.

[0019] In a second aspect, the present application provides an interaction device of a wearable device, the device comprising:

[0020] A first processing module, the first processing module being used to determine personal information of a user in response to a first input of the user;

[0021] An acquisition module, the acquisition module being used to acquire physiological data of the user collected by the wearable device;

[0022] A second processing module, the second processing module being used to process the personal information and the physiological data through a large language model to obtain feedback data corresponding to the user, and display the feedback data through the wearable device.

[0023] According to the interactive device of the wearable device provided in the embodiment of the present application, feedback data can be generated by combining the user's personal information with physiological data for processing and analysis, and displayed to the user through the wearable device. The feedback data displayed to the user by the device is described in natural language, which can enable the user to understand his or her own health status more clearly and intuitively. The feedback data integrates the user's physiological data and personal information, and is more in line with the user's personal condition. The user can obtain personalized health advice through the feedback data and improve his or her health status in a timely manner.

[0024] In a third aspect, the present application provides a wearable device, comprising:

[0025] An interactive device for a wearable device as described in the second aspect above.

[0026] According to one embodiment of the present application, the wearable device further includes:

[0027] An acquisition sensor, wherein the acquisition sensor is used to acquire the physiological data;

[0028] A human-computer interaction interface is used to obtain the first input and display the feedback data.

[0029] According to the wearable device provided in the embodiment of the present application, feedback data can be generated by combining user personal information with physiological data for processing and analysis, and displayed to the user through the wearable device. The feedback data displayed to the user by the wearable device is described in natural language, which can enable the user to understand his or her own health status more clearly and intuitively. In addition, the feedback data integrates the user's physiological data and personal information, and is more in line with the user's personal condition. The user can obtain personalized health advice through the feedback data and improve his or her health status in a timely manner.

[0030] In a fourth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the interaction method of the wearable device as described in the first aspect above is implemented.

[0031] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0033] Figure 1 1 is a flow chart of an interaction method for a wearable device provided in an embodiment of the present application;

[0034] Figure 2 is a structural schematic diagram of an interaction device of a wearable device provided by an embodiment of the present application;

[0035] Figure 3 is a structural schematic diagram of a wearable device provided by an embodiment of the present application;

[0036] Figure 4 is a work flow diagram of a wearable device provided by an embodiment of the present application;

[0037] Figure 5 is a structural schematic diagram of an electronic device provided by an embodiment of the present application.

[0038] Reference signs:

[0039] Interaction device 200, first processing module 210, acquisition module 220, second processing module 230,

[0040] Wearable device 300,

[0041] Electronic device 500, processor 501, memory 502. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art belong to the scope of protection of the present application.

[0043] The terms "first", "second", and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be exchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally a category and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" in the specification and claims indicates at least one of the connected objects, and the character " / ", generally indicates that the front and rear associated objects are in a "or" relationship.

[0044] The wearable device interaction method, the interaction device, the wearable device 300 and the electronic device provided by the embodiments of the present application will be described in detail below in combination with the drawings, through specific embodiments and application scenarios.

[0045] Currently, the data collected by health bracelets are usually presented in the form of simple numerical values ​​or charts, lacking intuitive and easy-to-understand expressions. Moreover, the bracelets can only provide data display functions and cannot provide professional health guidance suggestions based on data changes.

[0046] The embodiments of the present application provide an interactive method for a wearable device, which can enable users to understand their health status more intuitively through natural language descriptions and provide users with personalized health advice.

[0047] like Figure 1 As shown, the method includes: step 110, step 120 and step 130.

[0048] It is understandable that the wearable device 300 may refer to a device that can be worn on the human body and monitor, process or transmit physiological data, environmental information in real time or provide interactive functions.

[0049] In actual implementation, the wearable device 300 may include a smart watch, a health bracelet, or smart clothing.

[0050] Step 110: In response to the user's first input, determine the user's personal information.

[0051] The user refers to the user of the wearable device 300 , and the relevant indicators of the user can be measured through the wearable device 300 .

[0052] Personal information may include the user's physical characteristics, such as gender, age, height and weight, and the user's basic information, such as occupation and living habits.

[0053] The first input may be an instruction submitted by the user to the wearable device 300 for entering or modifying the user's personal information.

[0054] In this step, the first input can be in at least one of the following ways:

[0055] First, the first input may be a touch operation, including but not limited to a click operation, a slide operation, and a press operation.

[0056] In this embodiment, responding to the first input of the user may be responding to a touch operation of the user on the display area of ​​the wearable device 300 .

[0057] Secondly, the first input may be a physical key input.

[0058] In this embodiment, a physical button is provided on the body of the wearable device 300, and the response to the user's first input can be an operation in response to the user pressing the physical button; the first input can also be a combined operation of pressing multiple physical buttons at the same time.

[0059] Thirdly, the first input can be a voice input.

[0060] In this embodiment, the wearable device 300 can trigger the display of the input or modification interface of the personal information when receiving a voice such as "input personal information" or "modify personal information".

[0061] Of course, in other embodiments, the first input can also be in other forms, including but not limited to character input, etc., which can be determined according to actual needs, and the embodiments of the present application are not limited thereto.

[0062] In this step, in response to the first input of the user, the wearable device 300 can input or modify the personal information, and receive the data input by the user. After the user finishes inputting, the wearable device 300 can determine the personal information of the user based on the input data.

[0063] Step 120, acquiring physiological data of the user collected by the wearable device 300.

[0064] The physiological data refers to the index data collected by the wearable device 300, which can reflect the physiological activity state or physiological function state of the user, such as blood pressure, heart rate, step count, and sleep time, etc.

[0065] In this step, the physiological data of the user can be continuously acquired at a certain frequency to realize real-time health monitoring of the user.

[0066] Step 130, processing the personal information and the physiological data through a large language model to obtain feedback data corresponding to the user, and displaying the feedback data through the wearable device 300.

[0067] The large language model (Large Language Model, LLM) is a natural language processing model based on deep learning technology. The large language model can realize the understanding and generation ability of human language through training.

[0068] In actual execution, the large language model can be deployed in the cloud, and the wearable device 300 uses the large language model through calling.

[0069] In this step, the feedback data is the conclusion obtained by the large language model combining the personal information and conducting personalized analysis on the physiological data of the user, and the suggestion obtained by reasoning according to the conclusion.

[0070] It should be noted that the feedback data is in the form of natural language of human beings. Through the feedback data, the user can more clearly and intuitively understand the health status of himself and obtain relevant suggestions.

[0071] In this step, the large language model combines the user's personal information to determine the normal range and normal trend of the user's physiological indicators, and performs personalized analysis on the user's physiological data to obtain feedback data.

[0072] For example, for a 30-year-old male, the normal range of blood pressure is 75-115 mmHg, and the user's blood pressure in the physiological data is 90-130 mmHg, so the feedback data can be determined as "the user's blood pressure is high, and it is recommended to pay more attention to the risk of blood pressure disease".

[0073] For another example, the normal trend of blood pressure is the lowest at night after falling asleep and the highest from morning to morning, and the user's blood pressure in the physiological data rises at night, so the feedback data can be determined as "the user's blood pressure abnormally rises, and it is recommended to pay more attention to the risk of cardiovascular disease".

[0074] In this step, the large language model combines the user's personal information to determine the normal range and normal trend of the user's physiological indicators, and performs personalized analysis on the user's physiological data to obtain feedback data.

[0075] For example, the personal information shows that the user often works overtime, and the user's step count is low on weekdays in the physiological data, so the feedback data can be determined as "the user's activity level is insufficient on weekdays, which may be related to overtime work and work pressure, and it is recommended that the user take a walk after dinner".

[0076] In this step, the large language model combines the user's personal information to determine the normal range and normal trend of the user's physiological indicators, and performs personalized analysis on the user's physiological data to obtain feedback data.

[0077] For example, the higher the user's step count in the physiological data, the lower the sleep quality, so the correlation can be determined as a negative correlation between sleep quality and step count, and the user's step count is higher on rest days in the physiological data, so the feedback data can be determined as "the user's exercise will affect sleep quality, and it is recommended to appropriately reduce the exercise intensity on rest days and engage in relaxing activities before sleep".

[0078] In this step, after determining the feedback data, the feedback data is displayed through the wearable device 300.

[0079] In actual execution, the feedback data can be displayed through the wearable device 300, which can be directly displayed on the display area of the wearable device 300, or can be reminded to the user to view the feedback data through the wearable device 300 in the form of voice broadcast or vibration, or can be sent to the corresponding mobile application (APP).

[0080] In this step, the physiological data is processed and analyzed by the large language model combined with the personal information of the user to determine whether the physiological indicators of the user are within the normal range and whether they conform to the normal change trend, and also to determine the health degree of the daily behavior of the user and the correlation between the physiological data, etc., to obtain feedback data, which includes conclusions described in natural language and suggestions provided based on the conclusions. The feedback data displayed through the wearable device 300 enables the user to more clearly and intuitively understand the health status of the user and obtain personalized health suggestions to improve the health status in a timely manner.

[0081] In the related art, some health applications can provide health suggestions for users through data visualization and simple statistical analysis, for example, the Fitbit application displays charts of the steps, heart rate and sleep data of the user and provides some general health suggestions, but it is difficult for the user to accurately extract key information from complex data charts, and the suggestions provided by the related art are usually general and lack personalized analysis of the personal data of the user.

[0082] In the embodiment of the present application, the interaction method of the wearable device can obtain personal information and physiological data of the user, wherein the personal information can reflect the personal physical signs of the user, such as height, weight and age, etc., and according to the personal information, the reasonable range and trend of the indicators of the user under the physical sign can be determined to provide a reference standard for the evaluation of the physiological data. The method based on the large language model can perform personalized evaluation of the physiological data of the user based on the personal information to generate feedback data described in natural language and display it to the user through the wearable device 300. The feedback data includes conclusions such as the normal range and change trend analysis of the physiological indicators of the user, the health evaluation of the daily behavior and the correlation analysis between the physiological data, and also includes targeted health suggestions provided according to the conclusions. Compared with complex data and charts, the feedback data described in natural language can enable the user to more clearly and intuitively understand the health status of the user, and the feedback data generated based on the personal physical signs can more accurately reflect the health status of the user and provide more valuable suggestions. Compared with the related art, the interaction method of the wearable device in the embodiment of the present application integrates the physiological data and personal information of the user, and the feedback data displayed to the user is more in line with the personal condition of the user. The user can also obtain personalized health suggestions through the feedback data to improve the health status in a timely manner.

[0083] According to the interaction method of the wearable device provided in the embodiments of the present application, the user's personal information and physiological data are combined for processing and analysis, feedback data can be generated, and the feedback data is displayed to the user through the wearable device 300. The feedback data displayed to the user uses natural language description, so that the user can more clearly and intuitively understand the health status of the user, and the feedback data integrates the physiological data and personal information of the user, and is more in line with the personal condition of the user. The user can obtain personalized health suggestions through the feedback data, and improve the health condition in a timely manner.

[0084] In some embodiments, the feedback data includes a data processing result of the physiological data and health guidance information inferred by the large language model based on the data processing result.

[0085] The data processing result is a result obtained by the large language model performing personalized analysis on the physiological data in combination with the personal information of the user; and the health guidance information is a personalized health suggestion inferred by the large language model.

[0086] In actual execution, the data processing result can be an analysis result of a physiological index range and a change trend of the user.

[0087] For example, the user is a 30-year-old male, and the normal range of blood pressure of the user is 75-115 mmHg. In the physiological data of the user, the blood pressure is 90-130 mmHg. The data processing result of the large language model can be "the blood pressure of the user is high". The health guidance information inferred based on the data processing result can be "it is suggested that the user pay more attention to the risk of blood pressure disease".

[0088] For another example, the normal change trend of blood pressure is the lowest in the deep night after falling asleep and the highest from the morning to the morning. In the physiological data of the user, the blood pressure of the user rises at night. The data processing result of the large language model can be "the blood pressure of the user abnormally rises". The health guidance information inferred based on the data processing result can be "it is suggested that the user pay more attention to the risk of cardiovascular and cerebrovascular diseases".

[0089] In actual execution, the data processing result can be a health evaluation result of a daily behavior of the user.

[0090] For example, the personal information shows that the user often works overtime, and in the physiological data of the user, the user's step count is low on weekdays. The data processing result of the large language model can be "the activity amount of the user on weekdays is insufficient, which can be related to overtime work and work pressure". The health guidance information inferred based on the data processing result can be "it is suggested that the user take a walk after dinner".

[0091] In actual execution, the data processing result can be a correlation analysis result of the physiological data of the user.

[0092] For example, in the physiological data of a user, the higher the user's step count during the day, the lower the sleep quality of the user at night, and the higher the user's step count on rest days, the data processing result of the large language model can be "the user's exercise will affect sleep quality", and the health guidance information inferred based on the data processing result can be "suggesting to appropriately reduce the exercise amount on rest days and to perform relaxation activities before sleep".

[0093] In this embodiment, the health guidance information in the feedback data can provide an effective guidance scheme for the user to improve his / her health, and the data processing result serves as the inference basis of the health guidance information, and the health guidance information is displayed to the user together with the data processing result, so that the user can more clearly understand the source of the health guidance information, and it is helpful for the user to master his / her health status.

[0094] In some embodiments, the health guidance information includes an importance score, and the importance score is used to represent the urgency of the health guidance information.

[0095] In this embodiment, the importance score can be a determined score in the range of 0-10, and the closer the score is to 10, the higher the urgency of the health guidance information, and the closer the score is to 0, the lower the urgency of the health guidance information.

[0096] For example, for the health guidance information with the content of "suggesting the user to go to the hospital for further diagnosis and to seek medical treatment in time", the importance score can be 9.

[0097] For another example, for the health guidance information with the content of "suggesting the user to reasonably arrange rest time and reduce staying up late", the importance score can be 7.

[0098] For still another example, for the health guidance information with the content of "suggesting the user to walk properly after dinner", the importance score can be 5.

[0099] In actual execution, the health guidance information with a higher importance score can be pushed as a focus.

[0100] The way of focusing pushing can be at least one of the following ways:

[0101] Firstly, the way of focusing pushing can be highlighting, for example, increasing the font size of the health guidance information, changing the font color of the health guidance information, and highlighting the health guidance information.

[0102] Secondly, the way of focusing pushing can be multiple pushing, for example, repeatedly pushing the health guidance information 3 times through the wearable device 300 or the mobile phone APP.

[0103] Thirdly, the way of the key push can be the interaction with the user, for example, continuously displaying the health guidance information on the display interface of the wearable device 300 until the user clicks the confirmation button to normally display other content.

[0104] Of course, in other embodiments, the way of the key push can also be other forms, which can be determined according to actual needs, and the embodiments of the present application do not limit this.

[0105] In this embodiment, by scoring the importance of each suggestion in the health guidance information, the importance and urgency of the corresponding suggestion can be quantified, and for the suggestion with high importance score, the key push is performed, which can remind the user to pay attention to the health guidance information that has greater or more urgent impact on the user's health.

[0106] In some embodiments, the health guidance information is determined according to the following steps:

[0107] Based on the personal information and physiological data of the user, a preset prompt word is determined;

[0108] The preset prompt word is input into the large language model to obtain the health guidance information inferred by the large language model based on the data processing result.

[0109] It can be understood that the large language model can understand the data and language input into the model, and generate the corresponding result according to the input content, and the input content can be the prompt word of the large language model.

[0110] In this embodiment, the preset prompt word has a pre-written template part, the personal information and physiological data of the user are added to the corresponding position in the template, and the preset prompt word is input into the large language model to obtain the health guidance information.

[0111] For example, the template part of the preset prompt word can be,

[0112] "Personal information: (to be input)

[0113] Physiological data: (to be input)

[0114] Please generate a data processing result based on the above information, the data processing result should include the analysis result of the user's physiological index range and trend, the health evaluation result of daily behavior and the correlation analysis result of physiological data, and at least 10 personalized health guidance information is generated based on the data processing result, please ensure that the health guidance information is practical and targeted, which can help the user better understand his own health status and obtain specific improvement suggestions and guidance schemes, each health guidance information should include the following contents:

[0115] 1. The specific content of the health guidance information;

[0116] 2, the corresponding reasoning basis of the health guidance information in the data processing result;

[0117] 3, the importance score of the health guidance information (0-10 points)”.

[0118] In this embodiment, based on the personal information and physiological data of the user, the preset prompt word is determined, and the preset prompt word is taken as the input of the large language model, which can make the large language model understand the task content more quickly and accurately, and improve the accuracy of the health guidance information output by the large language model.

[0119] In some embodiments, the physiological data includes at least one of physiological index change trend, physiological index correlation, visual chart and data summary.

[0120] In this embodiment, the physiological data includes the interaction device 200 data of the physiological indicators collected by the wearable device 300, such as blood pressure, heart rate, step count and sleep time, etc., and also includes the content obtained after processing and analysis based on the interaction device 200 data, such as physiological index change trend, physiological index correlation, visual chart and data summary, etc.

[0121] Among them, the data summary includes the maximum value, minimum value and average value of each physiological index of the user.

[0122] For example, for the heart rate index, the data summary can be: average value: 72bpm; minimum value: 60bpm; maximum value: 90bpm.

[0123] For example, for the daily step count index, the data summary can be: average value: 8000 steps / day; minimum value: 3000 steps; maximum value: 12000 steps.

[0124] In this embodiment, the physiological index change trend is the change trend of each physiological index of the user in a certain period of time.

[0125] For example, for the heart rate index, the physiological index change trend can be that the user's heart rate is higher on weekdays and lower on weekends this week.

[0126] For example, for the daily step count index, the physiological index change trend can be that the user's step count is higher on weekends and lower on weekdays this week.

[0127] In this embodiment, the physiological index correlation is the interaction relationship between different physiological indexes of the user in the physiological activity process of the user.

[0128] For example, for the two physiological indexes of heart rate and daily step count, the physiological index correlation can be that the heart rate and the step count are positively correlated (the correlation coefficient is 0.7).

[0129] For example, the correlation between sleep quality and step count can be negative (correlation coefficient is -0.5).

[0130] In this embodiment, the visualization chart is a result of presenting physiological indicators in a graphical manner. The visualization chart can be in the form of a line chart, a column chart, a heat map, or a waveform chart, etc., which intuitively displays the trend of the user's physiological indicators over time or state.

[0131] It should be noted that in the process of obtaining the physiological indicator trend, the correlation between physiological indicators, the visualization chart, and the data summary, etc. based on the data processing and analysis of the interaction device 200, the data of the interaction device 200 can be filtered, aligned, and adjusted in time.

[0132] The data filtering can exclude invalid or abnormal data points in the data of the interaction device 200.

[0133] For example, if there is an obviously incorrect value in the heart rate indicator (e.g., heart rate exceeding 200 bpm), it can be filtered out.

[0134] The data alignment can align the data of different physiological indicators by time and date.

[0135] For example, the heart rate indicator is sampled every 5 minutes, the step count indicator is sampled every minute, and the sleep time indicator is recorded by day. The data alignment can unify these indicators to the same date and time framework.

[0136] The time adjustment can adjust the date of the sleep time indicator to the second day of the corresponding daytime activity.

[0137] For example, if the user goes to sleep at 10 pm, the sleep time indicator will be associated with the date of the second day.

[0138] In this embodiment, the data filtering, data alignment, and time adjustment of the interaction device 200 data of the physiological indicators collected by the wearable device 300 can improve the accuracy of the subsequent data processing and analysis process. After data processing and analysis, physiological data including physiological indicator trends, correlations between physiological indicators, visualization charts, and data summaries, etc. can be obtained, which can enable the user to quickly understand the basic conditions of their physiological indicators.

[0139] In some embodiments, the interaction method of the wearable device further includes:

[0140] In response to the second input of the user, the interaction information of the user is obtained, and the interaction result of the interaction information is displayed through the wearable device 300.

[0141] The interaction result is obtained by the large language model based on the physiological data and the feedback data.

[0142] In this embodiment, the second input can be at least one of the following modes:

[0143] Firstly, the second input can be a touch operation, including but not limited to a click operation, a sliding operation, a pressing operation, etc.

[0144] In this embodiment, in response to the second input of the user, the touch operation of the user on the display area of the wearable device 300 can be performed.

[0145] Secondly, the second input can be an entity key input.

[0146] In this embodiment, the wearable device 300 is provided with an entity key on the body, and in response to the second input of the user, the operation of pressing the entity key by the user can be performed; the second input can also be a combination operation of pressing multiple entity keys at the same time.

[0147] Thirdly, the second input can be a voice input.

[0148] In this embodiment, when the wearable device 300 receives a voice such as “start a dialogue” or “enter a dialogue mode”, the wearable device 300 can trigger the display of the interaction interface.

[0149] Of course, in other embodiments, the second input can also be in other forms, including but not limited to character input, etc., which can be determined according to actual needs, and the embodiments of the present application are not limited thereto.

[0150] In this embodiment, in response to the second input of the user, the interaction information of the user can be obtained, and the interaction information of the user can be a question raised by the user to the wearable device 300 based on physiological data, feedback data, and the health status of the user.

[0151] In actual execution, the question input by the user in the interaction interface, i.e., the interaction information of the user, can be obtained by setting the interaction interface in the wearable device 300.

[0152] In this embodiment, after obtaining the interaction information of the user, based on the physiological data and the feedback data of the user, the large language model can make a relevant reply to the interaction information of the user, i.e., output the interaction result to the user.

[0153] For example, in response to the second input of the user, the wearable device 300 displays an interaction interface and acquires the interaction information "why is my sleep quality not good" input by the user in the interaction interface. The large language model can generate a corresponding interaction result "according to your data, your sleep quality is negatively correlated with the number of steps, which may be due to increased activity leading to physical fatigue and affecting sleep quality. It is recommended that you perform some relaxation activities such as yoga or meditation before sleeping" based on the physiological data and feedback data of the user, and display the result to the user in the interaction interface.

[0154] In actual execution, the interaction interface can be set in the mobile phone APP to facilitate user operation and result display. In addition, the interaction result can be displayed to the user in the form of text combined with visual charts, making the interaction result more intuitive and easy for the user to understand.

[0155] In this embodiment, in response to the second data of the user, the interaction information of the user can be acquired, and a natural language description of a targeted reply to the interaction information can be generated by the large language model based on the physiological data and feedback data of the user. The doubts of the user about the physiological health status of the user can be answered in a timely manner, and feasible suggestions and guidance can be provided.

[0156] The interaction method of the wearable device provided in the embodiments of the present application can be executed by the interaction device 200 of the wearable device. In the embodiments of the present application, the interaction method of the wearable device is executed by the interaction device 200 of the wearable device as an example to illustrate the interaction device 200 of the wearable device provided in the embodiments of the present application.

[0157] The embodiments of the present application further provide an interaction device 200 of a wearable device.

[0158] As shown in Figure 2 The interaction device 200 of the wearable device includes a first processing module 210, an acquisition module 220, and a second processing module 230.

[0159] The first processing module 210 is configured to determine the personal information of the user in response to the first input of the user.

[0160] The acquisition module 220 is configured to acquire the physiological data of the user collected by the wearable device 300.

[0161] The second processing module 230 is configured to process the personal information and the physiological data by the large language model to obtain the feedback data corresponding to the user, and display the feedback data by the wearable device 300.

[0162] According to the wearable device interaction apparatus 200 provided in the embodiment of the present application, the user personal information and the physiological data are combined for processing and analysis, feedback data can be generated and displayed to the user through the wearable device 300. The feedback data displayed to the user by the apparatus uses natural language description, which can make the user more clearly and intuitively understand the health condition of the user, and the feedback data integrates the physiological data and the personal information of the user, which is more in line with the personal condition of the user. The user can obtain personalized health suggestions through the feedback data to improve the health condition in time.

[0163] The wearable device interaction apparatus 200 in the embodiment of the present application can be an apparatus with an operating system. The operating system can be an Android operating system, an IOS operating system or other possible operating systems, which are not limited in the embodiment of the present application.

[0164] The wearable device interaction apparatus 200 provided in the embodiment of the present application can realize the processes of the wearable device interaction method embodiment, which will not be repeated here.

[0165] The embodiment of the present application further provides a wearable device 300, as shown in the figure, the wearable device 300 includes the wearable device interaction apparatus 200 described above. Figure 3

[0166] According to the wearable device 300 provided in the embodiment of the present application, the user personal information and the physiological data are combined for processing and analysis, feedback data can be generated and displayed to the user through the wearable device 300. The feedback data displayed to the user by the apparatus uses natural language description, which can make the user more clearly and intuitively understand the health condition of the user, and the feedback data integrates the physiological data and the personal information of the user, which is more in line with the personal condition of the user. The user can obtain personalized health suggestions through the feedback data to improve the health condition in time.

[0167] In some embodiments, the wearable device 300 further includes a collection sensor and a human-computer interaction interface.

[0168] The collection sensor is configured to collect physiological data.

[0169] The human-computer interaction interface is configured to obtain the first input and display the feedback data.

[0170] In some embodiments, the human-computer interaction interface is further configured to obtain the interaction information of the user and display the interaction result of the interaction information in response to the second input.

[0171] In this embodiment, the human-computer interaction interface can include a user input box, a system answer area and a visual chart display area. ​

[0172] The user input box can be used to obtain the interactive information input by the user; the system answer area can be used to display the text part of the interactive result; and the visual chart display area can be used to display the chart part of the interactive result.

[0173] A specific embodiment will be introduced below.

[0174] As shown in Figure 4 , after the collection sensor in the wearable device 300 collects the physiological data of the user, the data can be sent to the data preparation module. The data preparation module analyzes the data of the interactive device 200 and obtains the data processing result of the user (i.e., the data summary, trend analysis result and correlation analysis result in Figure 4 ).

[0175] Then, the insight generation module calls the large language model (i.e., the LLM model in Figure 4 ) to analyze the data processing result in combination with the personal information of the user and obtains the feedback data of the user.

[0176] Finally, the man-machine interaction interface (i.e., the dialogue interface module in Figure 4 ) in the wearable device 300 replies to the interactive information of the user based on the physiological data, personal information, data processing result and feedback data, and outputs the interactive result to the user.

[0177] In some embodiments, as shown in Figure 5 , the present application also provides an electronic device 500, which includes a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. The program is executed by the processor 501 to implement the processes of the above-mentioned wearable device interaction method embodiments, and can achieve the same technical effects. To avoid repetition, details are not repeated here.

[0178] It should be noted that the electronic device in the embodiments of the present application includes the mobile electronic device and the non-mobile electronic device described above.

[0179] The present application also provides a non-transitory computer readable storage medium having a computer program stored thereon. The computer program is executed by a processor to implement the processes of the above-mentioned wearable device interaction method embodiments, and can achieve the same technical effects. To avoid repetition, details are not repeated here.

[0180] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0181] The embodiment of the present application further provides a computer program product comprising a computer program which, when executed by a processor, implements the interaction method of the wearable device.

[0182] The processor is the processor in the electronic device in the above embodiment. The readable storage medium comprises a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0183] The embodiment of the present application further provides a chip, which comprises a processor and a communication interface, wherein the communication interface is coupled with the processor, the processor is used to run programs or instructions, and realizes each process of the interaction method of the wearable device, and achieves the same technical effects. To avoid repetition, details are not described herein.

[0184] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0185] It should be noted that, in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the present application is not limited to the order of performing the functions shown or discussed, but can also include performing the functions in a substantially simultaneous manner or in reverse order, for example, the described method can be performed in an order different from that described, and various steps can be added, omitted or combined. In addition, the features described with reference to certain examples can be combined in other examples.

[0186] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk, etc.), and includes a plurality of instructions for making a terminal (which can be a mobile phone, computer, server or network device, etc.) execute the method described in each embodiment of the present application.

[0187] The embodiments of the present application are described above with reference to the drawings, but the present application is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative, not restrictive, and a person of ordinary skill in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, all of which belong to the protection of the present application.

[0188] In the description of the present specification, the description referring to the terms "one embodiment", "some embodiments", "exemplary embodiment", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the exemplary description of the above terms does not necessarily mean the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0189] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made thereto without departing from the principles and spirit of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A wearable device interaction method, characterized in that: include: In response to a first input from a user, determining personal information of the user; Acquiring physiological data of the user collected by the wearable device; The personal information and the physiological data are processed through a large language model to obtain feedback data corresponding to the user, and the feedback data is displayed through the wearable device.

2. The wearable device interaction method according to claim 1, characterized in that: The feedback data includes a data processing result of the physiological data and health guidance information inferred by the large language model based on the data processing result.

3. The wearable device interaction method according to claim 2, characterized in that: The health guidance information includes an importance score, and the importance score is used to represent the urgency of the health guidance information.

4. The wearable device interaction method according to claim 2, characterized in that: The health guidance information is determined according to the following steps: Determining a preset prompt word based on the personal information and the physiological data; The preset prompt words are input into the large language model to obtain the health guidance information inferred by the large language model based on the data processing result.

5. The wearable device interaction method according to claim 1, characterized in that: The physiological data includes at least one of a physiological indicator change trend, a correlation between physiological indicators, a visualization chart, and a data summary.

6. The wearable device interaction method according to claim 1, characterized in that: The method also includes: In response to a second input from the user, acquiring interaction information of the user, and displaying an interaction result of the interaction information through the wearable device; The interaction result is obtained by processing the large language model based on the physiological data and the feedback data.

7. An interactive device for a wearable device, characterized in that: include: a first processing module, configured to determine personal information of the user in response to a first input of the user; an acquisition module, configured to acquire physiological data of the user collected by the wearable device; The second processing module is used to process the personal information and the physiological data through a large language model to obtain feedback data corresponding to the user, and display the feedback data through the wearable device.

8. A wearable device, characterized in that: include: The interactive device for a wearable device as claimed in claim 7.

9. The wearable device according to claim 8, wherein: Also includes: An acquisition sensor, wherein the acquisition sensor is used to acquire the physiological data; A human-computer interaction interface is used to obtain the first input and display the feedback data.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the wearable device interaction method according to any one of claims 1 to 6 when executing the computer program.

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